Filevine LOIS
Embedded in case-management platform. Holds full scope of every matter — deadlines, billing, discovery, communications, negotiation history — as live context for every query. Case data is the context, not a separate retrieval corpus.
At a glance
- Type
- Whole-matter context as live LLM input
- Tier
- T1
- Created
- 2014 (founded 2014 by Nathan Morris Ryan Anderson Jim Blake; Salt Lake City UT)
- Latest release
- not applicable — not OSS
- License
- not applicable — not OSS
- GitHub
- not applicable — no GitHub repo
- Pricing
- Enterprise only
- Funding
- $508M total Undisclosed (2 rounds combined) · 2023-20
Taxonomy
- storage
- relational
- retrieval
- injection
- persistence
- long-term
- update
- overwrite
- unit
- document
- governance
- auditable
- conflict
- document-version
When to use
Optimised for: matter-scoped privilege + audit + firm-precedent memory
Anti-fit: not for non-legal verticals; not for self-represented litigants
Pros & cons
Pros
Memory grounded in case management workflow — knows where matter / client / document fit, not just text content.
Cons
Tied to Filevine's case management platform; not useful as a standalone memory layer.
Claims & capabilities
$400M raised across two 2025 rounds (Insight, Accel, Halo). ~6k customers, 100k legal professionals.
Technical surface
- API surface
- searched not found
- Backend storage
- searched not found
- Deployment
- Managed-only
- Embedding model
- searched not found
- Multi-tenancy
- