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137 Listings in Healthcare AI Available
What is Corti? Corti is an AI platform for healthcare and life-science developers that provides APIs for medical coding, clinical speech-to-text, clinical note generation and building clinical agents. It also offers open-weight models hosted on European hardware. Key capabilities of Corti Medical Coding API: ICD-10 and CPT coding Speech to Text API: clinical transcription Text Generation API: clinical note generation Agentic Framework: builds clinical AI agents Pre-built agents: 20+ for tasks such as medication reconciliation and denial appeals Symphony: unified API for speech, documentation, coding and reasoning How Corti works Developers call Corti APIs to transcribe consultations, generate notes and assign medical codes, or compose them through Symphony. The agentic framework and 20+ pre-built agents handle tasks like medication reconciliation and denial appeals. Usage consumes credits across all APIs. Who uses Corti? Healthcare and life-science developers building clinical features use it, and Corti reports more than 1 million interactions every week. Its certifications include HIPAA, SOC 2, FedRAMP, ISO 27001, GDPR and EU AI Act compliance. Corti pricing Developers can start with $50 in free credits and no credit card. An Acceleration Pack costs $1,000 a month and includes 1,000 monthly credits plus development support, with usage-based credits across all APIs. Corti alternatives Alternatives include January AI for health insights, Owkin for pathology and drug discovery AI, BenchSci for preclinical research, Unlearn for clinical trial digital twins, and Insilico Medicine for drug discovery.
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Saaskart Market Grid™
Explore how leading Healthcare AI solutions compare based on customer satisfaction, market presence, adoption, and buyer feedback. The Market Grid helps you identify category leaders, high-performing solutions, and emerging products within the Healthcare AI ecosystem.
Category Leader
Navina
#1 in Healthcare AI
Best Value Healthcare AI
Mentalyc
From $15/mo
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Navina
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Derived from live Saaskart marketplace data, engagement, reviews, and pricing for this category.
Tech stacks
See where healthcare ai fits in a complete stack, with the other software, AI agents and services each business needs.
What is August AI? August AI is a personal health AI agent offering an AI health companion on WhatsApp and web that answers health questions and explains lab reports. Based in India, August AI helps consumers managing personal and family health automate personal health work and get results faster. Key capabilities of August AI Health Q&A Lab report analysis Medication info Symptom guidance Symptom assessment Plain-language explanations How August AI works August AI takes text, images and documents as input and produces text. It combines large language models with task-specific AI, with the vendor managing prompts, models and updates. It connects to tools such as WhatsApp, iOS, Android and Web browsers, so the agent works inside existing workflows. Who uses August AI? August AI is built for consumers managing personal and family health. It suits teams that want health Q&A and lab report analysis without adding headcount, while keeping people in control of review and final decisions. August AI vs Ada Health August AI is often compared with Ada Health. August AI stands out for health Q&A and medication info. The right choice depends on your workflow, integrations and budget, so compare both on a real task.
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What is Sully.ai? Sully.ai is an AI healthcare platform that adds capacity to health systems through agents connected to the electronic health record. It offers agents for the front desk, the visit and follow-up work. The vendor says health systems operating 20,000+ clinicians have adopted it. Key capabilities of Sully.ai Receptionist Agent: handles incoming calls, scheduling, triage, intake and insurance verification Scribe Agent: supports encounters through dictation and clinical decision support Consultant Agent: gives clinical guidance during visits Medical Coder Agent: completes documentation, coding, orders, follow-up and revenue cycle work EHR read and write-back: agents read from and write to connected EHRs Familiar workflows: keeps existing staff workflows intact How Sully.ai works Sully agents connect to the EHR, take on tasks such as answering calls or drafting notes and codes, and write results back to the record. Staff keep their workflow and review output. The vendor says it does not train on customer data. Who uses Sully.ai? Health systems, FQHCs and clinician networks use Sully. The vendor reports $650K+ saved at a 120-clinician FQHC by reducing abandoned calls and $2M+ saved through coding accuracy at a 200-clinician network. Sully.ai pricing Sully.ai does not publish pricing. Contact the vendor for a quote. Sully.ai alternatives Sully.ai is compared with Suki AI, Nabla and Navina. Suki and Nabla focus on ambient clinical documentation, while Navina surfaces patient insights for primary care.
