Frequently Asked Questions

Below is a list of our most frequently asked questions (FAQs) about cliexa intended to serve as a knowledge base for patients and primary care providers. For more information about cliexa or additional support, please contact us.
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    Healthcare AI refers to the application of artificial intelligence in various healthcare processes, such as diagnostics, treatment planning, and administrative workflows. AI helps process large amounts of clinical data to generate actionable insights and predictive models for better patient care. Healthcare AI plays a crucial role in the medical industry by streamlining operations and enhancing patient experiences. Learn more about cliexa’s AI-driven platforms.

    AI improves patient outcomes by enabling faster, data-driven clinical decisions, early detection of diseases, personalized treatment plans, and continuous patient monitoring. This leads to more accurate diagnoses, timely interventions, and overall improved care quality. AI-based patient engagement tools facilitate proactive care management. Explore our predictive AI models.

    AI enhances clinical decision-making by analyzing complex medical data quickly, providing predictive insights, identifying trends, and suggesting treatments based on patient history and current data. It helps reduce human error and ensures that clinical decisions are evidence-based. Story health transformations, powered by AI, help streamline clinical workflows. Learn how cliexa supports clinical decision-making.

    AI assists healthcare providers by analyzing patient data in real-time to generate diagnostic insights, recommend personalized treatments, and optimize care pathways. It integrates with electronic health records (EHR) to provide ongoing support throughout the patient journey. The role of artificial intelligence in healthcare is constantly expanding, making it easier for providers to deliver effective care. 

    Yes, AI in healthcare is built with strict protocols for accuracy, data privacy, and safety. It undergoes rigorous validation processes to ensure its efficacy. AI enhances the capabilities of healthcare providers, ensuring safer, more effective care delivery. Stay updated with healthcare AI news and developments that ensure compliance and effectiveness. See how AI enhances patient safety.

    Challenges include integrating AI with existing healthcare systems, ensuring data privacy and security, and managing the complexity of medical data. Overcoming these requires robust interoperability and AI solutions tailored for healthcare settings. AI-driven healthcare solutions must address these barriers to be effectively implemented. Learn how cliexa addresses these challenges.

     

    AI systems like cliexa use advanced encryption and follow HIPAA compliance standards to ensure patient data is securely processed. These platforms prioritize data protection while ensuring that real-time analytics are possible without compromising privacy. Discover how our patient engagement tools maintain high standards of security and privacy. 

     

    Healthcare IT encompasses the tools and technologies that manage healthcare information, including EHRs, patient portals, and diagnostic systems. AI integrates with healthcare IT to analyze, automate, and optimize clinical data, enabling improved interoperability and decision-making. Story health integration ensures that AI complements healthcare IT for better patient outcomes. 

    cliexa’s platform integrates seamlessly with existing IT infrastructures, enhancing them with AI capabilities such as predictive modeling, real-time patient monitoring, and automated documentation, ensuring streamlined workflows for healthcare teams. The role of artificial intelligence in healthcare IT is crucial for enabling smarter data management and decision-making.  Enabled through cliexaTrac, and cliexaDiagnostics.

     

    Interoperability issues often arise due to siloed healthcare data systems. AI platforms like cliexaConnect solve this by enabling bi-directional data exchange between systems, structuring clinical data, and automating real-time insights, helping providers deliver cohesive care. Stay informed with the latest healthcare AI news on interoperability and digital health advancements. Explore cliexa’s interoperability features: cliexaConnect.

     

    Healthcare IT systems are vital for managing and analyzing patient data. They ensure that data is accurately recorded, securely stored, and accessible for both clinicians and patients. This enables AI tools to extract meaningful insights, leading to improved patient outcomes. The healthcare industry increasingly relies on AI-driven IT systems to maintain data integrity and precision. Learn more: cliexaConnect.

     

    With advancements in healthcare IT and AI, real-time data processing is possible through platforms like cliexaConnect. Clinicians can instantly access updated patient information, enabling faster diagnoses and timely treatment adjustments. AI tools play a crucial role in enhancing real-time data processing and improving clinical decision-making. Learn more about real-time processing: cliexaTraccliexaConnect.

     

    Digital health involves the use of technology, such as AI and mobile apps, to enhance healthcare delivery. It is transforming how care is provided by improving accessibility, patient engagement, and coordination across healthcare settings. Innovations in digital health continue to reshape healthcare, making it more efficient and connected. Learn more about cliexa’s digital health platforms: cliexaTrac.

     

    AI-powered digital health solutions benefit patients by offering personalized and proactive care. Providers gain efficiency, improved decision-making capabilities, and automated administrative tasks, allowing them to focus more on patient care. These solutions bridge the gap between patients and providers, enhancing communication and outcomes. Explore more: cliexaTraccliexaAI.

     

    A comprehensive digital health platform includes patient engagement tools, AI-driven analytics, EHR interoperability, and administrative automation. cliexa also offers predictive analytics for improved clinical outcomes. AI plays a vital role in making digital health platforms more effective and cohesive. Learn more: cliexaTraccliexaDiagnostics.

     

    Digital health platforms, such as cliexaTrac, provide patients with easy access to their health data, real-time condition monitoring, and seamless communication with healthcare providers, improving overall engagement and involvement in care. Ongoing innovations in digital health continue to enhance patient experiences. Learn more: cliexaTrac.

     

    AI-powered digital health services include remote patient monitoring, automated diagnostics, predictive risk modeling, and personalized treatment recommendations. cliexa provides these services to streamline care and improve patient outcomes. Explore more AI-powered services: cliexaDiagnostics, cliexaAI

    Challenges include integrating digital health solutions with existing systems, ensuring patient data security, and training healthcare staff. cliexa addresses these challenges by offering user-friendly platforms with strong security measures and seamless system integration. Learn how cliexa helps: cliexaConnect.

     

    Predictive risk modeling involves using AI algorithms to analyze patient data and predict health risks, allowing for early intervention and personalized care. These models are vital for optimizing healthcare delivery and improving patient outcomes. Learn more: cliexaAI.

     

    cliexa’s AI-powered platform analyzes chronic care data to predict disease progression, identify risks, and offer actionable insights for early interventions. This enhances chronic care management by enabling healthcare providers to make informed decisions. Explore more: cliexaAI.

    AI predictive models can assess risks for chronic conditions such as heart disease, diabetes, kidney disease, and opioid use disorder. cliexa’s models are designed to predict complications and guide treatment plans for these conditions. Learn more: cliexaAI.

     

    AI’s accuracy in predicting health outcomes depends on the quality of the data and algorithms used. cliexa’s AI models have been validated through clinical studies, demonstrating high accuracy in risk prediction.

    Predictive risk modeling gives healthcare providers actionable insights based on real-time data, helping them reduce risks and optimize care plans for better patient outcomes. These models are integral to improving decision-making in healthcare.

    cliexa uses structured clinical data, real-time monitoring data, and historical health records to train its AI models, ensuring comprehensive insights and accurate predictions. Learn more about cliexa’s data-driven models.

