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The best agentic AI platform for healthcare in 2026 includes Kore.ai, Avaamo, Oracle Health, Salesforce, ServiceNow, Sierra AI, and Hyro.
As Eric Boyd, Corporate Vice President, Microsoft, stated: “Today, the promise of technology can help us solve some of the biggest challenges we face—and nowhere is AI more needed, or possibly more impactful, than in healthcare.”
And it is not hard to see why.
Healthcare is operating under pressure that no amount of clinical excellence alone can solve. There simply aren't enough people to deliver the care the world needs. The U.S. alone faces a projected shortage of up to 124,000 physicians by 2034, according to the AAMC.
But the most urgent problem isn't the number of doctors. It's where their time goes. A Harris Poll survey commissioned by Google Cloud found that clinicians spend nearly 28 hours per week on administrative tasks alone; more than half a working week lost to work that has nothing to do with patient care.
While agentic AI cannot replace care teams or human empathy, it can take on the high-volume, repetitive work that consumes a significant portion of healthcare operations. AI agents are already being deployed to reduce administrative burden and improve operational efficiency.
The gains, however, only materialize when organizations choose the right foundation. Choosing the right agentic AI platform for healthcare is a strategic decision, with real consequences for patient experience, operational efficiency, and long-term competitive position.
In this guide, we explore the 7 best AI platforms for healthcare in 2026, examining how leading vendors are enabling this next phase of healthcare transformation.
Key takeaways (The TL;DR)
- Healthcare enterprises are deploying AI agents that can automate real workflows across clinical, operational, and patient-facing functions.
- The biggest differentiator is time to value. What separates platforms is how much engineering, integration, and configuration work stands between you and a live healthcare workflow.
- The best agentic AI platform for healthcare in 2026 includes Kore.ai, Oracle Health, Salesforce, ServiceNow, Avaamo, Sierra AI, and Hyro.
What is an agentic AI platform for healthcare?
A healthcare agentic AI platform is a purpose-built environment where healthcare organizations can build, deploy, and orchestrate AI agents across clinical, operational, and patient-facing workflows at scale. Unlike traditional automation tools that follow fixed rules, agentic AI systems can reason, plan, execute multi-step actions, and adapt in real time.
The strongest platforms combine three foundational capabilities:
- Data integration: connecting EHRs, claims systems, and other healthcare data sources using standards like FHIR and HL7 to create a single, searchable foundation for agent decision-making
- Intelligent applications: prebuilt and configurable capabilities for use cases such as clinical documentation, patient engagement, care coordination, and revenue cycle operations, so they are deployable without building from scratch
- Orchestration and automation: a workflow layer that sequences agent actions across systems, teams, and touchpoints, handling handoffs, exceptions, and escalations automatically.
- Governance and compliance: audit logging, role-based access controls, and configurable guardrails that ensure every agent action is traceable, explainable, and HIPAA-compliant.
Together, these layers determine how quickly a healthcare organization can move from AI experimentation to production-grade workflows, and how safely they can do it at scale. The platforms that get all four right are the ones worth evaluating. In this section, we will evaluate seven platforms that are leading in enterprise healthcare AI deployment in 2026.
Before moving further, if you want to learn about the real-world use cases, explore agentic AI use cases in healthcare
Top 7 agentic AI platforms for healthcare in 2026
Below are the top 7 agentic AI for healthcare platforms that stand out in 2026 and beyond, along with a breakdown of where they excel, the problems they solve, and the use cases they’re best suited for.
Our evaluation draws on neutral, third-party analyst reports from Gartner, Forrester, and Everest Group to provide a vendor-neutral assessment of each platform. We assessed each across agentic AI maturity, EHR integration depth, time to value, and compliance posture, to give healthcare enterprises a clear, comparable view of where each solution genuinely excels and where it falls short.
1. Kore.ai - Best for healthcare enterprises that need production-ready AI agents across patient service, contact centre, and payer operations
Kore.ai is an enterprise-grade agentic AI platform that helps healthcare organizations quickly design, deploy, manage, and scale AI agents across the clinical and administrative spectrum. The platform offers a full range of agentic solutions for patient engagement, member services, and process orchestration, giving enterprises the freedom to build HIPAA-compliant AI agents for virtually any healthcare scenario.
Gartner, in its Magic Quadrant for Conversation AI platforms, notes that Kore.ai delivers a feature-rich platform that stands out for its comprehensive and well-balanced AI capabilities, excelling particularly in AI enablement and process management.
What sets Kore.ai’s ‘AI for Healthcare’ apart is how it enables end-to-end workflow automation across the care journey — from patient access to post-care follow-ups — giving enterprises the tools to build HIPAA-compliant AI agents across patient engagement, payer operations, and life sciences workflows.