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What is Navina? Navina is a primary care copilot AI agent offering an AI copilot that turns fragmented patient data into a clear clinical picture for value-based care. Founded in 2018 and based in New York, New York, USA, Navina helps primary care groups in value-based care automate primary care copilot work and get results faster. Key capabilities of Navina Patient data synthesis Risk adjustment Care gap closure Visit preparation EHR integration Clinician review workflows How Navina works Navina takes EHR data and documents as input and produces insights and text. It combines large language models with task-specific AI, with the vendor managing prompts, models and updates. It connects to tools such as Epic, Oracle Health (Cerner), athenahealth and eClinicalWorks, so the agent works inside existing workflows. Who uses Navina? Navina is built for primary care groups in value-based care. It suits teams that want patient data synthesis and risk adjustment without adding headcount, while keeping people in control of review and final decisions. Navina vs Pieces Technologies Navina is often compared with Pieces Technologies. Navina stands out for patient data synthesis and care gap closure. The right choice depends on your workflow, integrations and budget, so compare both on a real task.
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What is Saama? Saama is an AI-focused company that provides SaaS platforms and services to automate clinical development and commercialization. Its products cover data management, quality, patient review, operations analytics and document drafting for life sciences teams. Key capabilities of Saama Data Hub: data discovery and management Smart Data Quality: automated clinical data quality processes Patient Insights: speeds up patient data review Operational Insights: clinical operations analytics AI Document Generator: drafts clinical content BRAIN Suite: statistical programming and submissions tools How Saama works Saama applies machine learning models developed in its own AI research lab to clinical trial data. Reviewers use Patient Insights and Smart Data Quality to spot issues faster, while biostatistics tools support programming and regulatory submissions. Who uses Saama? Trial sponsors and clinical teams across study startup, clinical data management, clinical operations, risk-based quality monitoring, medical and safety, and biostatistics. It won AI-based Life Sciences Solution of the Year at the 2026 AI Breakthrough Awards. Saama pricing Saama does not publish pricing, and platforms are sold through vendor sales. Customers are not named on the homepage. Saama alternatives BenchSci and LatchBio serve earlier-stage research, Hippocratic AI and Ambience Healthcare target care delivery, and Insilico Medicine focuses on drug discovery.
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What is Avicenna.AI? Avicenna.AI is an emergency radiology AI AI agent offering AI for emergency CT that flags stroke, pulmonary embolism and other urgent findings. Founded in 2018 and based in La Ciotat, France, Avicenna.AI helps emergency radiology automate emergency radiology AI work and get results faster. Key capabilities of Avicenna.AI Urgent finding triage Stroke and PE detection Worklist prioritization PACS integration Regulatory-cleared algorithms How Avicenna.AI works Avicenna.AI takes image as input and produces alerts. It combines large language models with task-specific AI, with the vendor managing prompts, models and updates. It connects to tools such as PACS, DICOM, Epic and HL7 FHIR, so the agent works inside existing workflows. Who uses Avicenna.AI? Avicenna.AI is built for emergency radiology. It suits teams that want urgent finding triage and stroke and PE detection without adding headcount, while keeping people in control of review and final decisions. Avicenna.AI vs Aidoc Avicenna.AI is often compared with Aidoc. Avicenna.AI stands out for urgent finding triage and worklist prioritization. The right choice depends on your workflow, integrations and budget, so compare both on a real task.
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What is Youper? Youper is a mental health support AI agent offering an AI mental health assistant that uses CBT-based conversations to help people manage anxiety and mood. Founded in 2016 and based in San Francisco, California, USA, Youper helps adults managing anxiety and depression automate AI mental health support work and get results faster. Key capabilities of Youper CBT-based AI conversations Mood tracking Mental health screenings Personalized exercises Personalized insights Mobile apps How Youper works Youper takes text as input and produces text and insights. It combines large language models with task-specific AI, with the vendor managing prompts, models and updates. It connects to tools such as Apple Health, Google Fit, iOS and Android, so the agent works inside existing workflows. Who uses Youper? Youper is built for adults managing anxiety and depression. It suits teams that want CBT-based AI conversations and mood tracking without adding headcount, while keeping people in control of review and final decisions. Youper vs Wysa Youper is often compared with Wysa. Youper stands out for CBT-based AI conversations and mental health screenings. The right choice depends on your workflow, integrations and budget, so compare both on a real task.