     

    Generative AI creates new content, such as clinical notes or treatment plans, based on existing healthcare data. It enhances workflows by automating documentation and offering new insights based on patient records. Generative AI’s applications in the medical industry streamline administrative tasks and support clinical decisions. Learn more about generative AI in cliexa.

     

    Generative AI automates the creation of clinical documentation, reducing the administrative burden on healthcare providers. It can generate SOAP notes, encounter reports, and personalized treatment plans from structured data. These capabilities form part of comprehensive healthcare solutions that enhance clinical productivity and patient care. Explore automated documentation.

     

    Generative AI can create tailored treatment recommendations by analyzing patient data and clinical guidelines, helping healthcare providers make more informed decisions. It can also flag potential risks or treatment inefficiencies. Story health applications of AI offer new ways to interpret diagnostic information and streamline treatment planning. Learn more about AI in Healthcare.

    While generative AI offers many benefits, challenges include ensuring the accuracy of generated content, managing data privacy, and avoiding over-reliance on AI-generated recommendations without clinician oversight. Healthcare AI news often highlights ongoing developments to mitigate these risks and enhance AI reliability. Learn how cliexa mitigates these risks.

     

    Yes, generative AI analyzes patient-specific data to suggest personalized treatment plans, aligning with the latest clinical guidelines and patient history for optimal outcomes. These personalized recommendations are integral to patient engagement tools that foster improved patient-provider communication. Explore AI-powered treatment recommendations.

     

    Healthcare organizations can use AI to streamline administrative tasks, optimize resource allocation, and improve clinical workflows by automating data analysis, documentation, and predictive insights. The role of artificial intelligence in healthcare extends to supporting providers with better decision-making and smoother operations. Learn how cliexa enhances efficiency.

    AI reduces costs by minimizing human error, optimizing patient care workflows, reducing claim denials, and improving operational efficiency. It also helps identify cost-effective treatment plans through predictive modeling. Many healthcare AI news sources highlight the economic impact AI has on reducing overall healthcare expenses. Discover how AI saves costs.

     

    cliexa’s platform supports providers by offering real-time insights, automating documentation, integrating with existing EHR systems, and providing predictive analytics to enhance patient care and optimize clinical workflows. Healthcare AI integration with platforms like cliexaTrac ensures a seamless experience for providers and patients. Explore cliexa’s AI capabilities.

     

    Many healthcare organizations using AI have reported improved patient outcomes, more efficient workflows, and cost savings. cliexa’s clients have seen significant improvements in chronic disease management, diagnostics, and patient engagement. These success stories illustrate the impact of story health innovations in real-world clinical settings.

     

    Common barriers include integration challenges, data privacy concerns, and staff training. These can be overcome by choosing interoperable AI platforms, like cliexaConnect, that ensure compliance and provide easy-to-use tools for healthcare teams. Healthcare solutions that prioritize ease of use and robust security can facilitate smoother adoption. Explore integration solutions: cliexaConnect.

     

    Providers should look for platforms that offer seamless EHR integration, real-time data processing, predictive insights, and compliance with healthcare regulations like HIPAA. Choosing a platform with robust patient engagement tools can further enhance patient-provider interactions and improve care quality. cliexa’s platforms, cliexaTrac, cliexaProspect, provide these features, ensuring a smooth transition to AI-powered care.

    Traditional clinical prediction models, while built with the best intentions, often fall short. They tend to be rigid—based on limited data from a specific population—and are rarely adaptable to diverse real-world settings. Once developed, these models are “locked in,” requiring years of validation before they can be deployed. By the time they reach the bedside, the healthcare landscape has often shifted with new medications, research, or population needs. These models lack the agility, personalization, and feedback loops necessary to remain relevant. cliexa’s platform was built to overcome exactly these shortcomings.

    The initial implementation of a new clinical prediction model can typically be completed within approximately one month. However, training the AI to learn and optimize its predictive capabilities is an ongoing process that depends heavily on the volume, quality, and diversity of available data. As more patient data is collected and outcomes are observed, the model continues to evolve, improving accuracy and clinical relevance over time.

    There is no universal legal requirement to retain audio recordings generated by ambient AI in clinical settings, and most systems intentionally avoid retaining them to minimize liability and simplify compliance. These recordings, if temporarily stored, are considered protected health information (PHI) and must meet the same HIPAA security and privacy standards as other clinical data, but they are typically purged within 24–72 hours once the transcript is generated. On the other hand, transcripts produced from these recordings are usually classified as part of the official medical record and are subject to state-specific medical record retention laws. HIPAA defers to state requirements in this regard, meaning the retention timeline for transcripts can vary significantly—for example, five years after last contact in Florida versus seven years in Texas. Whether the transcript documents a standard office visit, a surgical consultation, or another clinical interaction, it generally must be preserved according to the same rules governing medical documentation. Additionally, organizations must ensure that proper patient consent is obtained before recording clinical encounters. This consent process must comply with both organizational policies and state laws regarding audio capture—some states, like California and Florida, require all parties involved to consent to recording, while others follow one-party consent rules. Overall, while transcript retention is a compliance requirement in most cases, audio retention is not and is often viewed as a security risk rather than a legal necessity.

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    cliexa helps physicians and clinical teams quickly turn fragmented patient data into actionable plans for better health using advanced AI technology. Seamlessly integrating with electronic medical records and clinical data sources, cliexa operates in the background, streamlining data without the need for additional tools. Our healthcare solutions enable health systems to continuously evolve and innovate by leveraging clinical data in real-time, powered by AI, without disrupting current workflows. Learn more: About Us.

    cliexa stands for CLInical EXcellence and Algorithms. Our name embodies our commitment to transforming healthcare through advanced technology. By integrating clinical insights, excellence in patient care, and cutting-edge algorithms, we provide a robust AI-powered platform that engages, integrates, and delivers actionable insights to clinical teams and their partners. Learn more: Who We Are.

    The lowercase “c” in “cliexa” emphasizes our focus on excellence in clinical outcomes while maintaining a modern and approachable brand image. This reflects our commitment to setting new standards in healthcare, prioritizing innovation and clinical excellence. Learn more: Who We Are.

    cliexa’s mission is to revolutionize healthcare by providing innovative, AI-powered platforms that enhance patient engagement, streamline clinical workflows, and offer predictive analytics to improve care outcomes. Learn more: Our Mission.

    cliexa’s vision is to enable innovation and AI-powered solutions that personalize care and improve patient outcomes. Learn more: Our Vision.

    cliexa operates with transparency, integrity, and collaboration, focusing on personalized patient care. These values keep us at the forefront of healthcare innovation while ensuring patient-centered care. Learn more: Our Values.

    cliexaTrac is a patient engagement platform that enables real-time monitoring and interaction. It integrates with existing systems, allowing patients to track symptoms and share real-time data with healthcare providers. 

    cliexaConnect enables seamless bi-directional EMR connectivity, ensuring efficient clinical and administrative data exchange across multiple systems. Learn more: cliexaConnect.

    cliexaDiagnostics pulls data from multiple sources and generates SOAP notes and encounter summaries automatically, giving healthcare providers real-time diagnostic insights. 