Kore.ai's agent library spans three core healthcare segments, each with purpose-built workflows:
For providers, Kore.ai's AI agents automate appointment scheduling, send personalized medication and visit reminders, enable symptom checks, and give patients instant access to medical records and lab results. This reduces no-shows and relieves administrative burden on clinical staff.
On the payer side, Kore.ai's AI agents guide members through billing details, payment plans, and eligibility, while also providing real-time claims updates and recommending financial assistance options. This improves member experience while streamlining back-office operations such as payment handling and claims management.
In life sciences, agents assist with medical information delivery, handle provider and patient inquiries, and use NLP to monitor conversations in real time for potential adverse events, cutting response times and keeping regulatory reporting on track without manual effort.
At the architecture level, Kore.ai is built for enterprise flexibility. Its model-agnostic and cloud-agnostic design allows organizations to integrate with their existing tech stack, rather than requiring them to rebuild around it. With 250+ plug-and-play integrations and native support for FHIR and HL7, it connects to the systems healthcare enterprises already rely on, including Epic, Oracle Cerner, NextGen, Salesforce, Microsoft Teams, Slack, and Twilio.
Where Kore.ai truly differentiates is in its governance-first approach to healthcare AI. The platform provides full audit logs and monitoring of every agent decision (critical for HIPAA compliance) alongside role-based access controls and configurable guardrails that enforce safe AI behaviour across clinical and operational workflows.
Trusted by over 400+ Fortune 2000 companies globally, Kore.ai brings proven enterprise scale and reliability to organizations looking to operationalize AI across healthcare workflows.
Key healthcare features of Kore.ai:
- Pre-built agentic app for healthcare that reduces administrative work, improves access for patients and members, and delivers more consistent service experiences
- Provider optimization: Automates scheduling, medication reminders, symptom checks, and instant access to lab results
- Payer empowerment: Enables real-time billing visibility, claim status tracking, and personalized financial assistance recommendations for members
- Life sciences support: Delivers real-time clinical and safety data, handles medical inquiries, and uses NLP to detect adverse events proactively
- Multi-agent orchestration: Allows AI agents to collaborate, share context, and execute multi-step workflows across patient, provider, and operational use cases
- 300+ pre-built agents and templates to accelerate deployment and time to value
- 250+ plug-and-play integrations: Connects with EHRs (Epic, Oracle Cerner, NextGen), CRMs, and enterprise tools (Salesforce, Microsoft Teams, Slack, Twilio) with FHIR and HL7 support
- Model-, data-, and cloud-agnostic architecture provides flexible deployment options
- Configurable guardrails: Structured access control and safe AI behaviour frameworks that keep every agent operating within compliance boundaries
When to consider Kore.ai
Kore.ai delivers the most value for organizations that are ready to move beyond point solutions, where the goal isn't adding an AI feature to an existing workflow, but redesigning the workflow around AI. If that's where your organization is, Kore.ai is built for exactly that transition.
See what this looks like in practice: How a California-based healthcare provider unlocked $3.2M in revenue with Kore.ai →
2. Avaamo - Best for healthcare enterprises that need conversational AI
Avaamo is an enterprise conversational AI platform for healthcare that provides pre-tuned small language models (SLMs) and a library of prebuilt agents covering patient and member-facing use cases.
IDC, in its 2025 MarketScape for Conversational AI Platforms, notes that Avaamo provides prebuilt features, including industry- and use-case-specific agents, alongside production readiness testing and ROI metrics.
Similar to Kore.ai, Avaamo also supports a BYO-LLM model, offering organizations flexibility in their choice of models from providers including OpenAI, Anthropic, Mistral, AWS, and others.
The platform offers small language models pre-tuned for healthcare, which allows organizations to deploy agents that are contextually grounded, without investing heavily in custom model training.
That said, Avaamo still needs to work on some areas. IDC cautions that organizations evaluating Avaamo should also consider that while its conversational AI foundation is strong, its agentic orchestration layer, including protocols like MCP and A2A for cross-agent interoperability, is still on the near-term roadmap rather than fully generally available.
Additionally, IDC also notes that Avaamo needs to increase its thought leadership activities and expand its industry-specific LLM support to sustain differentiation as the market matures.