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What is Sonia? Sonia is an AI mental health app that offers private voice and text conversations about stress, anxiety, relationships and emotional wellbeing. It is not a licensed human therapist. Key capabilities of Sonia Voice and text sessions: Talk or type with a customizable AI therapist. Memory: Remembers earlier sessions and connects themes over time. Weekly insights: Tracks emotional resilience and shows summaries. Mindfulness exercises: Guided exercises and meditations. Support plans: Builds a personal plan from conversations. Partner sessions: Supports couples sessions. How Sonia works Users open the app and start a voice or text session. The AI draws on cognitive behavioral principles and remembers prior conversations to personalize guidance, then produces weekly insights and a support plan. The App Store listing says it was designed with licensed therapists and researchers from Stanford, MIT and ETH, describes HIPAA-compliant privacy design, and states it is not for crisis situations. Who uses Sonia? Adults looking for between-session support, stress and anxiety coping tools or a low-barrier way to talk through emotions. It does not replace professional care or crisis services. Sonia pricing The iPhone app is free to download with in-app purchases. Sonia Grow is listed at $64.99 per month or $419.99 per year on the US App Store. Third-party sites list different plan prices. Sonia alternatives Doctronic and August AI offer AI health guidance, while Suki AI and Nuance DAX Copilot are clinician documentation tools. Sonia is aimed at consumers seeking emotional support.
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What is Cleerly? Cleerly is an AI-driven platform that quantifies and assesses coronary artery disease and delivers clinically actionable insights through a web-based solution. It measures plaque volume, composition, length and location, and evaluates stenosis severity in 2D and 3D. Cleerly serves healthcare providers, payors and patients. Key capabilities of Cleerly Cleerly Plaque Analysis: quantifies plaque volume, composition, length and location Stenosis evaluation: severity in 2D and 3D views Cleerly ISCHEMIA: workflow for the likely presence of ischemia Cleerly COMPARE: compares studies over time Web-based delivery: runs through a browser-based solution Clinical reports: actionable results for physicians and patients How Cleerly works A coronary CT angiography scan is submitted to the web platform, where AI quantifies plaque and stenosis. Cleerly ISCHEMIA adds a diagnostic ischemia assessment, and clinicians review the output to guide care. In the CREDENCE trial, the vendor says Cleerly ISCHEMIA showed higher diagnostic accuracy and area under the curve than FFRCT and stress testing. Who uses Cleerly? Cardiologists, imaging centers and health systems use Cleerly. In an analysis of the PACIFIC trial, Cleerly ISCHEMIA was noted as the only non-invasive ischemia test prognostic of future MACE events. Cleerly pricing Cleerly does not publish pricing. Contact the vendor for terms. Cleerly alternatives Cleerly is compared with Us2.ai, Anumana and Eko Health. Us2.ai automates echocardiography measurements, Anumana applies AI to ECGs and Eko Health uses digital stethoscopes.
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What is Deepnoid? Deepnoid is a medical imaging AI agent offering a Korean medical AI company offering imaging diagnosis support and a no-code platform for building medical AI. Based in Seoul, South Korea, Deepnoid helps hospitals and radiologists automate medical imaging work and get results faster. Key capabilities of Deepnoid Radiology AI Medical image analysis No-code AI builder Clinical decision support Image-based detection How Deepnoid works Deepnoid takes images as input and produces findings and reports. It combines large language models with task-specific AI, with the vendor managing prompts, models and updates. It connects to tools such as PACS, DICOM, Hospital EMR and REST APIs, so the agent works inside existing workflows. Who uses Deepnoid? Deepnoid is built for hospitals and radiologists. It suits teams that want radiology AI and medical image analysis without adding headcount, while keeping people in control of review and final decisions. Deepnoid vs Lunit Deepnoid is often compared with Lunit. Deepnoid stands out for radiology AI and no-code AI builder. The right choice depends on your workflow, integrations and budget, so compare both on a real task.