     

    cliexaAI process real-time clinical data and generates personalized diagnostic profiles, supporting data-driven clinical decisions.

    cliexaAI offers real-time predictive clinical insights, allowing healthcare providers to make proactive decisions that improve patient outcomes. 

     

    cliexaHub centralizes population health data, allowing healthcare providers to monitor metrics and outcomes in real-time while offering insights for individual cases.

     

    cliexaEcho generates synthetic clinical data to train AI models, ensuring better accuracy and compliance through data de-identification and robust scenario testing.

    cliexaAI’s Closed-Loop LLM is an AI-powered predictive analytics and decision support system that continuously learns from real-world healthcare data to optimize clinical outcomes and reduce inefficiencies. It is pre-trained in real clinical settings, retrained with Mayo Clinic Platform data, and powered by a patented clinical rules engine based on an evidence-based data indexing model. The AI is deployed on-premise with customized learning models that adapt to each healthcare system’s specific needs.

    It ingests real-time patient data, generates AI-driven insights, integrates with EMRs, and retrains models based on clinician feedback and patient outcomes to improve future performance. Learn more: cliexaAI

    cliexa is fully integrated with all major EMRs, including Epic. We operate within your existing tech stack, ensuring your data remains in-house for security and efficiency. Our AI platform indexes structured and unstructured data, clinical guidelines, payer requirements, Health information exchanges, Prescription Drug Monitoring Programs, and Patient generated health data into a comprehensive and complete patient view.

    No, cliexa's core infrastructure is fully U.S.-based. While some partners may leverage international resources, our deployments for organizations like the Defense Health Administration require a fully containerized U.S. infrastructure. cliexa is HiTrust-certified.

    cliexa continues to support providers across the full age spectrum, including subspecialties with a significant focus on pediatric populations. We’re especially proud of our groundbreaking work in adolescent eating disorders in collaboration with international expert Dr. Ovidio Bermudez.

    cliexa provides access to critical labs, patient-reported outcomes, imaging, risk factors, and clinical guidelines in a single, indexed view. This streamlines clinician workflows by providing real-time insights enabling optimial clinical decision support. cliexa reduces provider cognitive load and significantly decreases documentation time by up to 80%.

    cliexa takes the static dictation and tranforms it with the context of the clinical history, patient reported outcomes, payer requirements and relevent clinical decisions and produces documentation that is in alignment with the payer requirements drastically reducing claim denials.

    cliexaARCH automates denial prevention by aligning documentation with payer policies and clinical guidelines in real time. The platform reduces denial rates and maximizes revenue recovery. Authors draft appeal letters, ensuring complete clinical justification for claim resubmission. Automates appeal management, reducing processing time from two hours to 15 minutes.

    cliexa seeks partners who: Invest in clinical expertise, allowing us to refine AI models with real-world data. Enable workflow integration, ensuring that AI-generated insights reach clinicians at the point of care. Are open to innovation, as we frequently uncover additional optimization opportunities during deployment.

    Pricing is use case-dependent. cliexa offers AI solutions ranging from clinical prediction models to full revenue cycle management (RCM) integration. Our Sales team would love to discuss your project and provide pricing details.

    Yes, cliexa’s AI-powered clinical intelligence verifies compliance by cross-referencing approved treatment guidelines for each clinical indication. This reduces liability risks and ensures adherence to best practices.

    cliexaARCH streamlines the billing process by offering precise claim resubmission guidance, including tailored letters of medical necessity. More importantly, it integrates seamlessly into existing clinical workflows to support pre-authorization, documentation aligned with payer-specific requirements, and adherence to clinical guidelines which helps avoid claims denials and maximize reiumbursements at the first submission of the claim.

    The role based Insights Panel is fully customizable. It can be tailored to specific subspeciality needs, displaying relevant patient data based on role, specialty, preferences, and workflows.

    cliexa dynamically determines the patient’s triage level in real time using the ESI (Emergency Severity Index) Triage Algorithm. This capability is built into our platform when supporting providers involved in urgent care, emergency care, or nurse triage workflows—enabling data-driven, immediate clinical prioritization.

    cliexa integrates your specific materials, such as unique guidelines and care pathways, and includes that information alongside patient reported data and medical history in the insight panel embedded within your EMR.

    cliexa’s LLM is built entirely from the ground up using clinical data and real-world use cases, powered by our patented clinical indexing algorithm.

    cliexa works inside your EMR, enhancing Epic without requiring separate tools or workflows.

    We don’t chase trends—we pursue the whitespace: the operational blind spots and clinical bottlenecks that limit outcomes, access, and reimbursement for our partners. Our north star is their success, and our platform is designed to unlock their full value by solving the problems no one else has figured out how to fix.
    We do this by aligning our capabilities with three critical areas:
    Outcome-driven innovation – Everything we build is designed to generate measurable, repeatable results.
    Effortless integration – We fit within existing workflows, not around them—meeting partners where they are, then elevating performance.
    Future-ready infrastructure – Our patented AI architecture scales with evolving care models, payer requirements, and patient needs.
    In short, we focus where the friction lives—so our partners can focus on delivering care, not fighting systems.

    Yes, all interactions, diagnostic documents, and AI-generated SOAP notes are documented directly within the patient’s chart. All documentation is easily uploaded to the EMR with a single click, making it both comprehensive and effortless for clinical teams to access.

    The platform is highly configurable to serve a broad spectrum of healthcare professionals, including physicians, nurses, mid-level practitioners, surgeons, and administrative staff. Using an advanced rules engine, it customizes access and data presentation based on the user’s clinical role, decision-making authority, and medical specialty—such as orthopedics, ENT, or emergency medicine. This ensures that each provider sees only the most relevant information, allowing them to focus on top-of-license care, enhance efficiency, and improve decision-making.

    cliexa’s unique advantages over other ambient AI tools such as Deep Scribe:
     
    1. Advanced Patient History Insights
    Unlike other tools that rely solely on current audio or text inputs, cliexa leverages the progression of the patient’s journey. It generates encounter notes by analyzing previous notes and clinical progression, allowing for a comprehensive view of the patient’s health trajectory. This historical insight provides a continuity of care not seen in competitors.
     
    2. Real-Time, Multi-Source Data Integration
    cliexa doesn’t just use static or isolated data sources. It dynamically incorporates real-time information from lab results, medications, and other clinical data sources beyond the EMR. This means clinicians have access to the latest updates about the patient, including data that might come from outside traditional medical records, allowing for more informed, timely decisions.
     
    3. Beyond Single-Point Audio Transcription
    While tools like DeepScribe focus on capturing real-time audio and transcribing it for note generation, cliexa goes further. It integrates audio insights alongside insurance claims, patient onboarding data, and other relevant data streams, providing a multi-dimensional patient profile.
     