Key healthcare features of Avaamo:
- Healthcare-specific SLMs: Pre-tuned small language models for healthcare use cases, further customizable per deployment
- 50+ prebuilt agents: Ready-to-deploy templates across patient services, HR, and clinical support workflows
- Omnichannel multilingual support: Voice, chat, and messaging across languages, making it suitable for diverse patient populations
- Low-code development: Enables business teams to build and deploy agents for HR, IT, and customer service without deep engineering
- Flexible deployment options: Private cloud, public SaaS (AWS, Azure, Google), hybrid, and on-premises support
When to consider Avaamo:
Avaamo is well-suited for healthcare organizations that prioritize omnichannel patient or member engagement and want healthcare-specific SLMs. Organizations with complex multi-agent orchestration needs or those requiring deep EHR-native workflow automation may wish to assess whether Avaamo's agentic roadmap aligns with their deployment timelines.
3. Oracle Health - Best for organizations that need an EHR with AI capabilities
Oracle Health is evolving its legacy EHR platform into a more AI-enabled healthcare environment, focused on embedding intelligence directly into clinical workflows. Its approach centres on reducing documentation burden, surfacing contextual patient insights, and automating routine clinical tasks within the care delivery process.
A key area of focus is clinical agentic workflows. Gartner, in its Market Guide for Health Platforms, notes that Oracle includes AI-powered capabilities such as contextual patient summaries, conversational chart search, and conversation assistance that can auto-generate physician notes.
Building on this, Oracle has introduced Oracle Clinical AI Agent, a voice-driven assistant designed to operate in clinical settings. Using ambient listening during patient encounters, it can capture interactions, generate structured clinical documentation, and surface relevant patient data, such as lab results, medications, and care history, in real time.
While Oracle’s Clinical AI Agent represents a meaningful step forward, the broader Oracle Health platform has faced operational challenges following its Cerner integration. Industry feedback has highlighted concerns around support responsiveness, implementation consistency, and overall platform maturity.
In fact, in a customer survey, Oracle received a "D+" for overall performance, with most customers stating they would not buy the Oracle EHR again.
Leadership continuity has also been a point of attention, with organizational changes and executive layoffs in September 2025, underscoring the need for careful evaluation by healthcare CIOs.
Key features of Oracle Health
- Voice-first clinical AI: Ambient listening, draft note generation, and conversational chart interaction for clinician workflows.
- Clinical workflow execution: Automated draft orders for labs, imaging, prescriptions, and follow-up appointments.
- Context-rich healthcare data layer: Semantic indexing and longitudinal clinical data designed to support LLM-ready retrieval and querying.
- Low-code extensibility: Plug-in architecture and low-code tools for extending experiences across UI, logic, and data layers.
- EHR-adjacent intelligence: Tight integration with Oracle Health clinical workflows to reduce documentation effort and improve care coordination.
When to consider Oracle Health:
Oracle Health is best evaluated as two separate decisions: the Clinical AI Agent and the broader EHR platform. If you're considering Oracle Health, it may be worth assessing the maturity of the next-generation EHR, particularly in acute care settings, before making long-term commitments.
4. Salesforce - Best for AI-driven patient engagement journeys
Salesforce is an AI platform that enables healthcare providers and payers to deploy AI agents through Agentforce for Health. It powers use cases such as automated patient engagement, care coordination, and front-office or service-heavy healthcare journeys.
Gartner, in its Market Guide for Digital Health Platforms, notes that Salesforce focuses on delivering personalized digital experiences at scale, built on a 360-degree patient view and supported by composable application capabilities.
Much like Kore.ai, Salesforce also offers a Healthcare Agent Library, featuring prebuilt templates for use cases such as prior authorizations, patient recruitment for clinical trials, and care plan adherence. This allows health systems to accelerate deployment and reduce engineering effort.
That said, Salesforce’s architecture remains a walled garden and is only effective when data nd workflows are centralized within its ecosystem. Organizations often need to rely heavily on Salesforce Data Cloud and related services to unlock the platform’s full potential. While this creates a unified experience, it can also introduce ecosystem dependency and increased data management costs as healthcare datasets scale.
Pricing is another area to evaluate carefully. Salesforce requires Health Cloud and Data Cloud licenses as prerequisites for the most advanced agentic features. Along with consumption-based pricing for Agentforce (often tied to interactions or usage), this results in the total cost of ownership becoming less predictable, particularly for large-scale patient engagement or outreach programs.
Key features of Salesforce:
- Agentforce for Healthcare: Enables AI agents to automate patient engagement, care coordination, and service workflows
- Data Cloud for Health: Unifies patient, claims, and operational data to power real-time personalization and automation
- Prebuilt healthcare workflows: Includes care plans, referral management, prior authorizations, and patient communication flows
- Healthcare Agent Library: Prebuilt agent templates for clinical trials, adherence programs, and administrative workflows
- Low-code extensibility: Allows teams to customize workflows and experiences without heavy engineering
When to consider Salesforce:
While Salesforce offers a personalized patient journey, its full power is only unlocked when clinical and behavioral data are centralized within the Salesforce ecosystem. For many healthcare enterprises, this requires significant investment in Data Cloud and professional services to ensure agents are grounded in accurate, real-time context.
