Instruction-Tuned
Intelligence
Agents are pre-trained on healthcare standards like ICD, CPT, and CMS policies, fine-tuned with your organization's specific needs. Ability to pass custom instructions, prompts, and labeled data—capturing local rules, workflows, and edge cases. This enables the agent to learn & adapt continuously, aligning with evolving internal logic, clinical operations, and team feedback.
Manage
Hallucinations
Every agent response undergoes a rigorous two-step process. First, the raw output from the LLM is validated using techniques such as self-consistency checks, retrieval-based grounding, knowledge base alignment, and confidence estimation. Then, the validated result is refined by healthcare-specific rules or human-in-the-loop feedback—ensuring decisions are safe, traceable, and grounded in fact.
Federated Data Access
& Governance
Agents securely connect to EHRs, payer systems, clinical documents, imaging, and unstructured text—without compromising HIPAA or local data governance. By maintaining source-level data ownership and respecting access controls, agents surface real-time insights across silos while ensuring compliance, traceability, and auditability.
Workflow
& Rule Orchestration
Agents are pre-trained on healthcare standards like ICD, CPT, and CMS policies, fine-tuned with your organization's specific needs. Ability to pass custom instructions, prompts, and labeled data—capturing local rules, workflows, and edge cases. This enables the agent to learn & adapt continuously, aligning with evolving internal logic, clinical operations, and team feedback.
Responsible
& Compliant AI
Agents are designed with layered guardrails: policy constraints, input/output validation, fallback behaviors, restricted function access, and full trace logging. These measures enforce transparency, prevent unintended actions, and support HIPAA/CMS compliance. By combining runtime governance with auditability, agents remain safe, fair, and aligned with institutional responsibility.
Instruction-Tuned
Intelligence
Agents are available through FHIR-compatible APIs or natural language interfaces—providing structured responses for system-to-system automation or freeform replies for chat-based interaction. This dual-mode delivery supports both developer integration and day-to-day clinical or operations use, enabling fast adoption across technical and non-technical teams.