    4. Real-Time Feedback and Provider Learning
    cliexs incorporates real-time feedback loops from providers, allowing the AI to learn from ongoing interactions and improve continuously. This is not simply an AI that “generates notes”; it’s a proactive engine that adapts based on clinician feedback, enhancing its accuracy and relevance.
    Yes—and we can take it even further.
    While traditional methods can give you a snapshot of where Medicare is a dominant payer—using CMS claims, CIVHC, Contexture, and Census data to highlight high-need ZIP codes, provider deserts, and communities with rising chronic conditions—cliexaAI doesn’t stop at descriptive analytics.
    Our platform is designed to move from insight to foresight.
    We start with foundational data inputs—Medicare enrollment trends, reimbursement volumes, and SDOH metrics—and apply our AI engine to surface patterns and predict where unmet demand is hiding. From there, we enable our partners to act faster and more effectively by:
    Tracking real-time care gaps using automated data ingestion and geospatial modeling
    Forecasting high-utilization zones based on disease burden, provider capacity, and payer mix
    Targeting outreach to patients most at risk for complications, readmissions, or care delays—before they enter the system
    Optimizing resource allocation by mapping services to need with surgical precision
    Where legacy systems identify what was, cliexaAI helps you see what will be.
    It’s not just about where Medicare patients live—it’s about where outcomes, revenue, and equity can be unlocked next.
    Absolutely! Case managers can use cliexaARCH and get a clear, real-time view of transactions, claim denials, and financial trends through our Population Health Dashboard. It’s designed to make their job easier—helping them spot issues, track patterns, and take action faster without digging through piles of data.
    Plus, cliexaARCH automates a lot of the heavy lifting, like flagging problem claims, pre-filling appeal letters, and keeping up with compliance updates. That means less manual work and more time focusing on what matters most: keeping claims on track and revenue flowing.

    cliexa indexes all clinical data regarding patient that from your EMR, and other relevant data sources including lab results, imaging, patient insurance, the federal prescription drug monitoring program and more.

    cliexa can be deployed however you prefer, into your own environment whether that is on premise or in your private cloud

    Yes, our integration with the EMR is bi-directional and edits made in one are relfected in the other in real time.

    Yes, cliexa provides personalized and customizable responses based on the current real time presentation of the patient in conjuction with the services you offer.

    Yes, we can enable OCR capability to index data scanned from paper.

    cliexa reduces administrative errors by dynamically identifying the appropriate preoperative orders based on a patient’s current medications, medical history, and demographic data. Our platform includes a real-time patient status screen that highlights actionable next steps such as recommended orders, insurance eligibility, preauthorization status, and applicable billing codes, helping providers streamline decision-making and ensure nothing falls through the cracks.

    cliexa's unique connection to the patient's insurance enables a real-time checklist of what the patient needs to do to become surgical ready, including rehabilitation, imiaging, labs, medications to ensure that operational staff can interact with the patient to schedule and confirm all appropirate prrequisites prior to the procedure. Additionally cliexa generates appropriate patient education including necessary preparation (e.g. no food or drink before a surgical procedure, stopping blood pressure medications as advised)

    cliexa runs in conjuction with your EMR and is a bidirectional integration enabling access to data in real time as it is updated in the EMR

    cliexa runs in conjuction with your EMR and is a bidirectional integration enabling access to data in real time as it is updated in the EMR

    Yes. cliexa is designed to complement your existing investment in scribe technologies like Dragon. While you continue using Dragon for dictation, cliexa adds value by integrating clinical data into the workflow. cliexaAI actively engages with scribe, clinician, and patient inputs to generate structured documentation within the patient record, enhancing accuracy and clinical utility.

    Yes, our cliexaARCH solution includes a real-time set of dashboards highlighting practice performance including claims aging, reimbursement analysis and trends, provider and procedure success rates, predictive risk analysis and more.

    Yes, our cliexaARCH solution includes claim success and denial rates in real time to billing and adminsitrative users.

    Our cliexaARCH solution includes real-time dashboards highlighting billing efficiencies, claim denial rates, submission attempts and more, all designed to highlight billing and clinic operational efficiencies.

    Yes, cliexa presents the appropriate CPT codes aligning the patient's chief complaint, diagnostic codes, insurance and relevant clinical guidelines, ensuring that the codes avaialble for billing are accurate and best matched to what the provider will be paid for.

    No, you will be charged only when you interact with the cliexa insight panel in an encounter. You choose if you interact.

    cliexa's automated documentation process saves over 10 minutes of time per encounter. The improved coding capabilities ensure less time required by billing personnel for initial claim subsmittion and fewer denials resulting in improved A/R and reduced time to adjudicate claims.

    Yes cliexaARCH highlights underpayments and short pays in comparison to allowed amounts, enabling the billing users to resubmit and recoup potentially lost revenue by supplying the missing information necessary.

    Yes, cliexa handles authorization requirements by evaluating the patient's insurance information, chief complaint, and diagnosis. The platform also provides an intelligent, real-time checklist tailored to the patient’s specific case. This checklist outlines all necessary steps, documentation, and payer-specific criteria required to obtain prior authorization, helping staff streamline the process, reduce administrative burden, and improve approval timelines.

    cliexa’s clinical rules engine calculates the risk score for opioid use disorder using a comprehensive, multidimensional data set. Key factors include:
     

    Yes, the model continuously learns from provider-specific documentation patterns and adapts its responses accordingly. By recognizing individual provider behaviors and preferences, the system is able to tailor outputs such as clinical recommendations or documentation support to align with each provider’s unique workflow and style.

    Yes, during onboarding, the system reviews all available historical clinical documentation to train and calibrate its models. This allows cliexaAI to better understand existing documentation styles, clinical workflows, and patient population characteristics, enabling a more accurate and personalized deployment from day one.

    cliexa is integrated with all major EHR platforms and supports interoperability with dozens of systems. This includes widely used solutions such as Epic, Cerner, AthenaHealth, eClinicalWorks, Healthie, Greenway Health, and others. Our flexible integration framework ensures seamless data exchange and workflow alignment across diverse clinical environments.

    Through any means necessary. Typically the batch responses are directly uploaded into cliexaARCH and this can be enabled via API as well.

    Yes, the questions asked during exit surveys are fully customizable.

    Yes, output from cliexa can be transated to any language needed by the patient population. Intake languages are also fully customizable.

    cliexa servces real time information to patients in the intake application, including lab results.