5. Sierra AI - Best for healthcare teams adopting autonomous customer service
Sierra AI is a young startup in the agentic AI landscape. For healthcare organizations, its relevance lies in automating patient-facing service journeys such as billing questions, account updates, scheduling support, and other administrative interactions.
Another key component of the platform is Sierra’s Agent Data Platform (ADP), which stores long-term patient context. This allows agents to maintain continuity across interactions and personalize responses based on historical data. The platform also supports omnichannel deployment across voice, chat, email, and messaging channels, which can help enterprises modernize patient access and support experiences.
Where Sierra becomes limited for healthcare enterprises is in its architectural depth. Sierra’s architecture currently relies on a single-agent model, where one AI agent manages an entire workflow. This may work well for patient support workflow, but healthcare enterprises with more complex environments may need broader multi-agent orchestration, deeper EHR connectivity, and stronger workflow governance. This is especially relevant when moving beyond customer service into clinical, payer, or cross-departmental automation.
Another consideration is how Sierra is implemented. While the platform is marketed as no-code, Sierra itself emphasizes close collaboration with its own agent engineering teams to design, build, and optimize deployments. In practice, that makes the model feel less like fully self-serve software and more like a guided or partner-led implementation approach.
Pricing is also worth evaluating carefully. Sierra uses an outcome-based pricing model, where customers pay for value delivered rather than simple usage. While that can sound attractive, it may also introduce ambiguity around what qualifies as a billable “outcome,” especially in healthcare workflows where success can be harder to define than in retail or subscription support. For organizations running large-scale patient outreach or service programs, this can make forecasting and budget control more difficult.
Key AI capabilities of Sierra AI
- Goal-oriented AI agents, built to complete service workflows
- AI agents use long-term interaction history to personalize responses and maintain continuity
- Supports voice, chat, email, SMS, and messaging experiences from a single agent layer
- Outcome-based pricing charges based on business results rather than raw usage
When to consider Sierra AI
Sierra is a good option for healthcare organizations that want to introduce autonomous patient service in workflows such as billing support, appointment help, or account management. For broader healthcare automation strategies, though, enterprises should look closely at architectural fit and whether Sierra’s customer-service-first model is sufficient for more complex, regulated workflows.
6. ServiceNow - Best for healthcare enterprises automating service-heavy workflows
Started as an enterprise IT service management (ITSM) platform, ServiceNow has evolved into an enterprise-grade system for building and managing AI-driven workflows. It is important to note, however, that ServiceNow is fundamentally an operational platform, not a clinical one.
ServiceNow’s strength lies in orchestrating the people, data, and applications involved in service-heavy healthcare journeys, such as previsit management, patient onboarding, case management, and support operations.
From a healthcare platform perspective, Gartner, in its Market Guide for Digital Health Platforms, notes that ServiceNow has developed a healthcare-specific data model, data management capabilities, and an integration layer that gives organizations a more contextual view of workflows and service issues. It also highlights capabilities such as clinical device management and patient engagement operations.
That said, ServiceNow’s AI agents, while configurable for patient-facing interactions, are ultimately extensions of a platform built for operational workflows, not a purpose-built patient engagement layer. As a result, ServiceNow is suited for service automation and coordination, rather than clinical decision support or EHR-embedded agentic intelligence.
Gartner also notes that ServiceNow’s strengths are centered around workflow tools and service management rather than a broad set of healthcare-native clinical capabilities. In practice, this means organizations may still need additional platforms to support richer clinical context, patient intelligence, or advanced care-delivery workflows.
Key AI capabilities of ServiceNow for healthcare:
- Now Assist AI agents: Supports AI agents that can answer, summarize, and take action across workflows
- Healthcare and Life Sciences Service Management: Streamlines patient and care-team workflows using playbooks and case management
- Integration Hub: Connects third-party systems and data to create end-to-end digital workflows
- Healthcare data model and Patient 360: Extends the Now Platform with healthcare-specific data structures and patient support capabilities
When to consider ServiceNow:
ServiceNow is best evaluated as a healthcare service orchestration platform. If you need deeper clinical intelligence or EHR-native agentic workflows, assess what additional platforms or integrations will be required.
7. Hyro - Best for healthcare-native patient access
Hyro is a healthcare-focused agentic AI platform built specifically for automating patient communications. The platform is designed from the ground up for healthcare workflows, with a strong emphasis on patient access and digital front door experiences.
