The history gap
Every session starts from zero. Patients recite the same chronology; clinicians rebuild context from notes. Minutes of care are lost before care begins.
Your AI agents shouldn't start over every session. Neither should your patients.
Every session starts from zero. Patients recite the same chronology; clinicians rebuild context from notes. Minutes of care are lost before care begins.
Treatment plans live in one clinician's head. Second opinions, handoffs, and follow-ups lose the thread of what was tried and what's been working.
Mental health progress compounds — or it should. An agent that forgets last week's breakthrough can't support this week's setback.
Conditions, allergies, medications, and preferences carry across sessions and agents — structured, queryable, and updated in place.
Every recommendation tracked through to outcome, so the next clinician knows what's been tried, what worked, and what didn't.
Session-to-session awareness of mood, progress, and setbacks — so therapy doesn't reset on Monday.
Memory respects consent, retention, and role-based access. HIPAA-ready by architecture, not by afterthought.
Patients feel listened to. Clinicians keep their context. Care compounds.
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Whatever your agents do, Synap is the memory layer underneath.
Synap stores conditions, medications, allergies, and treatment history in a structured, queryable memory layer. Every agent interaction picks up where the last session ended — no re-establishing context required.
Yes. Synap provides consent-based scoping, role-based access control, and configurable retention policies designed for HIPAA compliance — so AI agents maintain continuity without compromising PHI.
Synap tracks session-to-session mood patterns, therapeutic progress, and emotional continuity — so therapy agents carry forward last week's breakthrough instead of resetting on Monday.
Synap integrates natively with LangChain, CrewAI, OpenAI Agents SDK, LlamaIndex, and five other frameworks, plus a REST API for any stack.