    Fathom Health focuses exclusively on AI-powered medical coding automation, whereas cliexaARCH delivers an end-to-end solution for claims resolution, compliance, and revenue cycle optimization. cliexaARCH manages the full lifecycle from intake to payment, unlike Fathom which stops at coding. cliexaARCH supports claim denial management by identifying patterns, generating appeal letters, and suggesting corrections, while Fathom does not. cliexaARCH includes pre-claim compliance checks with payer-specific rules at the intake, documentation, and billing stages; Fathom does not offer this. cliexaARCH converts and learns from EOBs to optimize future claims, supports appeal workflow automation with guided steps and real-time tracking, and integrates deeply with clinical workflows aligning CPT and ICD-10 codes at the visit level—Fathom does not support these functions. cliexaARCH is tailored for high-rejection specialties like orthopedics, ENT, pain, and GI, whereas Fathom has a generalist approach. cliexaARCH offers real-time payer compliance suggestions, identifies coding gaps to support higher reimbursement, and includes analytics, audit tools, and batch processing as part of an AI-as-a-Service platform. Fathom provides API-based automation for coders only and is available as cloud-only, while cliexaARCH also offers secure on-premise deployment. In short, cliexaARCH empowers providers and billing teams with a holistic, intelligent platform that goes well beyond coding automation.

    cliexa is addressing a fundamental challenge in healthcare: the high cost—both financial and human—of delayed or missed diagnoses. Too often, clinicians miss key windows to intervene early, resulting in preventable disease progression, unnecessary hospital readmissions, and increased healthcare utilization. These missed opportunities are not just costly; they’re exhausting for providers. Clinicians today are overwhelmed by the sheer volume of evolving guidelines and research, making it nearly impossible to stay up to date. cliexa steps in to change that narrative by surfacing real-time, predictive insights that allow clinicians to make earlier, smarter decisions without additional burden.

    What sets cliexa apart is that its technology wasn’t retrofitted for healthcare—it was born inside the clinic. The AI is designed to think clinically, not just statistically. It combines multiple deep learning models within a patented healthcare data indexing and rules engine to improve both accuracy and adaptability. Most importantly, cliexa’s platform is built around a closed-loop system. That means the model continues to learn and evolve, integrating new clinical research, interventions, and regional nuances. It doesn’t just identify correlations—it learns to reason like a clinician and refine itself continuously.

    cliexa has been working with Mayo Clinic for years—not just as a customer, but as an investor and thought partner. Mayo chose cliexa as its first partner for AI validation due to the company’s clinical rigor, scalable infrastructure, and commitment to excellence. This partnership underscores cliexa’s credibility and its alignment with the highest standards of care and innovation in healthcare.

    The creation of a cliexa model starts with the clinical experts. Together, cliexa and its partners develop a logic map based on literature, clinical guidelines, and lived expertise. Then, the AI is trained on synthetic data to mimic the reasoning patterns of the clinical team. Once calibrated, real-world patient data is introduced to test whether the model can accurately differentiate between likely outcomes. Validation involves running the model on novel cohorts to ensure predictive performance matches or exceeds that of the expert clinicians. From there, the model continues to improve with every patient interaction, evolving into an increasingly accurate and personalized prediction engine.

    cliexa’s value goes beyond predicting risk. The platform provides clinicians with transparent, explainable insights. For instance, if a patient is identified as high-risk for opioid misuse, the model also surfaces the key data points that led to that determination. This shared understanding builds trust and allows clinicians to make more informed decisions. Additionally, cliexa supports proactive care by recommending alternative care plans when risks emerge, helping clinicians intervene before problems escalate.

    cliexa’s platform is designed for speed, security, and simplicity. It’s fully containerized, which means it can be deployed directly within a partner’s infrastructure, eliminating privacy concerns and easing integration. Unlike other vendors that require months to implement, cliexa can go live in weeks. Most importantly, the platform integrates seamlessly into clinical workflows—clinicians don’t have to change the way they practice. cliexa simply enhances the decisions they’re already making by surfacing timely, actionable insights.

    Not at all. One of the biggest challenges with AI in healthcare is the lack of transparency. cliexa addresses this head-on. Its models are designed to explain themselves, showing clinicians the “why” behind every prediction. Rather than asking providers to trust a black box, cliexa invites them into the decision-making process, reinforcing their expertise rather than replacing it.

    When cliexa collaborates with a partner to build a clinical model, that partner’s insights and expertise remain their own. cliexa does not repurpose a partner’s intellectual property for other clients. The platform is custom-trained for each setting, and any redeployment would require retraining from scratch. This commitment to IP protection ensures that cliexa is an enabler—not a competitor—in your innovation strategy.

    Partners working with cliexa can expect earlier diagnoses, fewer preventable readmissions, and stronger alignment between risk prediction and care planning. Clinicians regain control of their workflows without sacrificing their time or clinical judgment. And healthcare organizations gain the ability to scale personalized, evidence-based care with measurable, validated outcomes.

    cliexa’s platform is actively used in some of the most complex and mission-driven healthcare environments in the world. Our work with the Defense Health Agency and Mayo Clinic reflects our proven ability to deliver scalable, secure, and clinically meaningful digital health solutions. Whether deployed in government systems focused on operational efficiency or leading academic health centers driving innovation, cliexa consistently delivers measurable value through AI-powered automation that reduces administrative burden, real-time clinical insights that improve decision-making, and integrated digital workflows that enhance access and patient engagement. We understand the expectations of enterprise buyers, and we’ve met them in some of the most demanding environments in healthcare. Trusted by both the Defense Health Agency and Mayo Clinic, cliexa delivers enterprise-grade AI solutions with clinical rigor, built for organizations that require trust, scale, and measurable impact.

    cliexa has active deployments in Turkiye and the U.S., with validated implementations in clinical environments. While we have not yet deployed cliexaARCH in the UAE, we have recently signed a distribution agreement with Diginova to bring our solutions to healthcare systems in the region, including Saudi Arabia and the UAE. We are actively working with leading hospitals for technical discovery and alignment.

    Yes. cliexaARCH is designed with interoperability in mind. Our platform supports HL7, FHIR, and CCDA standards to securely integrate with insurance portals, health authorities, and institutional systems such as UAE eClaims, eRx, or DHA/HAAD frameworks. Integration is tailored based on the payer and system requirements.

    Absolutely. cliexaARCH’s billing AI assistant can be configured to push claims directly to existing payer portals or clearinghouses used in your region. We support integration into EMR-connected submission gateways or standalone interfaces through secure APIs and data mapping.

    Yes. cliexaARCH is designed to consolidate all relevant data sources—including clinical documentation, EMR history, patient-reported outcomes, payer protocols, and insurance eligibility—into a single, real-time view. The platform uses AI to synthesize this data into a comprehensive clinical and financial profile for each patient. This allows providers and billing teams to see diagnosis, risk factors, required documentation, recommended procedures, and payer-specific coding guidance—all in one screen. The result is faster decision-making, reduced claim denials, and optimized reimbursement potential with minimal administrative effort.

    The clinical prediction AI continuously improves by analyzing patient outcomes over time. After each patient interaction, the system tracks outcomes and compares them to both the original AI-generated predictions and the clinical rules engine's recommendations. This feedback loop allows the AI to refine its algorithms, enhancing accuracy and relevance in future predictions. As more data is collected, the model becomes increasingly precise in identifying risk factors, predicting outcomes, and supporting clinical decision-making.

