Nabla + Navina

https://www.nabla.com/

Ambient scribe + longitudinal clinical intelligence (strategic partnership Jul 2025). Live encounter transcript reconciled against historical labs/imaging/notes; condition-suspecting + care-gap engine runs against the reconciled record.

Active · Verified 2026-10-22 · fresh as of 2026-10-22 · 39 cited facts, 8 with a third-party source · 1 recorded change · Suggest a correction

At a glance

Tier
T1
Latest release
not applicable — not OSS fix
License
not applicable — not OSS fix
GitHub
not applicable — no GitHub repo fix
Freshness
2026-10-22 fix
Layer
agent-infra repo fix
Licensing
commercial vendor fix
Deployment locus
cloud vendor fix
Platform vs product
product vendor fix

Memory taxonomy

storage
vector
retrieval
similarity
persistence
long-term
update
extraction
unit
episode
governance
auditable
conflict
editor-in-the-loop

When to use

Optimised for: HIPAA compliance + clinical-grade provenance + EHR integration

Anti-fit: not for non-healthcare verticals; must operate under HIPAA / regional health regulation

Pros & cons

Pros

Ambient clinical scribe that produces structured memory aligned with EMR fields — clinician adoption is high.

Cons

Memory is single-encounter focused; cross-encounter clinical reasoning is less mature.

Claims & capabilities

Nabla $70M Series C (HV Capital); Navina $55M Series C (Goldman Sachs Alts).

Technical surface

API surface
searched not found
Backend storage
searched not found
Deployment
Managed-only
Embedding model
searched not found
Multi-tenancy
GCP + Azure infrastructure; transcripts/notes retained 14 days configurable; audio chunks discarded after processing (no audio retained); customer-tenant separation
MCP
no MCP support advertised — vertical product, no MCP server / client integration documented
A2A
no A2A protocol support advertised — vertical product, no A2A integration documented
OpenTelemetry
no OpenTelemetry integration advertised — vendor logs/observability not publicly documented

Similar systems

Other vertical / domain-specific ai memory in the catalog, ranked by inbound references.

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    Builds long-horizon memory by captioning video segments with VILA, storing captions with timestamps + 3D position coordinates in MilvusDB. At query time, LLM iterates retrieval across text, time, and position modalities. Deployed on Nova Carter robot (Jetson Orin).

  • Abridge T1

    Clinician-assist ambient documentation. Source mapping: every AI-generated summary element traced back to the source utterance. Audit-and-trust layer over episodic memory. Built on proprietary 1.5M+ medical-encounter dataset.

  • ASAPP GenerativeAgent T1

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  • BenevolentAI T1

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  • Causaly T1

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Sources (38 cited facts, 8 third-party)

Each fact links to the page it came from; the badge says who published it (how to read sources).

What changed

Changes to this record's lifecycle, licence, release, pricing and hosting facts, from the catalog's git history. Subscribe (Atom)

  1. 2026-10-22
    • Pricing “Free + paid” → “Free trial; pricing via sales (none published)” source
    • Funding / ownership “$94M total $180M val Series C · 2025-06” → “total $120M ($70M Series C led by HV Capital, 2025-06-17)” source
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