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What is Scribeberry? Scribeberry is an AI clinical documentation platform that transcribes patient conversations into structured medical notes compatible with existing EMRs. It is made in Canada and the vendor reports 30,000+ healthcare providers. Key capabilities of Scribeberry Ambient AI scribe: Works for in-person and virtual visits. 2,000+ templates: Customizable note templates. 40+ languages: Plus live translation. EMR integration: Accuro, Oscar Pro, Epic, Jane and Plexia. PDF form auto-fill: Referrals and CRA DTC forms. AI clinical agents: Agents for clinical tasks. How Scribeberry works A provider records the visit, and Scribeberry transcribes it into a structured note using a template, with letters and PDF forms filled from the same encounter. One-click workflows push the note to supported EMRs, and a Chrome extension covers Zoom, Teams, Google Meet and Doxy. Data is encrypted, stored regionally, and never used for model training, per the vendor. Who uses Scribeberry? Physicians and clinics, especially in Canada. The vendor cites 30,000+ providers and institutions including Telus Health, Sunnybrook and CAMH. Scribeberry pricing Pricing is not shown on the homepage, and a Get Started Free option is offered with limits not detailed. Scribeberry alternatives Related tools include Supanote, Twofold, Autonotes, Suki AI and Nabla, which also generate clinical notes from visits.
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What is Subtle Medical? Subtle Medical develops vendor-neutral AI software for medical imaging that improves image quality and shortens scan times across MRI, PET and CT. Its products run on existing scanners rather than requiring new hardware, and the company says they work with all existing MRI scanners, old and new. Key capabilities of Subtle Medical SubtleHD (MR): denoising and sharpening that the vendor says enables up to 80% faster MRI scans SubtleHD (PET): denoising for up to 75% faster PET scans SubtleHD (CT): reduces noise and improves low contrast detectability SubtleSYNTH: generates additional MR contrasts from acquired data SubtleALIGN: automates brain MR alignment Vendor-neutral deployment: works across scanner manufacturers How Subtle Medical works The software applies deep learning models to images from the scanner, removing noise and restoring sharpness so that shorter acquisitions still yield diagnostic-quality images. The MRI products are grouped as the Subtle-ELITE package. SubtleGAD, aimed at reducing gadolinium dose, is listed as in development. Radiologists continue to review the resulting images. Who uses Subtle Medical? Hospitals and imaging centers use it to raise scanner throughput and patient comfort. AiMIFY, a brain lesion visualization product, is sold through Bracco. Subtle Medical pricing Subtle Medical does not publish pricing on its site. Quotes are provided by the vendor. Subtle Medical alternatives Subtle Medical works on top of any scanner, whereas GE HealthCare AIR Recon DL and Philips SmartSpeed are reconstruction tools tied to their makers. Aidoc focuses on triage and detection, not image enhancement.
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Healthcare AI applies machine learning and generative models to clinical and operational work, documentation, patient engagement, scheduling, and administrative automation, with safety, privacy, and compliance as the defining concerns. This guide explains what healthcare AI is, how it works, what matters, and how to choose one.
Healthcare AI applies machine learning and generative models to clinical and operational work, documentation, patient engagement, scheduling, and administrative automation, with safety, privacy, and compliance as the defining concerns. This guide explains what healthcare AI is, how it works, what matters, and how to choose one.
Healthcare AI covers tools that assist clinical and administrative tasks: ambient clinical documentation (AI scribes), patient engagement and triage chatbots, scheduling and intake automation, claims and revenue-cycle automation, and clinical decision support.
Most marketplace-relevant healthcare AI focuses on operational and administrative use cases, documentation, communication, and workflow, rather than autonomous diagnosis, which is heavily regulated.
The category is defined by stringent requirements: HIPAA and data privacy, clinical safety, accuracy, and regulatory compliance. Buyers weigh these alongside integration with EHR systems and measurable time or cost savings.
Depending on the use case, AI listens to and documents clinical encounters, answers patient questions and triages, automates scheduling and intake, or processes claims, surfacing outputs for clinician or staff review within compliant workflows.
Platforms combine speech and language models, EHR integration, knowledge grounding, and strict security and compliance controls, with human review for clinical content.
Healthcare organizations configure workflows, integrate with the EHR, and maintain oversight and compliance; AI handles documentation and routine tasks while clinicians and staff verify and decide.
AI scribes capture clinician-patient conversations and draft structured notes for review.
Chatbots answer questions, triage, and guide patients while protecting sensitive data.
Automate appointment scheduling, reminders, and intake to reduce administrative load.
Automate coding, claims, and billing tasks to reduce errors and denials.