    The clinical rules engine serves as the foundational baseline for the AI model. It is built on established, evidence-based clinical guidelines and protocols that produce consistent, rule-driven outputs. In contrast, the AI-powered prediction layer operates on dynamic learning—analyzing historical and real-time data to identify patterns, make predictions, and refine itself over time. The AI uses the outputs of the rules engine as a reference point to evaluate and improve its own predictions, enabling a balance between clinical consistency and adaptive intelligence.

    Yes, cliexa initiates prior authorization requests on behalf of the clinician by interfacing directly with payer portals and their electronic prior authorization (ePA) systems, when supported. The platform mirrors the clinic's standard workflows by leveraging the same triggering events and API channels used within the provider’s existing EHR. For more complex authorizations that require documentation of medical necessity, cliexa facilitates automation once that clinical determination has been made by the provider, helping streamline the process while maintaining clinical oversight.

    cliexa ensures that insurance information is current and accurate by connecting to payer networks through multiple integration points. These include electronic prior authorization (ePA) networks such as CoverMyMeds and Surescripts, direct payer APIs and EDI transactions, as well as FHIR and HL7 interfaces for advanced payers. By aggregating data from these sources in real time, cliexa maintains an up-to-date index of insurance details, which is then used to generate accurate and compliant automated documentation.

    We absolutely understand the importance of thorough evaluation when considering new vendors and initiatives. However, at this stage in cliexa's growth—being actively deployed in highly complex environments such as the Defense Health Agency and Mayo Clinic—we're no longer prioritizing unfunded proof-of-concept initiatives. Our platform has been rigorously validated in demanding healthcare settings, and we’ve designed our engagement model to align with partners who are ready to move forward with a defined scope and mutual investment. This structure ensures we can maintain the level of quality, support, and outcomes our partners rely on.

    That said, we remain open to collaborative models that include a clear, funded pathway—whether through phased deployments, grant-supported pilots, or other aligned initiatives. We’re happy to brainstorm options that allow for early-stage validation while acknowledging and respecting constraints on both sides. 

    cliexa sources diagnostic suggestion data from multiple patient-owned, real-time data streams: patient-reported data collected through clinically validated assessments before and between visits; claims data from the patient's current insurance coverage; Prescription Drug Monitoring Program (PDMP) data showing prescriptions from all providers, including refill details and frequencies; medical device data relevant to the patient's chief complaint; existing EMR data including clinical notes, lab results, diagnostics, diagnoses, and referrals. The data remains with and grows within the healthcare entity. cliexa's role is identifying and processing the most relevant data points for the current clinical moment, creating new data points that feed back into cliexa's AI self-guided learning model. This feedback loop enables the system to continuously improve with new datasets.

    Yes. Insurance companies do publish publicly available manuals or medical policies that include: clinical guidelines for approving tests, procedures, and treatments; utilization management policies including prior authorization requirements; CPT/ICD-10 code-specific rules, coverage limitations, and documentation requirements; payer-specific claim submission formats, including required modifiers and attachments. These can take the form of medical policy documents (PDFs on payer websites), clinical policy bulletins, provider manuals and prior authorization guidelines. cliexa doesn't just read these policies: it ingests, interprets, and applies them dynamically using a combination of: cliexa Rule Engine – a real-time, AI-driven engine that reverse-engineers payer behavior by scraping and parsing policy documents, analyzing Explanation of Benefits (EOB) outcomes, continuously learning from historical denials, approvals, and appeals across multiple clinics, structuring the data into payer-specific decision trees. Medical policies and guidelines are converted into structured formats using NLP. These are fed into a semantic engine that aligns: patient demographics, clinical context (e.g., chief complaint, diagnosis codes), CPT codes, documentation and prior auth rules. The graph-based architecture helps determine what carrier X vs. carrier Y requires for the same scenario. Dynamic Business Rule Updates: cliexa continuously monitors claims and EOBs using AI models built into cliexaAI. If a trend shows new denials for a previously approved scenario, an automated alert is generated. A new rule is created or updated (e.g., "Carrier Y now requires Modifier 25 for CPT 99213 with a same-day procedure"). That rule is pushed in real time to all clinics using cliexa. When a clinician is ordering labs, imaging, or referrals, cliexa: automatically documents the encounter using proper CPT or ICD codes; surfaces payer-specific suggestions for required documentation, modifiers, or alternate codes; warns of likely denials based on historical trends; proactively flags additional procedures or assessments that can be billed or are required for compliance.

    The system is designed as a co-pilot, not a replacement. It surfaces insights based on comprehensive data indexing but always empowers the clinician to make the final call. It avoids being a black-box solution by providing clear rationale for each suggestion, which helps clinicians maintain ownership over the care plan rather than blindly following a system-generated directive.

    Yes, the platform is designed to be transparent and informative rather than a black-box system. Whenever a clinical risk or recommendation is surfaced, the system clearly indicates the underlying data points driving that suggestion. For example, if a patient is flagged as a candidate for a specific therapy, the platform shows which data elements contributed to that decision and allows providers to click through for further details on each factor’s strength of evidence. This ensures clinicians remain actively engaged and informed in their decision-making, supported by insights that mirror their reasoning process.

    Currently, the system ranks recommendations based on evidence strength and relevance to the patient's data. Over time, as the AI learns from outcomes through a feedback loop, it will be able to surface metrics such as likelihood of success or outcome yield. In some use cases (like chronic kidney disease), it already indicates time-based risk progression and prioritized intervention strategies. Full probability modeling is in development and part of the long-term value.

    Rather than duplicating specialized imaging or genomic platforms, cliexa integrates with existing tools and systems. Its patented indexing engine captures and contextualizes vast, complex datasets—including genomics and imaging patterns—without the limitations of traditional linear querying. It identifies relevant relationships from structured and unstructured data sources and supports interoperability with external modules for things like 3D imaging.

    Yes. The care pathway module can surface exactly where a patient is in their clinical journey and highlight what's needed next—like pre-visit diagnostics or consults. It reduces the burden on schedulers and ensures patients are better prepared for appointments. It can also guide support staff with evidence-based triage protocols and escalate only those cases that truly require urgent intervention.

    Absolutely. The platform identifies the required preauthorization level for diagnostics or treatments and can automatically generate letters of medical necessity using indexed patient data. It knows payer-specific requirements and uses them to streamline pre-visit documentation, helping mid-level providers or clinical teams act confidently without adding administrative overhead.

    Yes. It’s built to handle diverse visit types per clinician such as wound care, primary care, allergy, pain management, all in one workflow. Rules-based triggers can suggest labs or assessments based on presentation.

    Yes. AI maps patient presentation to relevant guidelines, automating documentation and pre-authorizations aligned with payer policies.

    Yes. The platform can be configured to suggest appropriate interventions based on intake data, clinical triggers, services offered and more.

