Where ONTO is the right choice.
Four kinds of work where the standard autonomous loop fails — and where ONTO's primitives (Plan Mode, typed memory, consent scopes) map directly to the problem.
Healthcare
Clinical documentation copilots, intake triage, and care-team handoff agents that pass HIPAA review.
Primitives that matter
- Plan Mode for clinical orders
- Role-based consent scopes (intake nurse vs clinician)
- Audit trail with regulation tags [phi]
- On-prem deployment
Customer support
Per-account memory copilots with policy-driven auto-approval for refunds, escalations, and account changes.
Primitives that matter
- Per-tenant memory scoping
- Tier-based Plan Mode approval
- Audit-ready cost meter
- MCP for CRM/billing tools
Personal AI
Long-running personal assistants — email triage, calendar, notes — with durable user-owned memory.
Primitives that matter
- UPO + SMO for cross-session memory
- Async writes and background summarization
- Four-level extraction
- Open-weight defaults
Research
Document ingestion and synthesis agents that extract typed claims across many papers with conflict resolution.
Primitives that matter
- Four-level extraction at domain scope
- Conflict detection surfaces as Plan Mode tasks
- Background memory worker
- Per-researcher cost rollups
Don't see your vertical? It probably fits.
If your problem involves durable user memory, role-based consent, or human approval before action, ONTO is built for it. Open an issue with your use case.