Its core value lies in handling high-volume patient interactions, including appointment scheduling, billing inquiries, prescription refills, provider search, and registration, across voice, chat, SMS, and web channels.
From a technical standpoint, Hyro combines large language models with healthcare-specific small language models (SLMs) and knowledge graphs. This hybrid approach helps improve accuracy and contextual understanding in patient interactions, while maintaining compliance and explainability.
However, Hyro’s strength in patient access is also its primary limitation. The platform is largely focused on front-door interactions, rather than broader enterprise orchestration. Organizations looking to extend agentic AI into areas such as clinical workflows, payer operations, or multi-department automation may find its scope narrower compared to more comprehensive platforms.
Additionally, as Hyro is primarily built for patient engagement use cases, healthcare enterprises should evaluate how well it scales across complex, multi-system environments and whether it can serve as a standalone platform or needs to be complemented by other AI systems.
Key AI capabilities of Hyro for healthcare
- Healthcare-native AI agents: Purpose-built voice and chat agents for patient access workflows
- Hybrid AI architecture: Combines LLMs with healthcare-specific SLMs and knowledge graphs
- Omnichannel automation: Supports voice, chat, SMS, and web interactions across the patient journey
- EHR and CRM integrations: Connects with systems like Epic and Salesforce for real-time workflows
- Patient Intelligence Dashboard: Provides visibility into performance, automation rates, and outcomes
- Proactive engagement: Supports outbound patient communication for scheduling, reminders, and follow-ups
When to consider Hyro
Hyro is a good fit for healthcare organizations looking to quickly automate patient access with minimal engineering effort. For broader enterprise-wide agentic AI initiatives, it is important to assess how Hyro fits alongside other platforms that support deeper workflow orchestration and cross-functional automation.
Choosing the right agentic AI platform for healthcare
No single platform is the best fit for every healthcare organization. The right choice depends on your primary pain point, existing technology stack, internal capability, and time-to-value requirements.
Here are the most common decision scenarios:
- If your priority is patient engagement, enterprise workflow automation, and contact centre automation, Kore.ai is purpose-built for this, with pre-built healthcare agents, HIPAA-compliant omnichannel delivery, and deep EHR integration out of the box.
- If your priority is reducing clinical documentation, Oracle Health's Clinical AI Agent is the most mature ambient documentation agent with direct clinical workflow integration.
- If your priority is operational efficiency, ServiceNow is the natural fit for service-heavy administrative workflows around the EHR.
- If your priority is patient access automation, Hyro's healthcare-native agents offer fast deployment and improve scheduling automation across digital channels.
- If you are an SMB or mid-market organization exploring autonomous customer service for the first time, Sierra AI is worth evaluating for its goal-oriented approach.
- If you are evaluating across multiple use cases simultaneously patient engagement, contact centre, payer operations, and workflow automation: Kore.ai remains the broadest purpose-built option for patient engagement, contact centre, and workflow automation across healthcare journeys.
Conclusion: The future of agentic AI in healthcare
The first wave of healthcare AI brought predictive analytics, ambient documentation, and intelligent search. The next wave is agentic: AI systems that pursue goals, coordinate across systems, adapt in real time, and act.
However, this shift will not be uniform. What will separate the leaders is not access to the technology. Every major platform covered in this guide offers capable agentic AI. What will separate them is the ability to deploy that technology at healthcare speed, with the compliance posture, the pre-built clinical context, the EHR integrations, and the governance infrastructure already in place, rather than building it from scratch.
That is where purpose-built matters. Kore.ai is designed for exactly this. It’s a platform built to orchestrate intelligent, autonomous, HIPAA-compliant agents across the full care continuum, from the first patient interaction to the last claims workflow, without the months of custom engineering that general-purpose cloud platforms require.
For healthcare enterprises that are ready to move from experimentation to operationalization, it is the strongest starting point in this guide.
Ready to see how Kore.ai can help you build and scale healthcare AI agents? Schedule a custom demo. Not ready yet? Explore this webinar to learn how agentic AI is reshaping patient access, clinical operations, and revenue cycles.
(Legal disclaimer: The content in this guide is intended solely for general information and does not constitute professional, legal, financial, or procurement advice. All assessments are based on publicly available materials and customer-visible product information. Any mention of competitor limitations is for comparative context, not disparagement.
As vendor products evolve rapidly, details may become outdated. Kore.ai makes no representations or warranties regarding the completeness or accuracy of competitor information, and no party should rely on this article as the sole basis for a purchasing decision.)