    Optional. The platform can be configured to share performance data or insights across clinics to enhance best practices.

    Yes. The cliexa platform can ingest and attach external documents such as e-faxes, scanned referrals, and clinical notes from outside providers directly to the patient’s record. This functionality is part of the onboarding configuration, where workflows around referrals and external documentation are mapped out.

    Documents can be automatically routed to the correct patient chart, categorized appropriately (e.g., labs, prior authorizations, consults), and made available for both clinical and billing workflows. This ensures continuity of care, improves documentation completeness, and supports compliance with payer and CMS requirements.

    If automation isn’t feasible in some cases, cliexa still provides manual upload and tagging options for operational staff to keep records accurate and centralized.

    cliexaAI features a closed-loop system that learns continuously from patient outcomes and clinician feedback. Every interaction refines the model, increasing accuracy, reducing drift, and aligning outputs to evolving clinical standards. It’s not a static model—it’s a live system that improves in real time.

    No. Cliexa’s model performs at a high level from day one using pre-indexed clinical logic and specialty-specific training. Once your data becomes available, the model further calibrates—but it's not dependent on local historical data to operate safely and effectively.

    Yes. Cliexa delivers a fully managed AI service:

    Training and specialty indexing

    Continuous benchmarking and feedback loops

    Governance documentation and audit reporting

    Weekly performance monitoring and drift correction

    cliexaAI is built to evolve with your environment. Our patented indexing engine allows us to update weights, adjust protocols, and localize logic dynamically. Whether it's regional population changes or updated payer policies, cliexaAI keeps pace without starting over.

    Without cliexa’s closed-loop model and patented indexing engine:

    You risk retrofitting general LLMs with expensive safety layers

    Clinical accuracy and auditability may degrade over time

    You lose the ability to scale dynamic learning across diverse populations and high-risk environments

    Simply put: cliexa is the only path to enduring value, and the only model engineered for long-term readiness in healthcare AI.

    cliexa’s implementation is fast and seamless. Most clients are live within 6-10 weeks. We handle deployment end-to-end, including secure container setup, data indexing, EMR integration, and clinician onboarding. Our team conducts collaborative discovery to define use cases, configure workflows, and establish benchmarks for success—allowing minimal disruption to clinical operations.

    cliexa can be deployed on-premise or within your private cloud infrastructure. At minimum, we require secure access to your EMR’s API, access to claims/EOB files (for cliexaARCH), and clinician workflow specifications. Our platform supports FHIR, HL7, CCDA, and standard API protocols to integrate with existing systems while ensuring HIPAA and HiTrust compliance.

    In addition to HiTrust certification, cliexa follows zero-trust architecture principles, with data partitioning, role-based access controls, and on-premise deployment options for full PHI ownership. For deployments in government agencies, we meet elevated cybersecurity standards and support custom security governance frameworks, including audit trails and encryption at rest and in transit.

    Yes, cliexa supports multi-EMR environments through our modular architecture and standardized API integrations. We currently interface with all major EMRs including Epic, eClinicalWorks, Cerner, and Athena, and can operate across systems simultaneously while maintaining patient data fidelity and real-time synchronization.

    Yes, cliexa is fully compliant with interoperability standards including SMART on FHIR, HL7, CCDA, and CDS Hooks. Our system integrates securely with EMRs, payer portals, and third-party applications—ensuring seamless connectivity for both clinical and administrative functions.

    cliexa’s closed-loop AI continuously monitors real-world outcomes and clinician feedback to detect and correct model drift. Performance metrics are benchmarked weekly and the platform auto-calibrates to reflect new clinical insights, payer changes, and documentation trends—ensuring continued accuracy and alignment with clinical expectations.

    Yes, cliexa’s indexing engine can ingest structured and unstructured data, including streams from medical devices, wearables, and remote monitoring tools. This data becomes part of the patient’s unified profile, allowing real-time updates for risk prediction, care planning, and personalized engagement strategies.

    cliexa clients typically see measurable ROI within the first 90 days, including an 80% reduction in documentation time, 30% drop in denial rates, and significant improvement in clean claim submission. For revenue cycle clients, cliexaARCH boosts revenue yield by optimizing charge capture, appeal success, and underpayment identification.

    cliexa’s predictive models surface patients at risk before adverse events occur—supporting proactive interventions aligned with value-based care models. Our documentation tools ensure guideline compliance and reduce variation, while our analytics dashboard provides performance insights to support payer negotiations and risk stratification for shared savings.

    Yes. cliexa supports export and integration with population health platforms, registries, and reporting systems. Our platform provides structured clinical data aligned with coding, SDOH metrics, and outcome tracking for value-based initiatives and public health reporting.

    Yes. cliexa is built to meet the needs of diverse patient populations. Intake forms, patient-reported outcomes, and discharge summaries can be configured in any language required by your population. Our platform supports full multilingual deployment on both the patient- and clinician-facing sides, ensuring culturally appropriate engagement and compliance with health literacy standards. For international markets, documentation can be adapted to reflect regional clinical and payer terminology.

    cliexa’s platform is designed to scale securely and rapidly across multiple locations, specialties, and EMR environments. Whether for a single clinic or a national health system, cliexa uses a modular microservices architecture with centralized governance and localized configuration. We support multi-tenant deployments with role-based access, shared or independent dashboards, and custom rule sets by location. This enables seamless performance tracking, standardized care pathways, and centralized billing analytics—while empowering each site to meet its unique operational goals.

    Both cliexa and Microsoft Copilot offer foundational features such as clinical documentation automation, voice dictation capabilities, and EMR/EHR integration. These shared functionalities enable providers to capture patient-provider conversations and convert them into structured clinical notes efficiently. By streamlining documentation workflows, both platforms help alleviate administrative burdens on clinicians and support more timely recordkeeping within digital health environments. These baseline capabilities make each solution a valuable tool in improving productivity and clinical throughput. However, cliexa stands apart through its advanced, clinically intelligent, and AI-driven infrastructure. Unlike Microsoft Copilot, which is primarily focused on documentation automation, cliexa delivers true clinical reasoning powered by a proprietary rules engine and comprehensive patient journey analysis. Its AI was trained on over 12 million de-identified patient records from Mayo Clinic Platform and validated through real-world data, achieving 87–97% predictive accuracy for complex conditions such as opioid use disorder and cardiovascular disease. cliexa supports proactive healthcare interventions via its Risk Prediction Platform and integrates multi-dimensional data—including lab results, insurance claims, onboarding inputs, and behavioral health indicators—for a full-spectrum patient view. Its specialization in eating disorders is particularly notable, offering tailored clinical protocols, risk stratification, treatment pathways, and engagement strategies. These capabilities enable cliexa not just to document care, but to intelligently guide it—making it a significantly more robust solution for organizations seeking data-driven, personalized, and outcomes-focused digital health tools.