Integrate with electronic health record systems so AI fits clinical workflows.
Encryption, access controls, BAAs, and compliance for protected health information.
AI documentation cuts charting time so clinicians focus on patients, not paperwork.
Automating scheduling, intake, and claims reduces staff workload and errors.
24/7 engagement and faster scheduling improve patient experience and access.
Automation reduces documentation and billing mistakes when properly reviewed.
Streamlined workflows free capacity across clinical and administrative teams.
| Type | Best for | Ideal size | Pros | Limitations |
|---|---|---|---|---|
| Ambient AI scribes | Clinical documentation | Practices to health systems | Cuts charting time | Clinician review required |
| Patient engagement AI | Chat, triage, communication | Any | Access and deflection | Safety and privacy critical |
| Administrative automation | Scheduling, intake, claims | Any | Reduces admin load | EHR integration effort |
| Clinical decision support | Evidence and risk surfacing | Health systems | Supports clinicians | Regulatory scrutiny; oversight |
Hospitals & Health Systems: Reduce clinician documentation burden and streamline operations at scale.
Physician Practices: Cut charting time and automate scheduling and intake.
Telehealth: Power patient engagement, triage, and virtual-visit documentation.
Behavioral Health: Ease documentation while protecting sensitive patient data.
Health Insurance / Payers: Automate claims, prior authorization, and member engagement.
Pharmacy: Automate communication, refills, and administrative workflows.
This is non-negotiable. Confirm HIPAA compliance, a signed BAA, and certifications for protected health information.
Verify accuracy and that clinicians review AI-generated clinical content; demand evidence and oversight.
Confirm integration with your EHR so AI fits clinical workflows rather than adding steps.
Check data handling, residency, retention, and whether data trains shared models.
Look for credible evidence of time or cost savings in settings like yours.
Understand per-clinician, per-visit, or volume pricing and how it scales.
Ambient documentation is becoming standard, materially reducing clinician charting burden.
Agentic administrative automation is streamlining scheduling, intake, and revenue cycle end to end.
Regulatory frameworks for clinical AI are maturing, clarifying safe deployment.
Buyers should prioritize HIPAA compliance, clinical safety and oversight, EHR integration, and credible evidence above all.
Healthcare AI applies machine learning and generative models to clinical and administrative work, ambient clinical documentation (AI scribes), patient engagement and triage chatbots, scheduling and intake automation, revenue-cycle and claims automation, and clinical decision support. Most practical deployments focus on operational and documentation tasks rather than autonomous diagnosis, which is heavily regulated.
It can and must be for handling protected health information. Compliant vendors implement encryption, access controls, audit logs, and will sign a Business Associate Agreement (BAA). HIPAA compliance and a BAA are non-negotiable requirements, never use a tool that won't sign a BAA for PHI, and confirm data handling and residency before adopting.
Autonomous diagnosis is heavily regulated and not how most healthcare AI is used. Clinical decision support tools can surface evidence and flag risks to assist clinicians, but a licensed clinician makes the diagnosis and decisions. Any clinical AI should keep humans in the loop and comply with applicable regulatory requirements.
Ambient AI scribes listen to the clinician-patient conversation (with consent) and generate structured clinical notes that the clinician reviews and signs. They aim to reduce documentation burden and burnout. Accuracy and clinician review are essential, and the tool must handle the conversation as protected health information under HIPAA.
It must be, given the sensitivity and regulation of health data. Confirm HIPAA compliance, a BAA, encryption, access controls, data residency, retention policies, and whether data trains shared models. Strong security, privacy, and compliance should outweigh other factors when evaluating healthcare AI.
Leading tools integrate with major EHR systems so documentation and workflows fit clinical practice rather than adding steps. Integration depth varies and can be complex, so confirm support for your specific EHR and how deeply the tool reads from and writes to it.
Common models are per-clinician (PEPM), per-visit/encounter, or volume-based, sometimes as add-ons within EHR or practice-management systems. Estimate your clinician count or visit volume, and weigh compliance, EHR integration, and evidence of savings alongside cost.
Make HIPAA compliance and a BAA, clinical safety and human oversight, and EHR integration your top criteria, then evaluate data privacy and residency, credible evidence of time or cost savings, and pricing. Pilot in a real clinical or operational setting and verify compliance and accuracy before scaling.