    Tabia Health helps patients follow existing clinical pathways more reliably, increasing adherence and consistency, especially for standardized care plans like those in heart failure or oncology. cliexa, in contrast, empowers providers to choose the right pathway in the first place by using AI-driven precision medicine tools that account for patient-specific risks, comorbidities, and payer rules. Tabia’s strength is in keeping patients on the selected path; cliexa’s strength is in helping providers select and justify the best path, personalized and aligned with both clinical and reimbursement standards. For example, while Tabia might ensure adherence to an opioid prescription, cliexa could help prevent that prescription entirely by identifying OUD risk and guiding providers toward safer, payer-supported alternatives like Buprenorphine. Tabia excels at reinforcing predetermined decisions; cliexa excels at enhancing the decision itself. Their model focuses on conformity medicine; ours focuses on precision medicine. They ensure follow-through; we ensure smarter starting points. Both are vital, and together they represent a synergistic rather than overlapping opportunity — making a partnership with cliexa a strategic move into the rapidly emerging space of clinical complexity management and scalable precision care.

    Yes, cliexa has FDA APIs built into our platform. Additionally, we currently support customers who are actively utilizing state-level Prescription Drug Monitoring Programs (PDMPs). These integrations are part of our broader commitment to interoperability and regulatory compliance.

    cliexaConnect platform includes advanced OCR/ICR capabilities with AI-enhanced accuracy. The clinical rules engine validates extracted data against clinical protocols, achieving higher accuracy than traditional OCR solutions.

    cliexaConnect supports X12 standards (837, 835, 270/271, 276/277, 278), HL7 FHIR R4, and KSA-specific formats including NPHIES standards. It provides seamless bi-directional EDI processing.

    cliexa provides a purpose-built integration with NPHIES APIs for real-time claim submission, eligibility verification, and prior authorization. The platform is certified for FHIR compliance, as required by NPHIES standards.

    cliexaARCH provides complete claim lifecycle management with its proprietary clinical rules engine. Unlike generic solutions, it understands clinical context and automates complex medical decision-making processes.

    cliexa’s platform is designed specifically for KSA healthcare regulations. Continuous updates ensure ongoing compliance with Council of Health Insurance requirements and standards.

    cliexa has established integrations with major KSA insurers and TPAs. The platform adapts to each payer's specific requirements while maintaining standardized workflows.

    cliexaConnect enables instant eligibility verification through NPHIES APIs and direct payer connections. Results are integrated directly into clinical workflows.

    cliexaProtocols automatically identifies procedures requiring pre-authorization and initiates workflows. The clinical reasoning engine aligns requests with coverage criteria, improving approval rates.

    cliexaProtocols uses genuine clinical reasoning, going beyond traditional rule-based systems. It has been trained on over 12 million patient data points through its partnership with Mayo Clinic, achieving 87-97% accuracy in claim validation.

    cliexaAI identifies potential issues before submission, not just after denial. The system understands clinical context, enabling more accurate flagging of true discrepancies.

    cliexa supports international standards (CPT, ICD-10, HCPCS) and KSA-specific coding requirements. Its clinical reasoning ensures code appropriateness, not just format validation.

    cliexaProtocols serves as a comprehensive clinical knowledge base, continuously updated with the latest medical guidelines and coding best practices.

    cliexaAI analyzes coding patterns within clinical context to identify potential upcoding, unbundling, or inappropriate code combinations. Its clinical intelligence reduces false positives common in rule-based systems.

    cliexaAI analyzes clinical complexity, payer requirements, and historical patterns to optimize claim routing. The system continuously improves routing decisions through machine learning.

    cliexa employs a dynamic prioritization algorithm that considers multiple factors, including financial impact, clinical urgency, and processing deadlines.

    cliexa achieves 87-97% accuracy in denial prediction, compared to 65-75% with general-purpose models. Clinical context understanding enables precise predictions.

    cliexaAI not only predicts issues but provides specific, clinically-informed recommendations for resolution. Its closed-loop learning improves suggestions over time.

    cliexa maintains a complete transaction history with clinical reasoning documentation. This meets regulatory requirements for audit and compliance reporting.

    cliexa automates processing of remittance advice with immediate updates to claim status and financial records.

    cliexa automates appeals workflows following CHI guidelines. Its clinical intelligence improves appeal success rates by addressing root causes.

    cliexa learns from historical data to identify payer-specific patterns and requirements, reducing future denials.

    cliexaConnect enables seamless data flow between clinical and financial systems, preserving clinical context throughout the revenue cycle.

    cliexa provides full support for healthcare interoperability standards and offers flexible custom API development for unique integration needs.

    cliexa is built specifically for the KSA healthcare ecosystem and maintains comprehensive compliance with NPHIES standards.

    cliexa enables direct API integration for real-time claim submission, eligibility verification, and prior authorization.

    No, cliexaAI can be deployed into any health system, regardless of existing integrations. If there’s no prior infrastructure, we deploy into the health system’s own network or cloud environment. This requires the capability to support cliexa’s containerized architecture and connect necessary microservices, which differ by use case. We ensure deployment aligns with each site’s operational and IT security standards and offer flexibility for integration, data access, and compliance with institutional policies.

    Yes, deployment is designed to preserve existing clinical workflows. It starts within a staging environment that mirrors production, allowing safe model calibration. Data integration with the EMR can operate silently in the background or be semi-automated using clinical actions such as visit closeout or order entry as triggers. This approach ensures a seamless provider experience, allows real-time or batch data flows, and avoids requiring any changes in provider behavior unless explicitly intended.

    cliexa leverages its Clinical Rules Engine (CRE) to drive advanced, multi-comorbidity risk prediction models specifically built to address post-discharge readmission risk. Initially validated through a partnership with Mayo Clinic for opioid use disorder (OUD), the CRE has since expanded its capabilities to process over 12 million real-world patient data points across various specialties, including chronic pain, cardiovascular disease, adolescent risk, and mental health. For transitional care platforms, cliexa ingests data from electronic health records (EHRs), laboratory results, prescription histories, and patient-reported outcomes. It evaluates six core domains of risk: clinical history and comorbidities, medication usage and adherence patterns, lab and physical examination data, psychosocial and family history, patient-reported functional outcomes, and clinical narratives parsed via natural language processing (NLP). Using proprietary predictive algorithms, cliexa identifies high-risk patients who may be overlooked by standard discharge planning tools. This enables care teams to implement timely, targeted interventions, thereby reducing unnecessary readmissions and improving clinical outcomes.

    Yes, cliexa integrates seamlessly with Healthie. Our AI-enhanced platform operates natively within the Healthie interface to personalize patient intake, analyze clinical and lab data, and generate intelligent summaries and treatment suggestions—all without disrupting your workflow. Key capabilities include smart intake automation, AI-driven documentation (including an integrated AI Scribe), adherence monitoring with alerts, and lab analysis tied to clinical risk factors. We also support the creation of care pathways aligned with functional medicine protocols. Pricing is tailored based on your practice size and selected features.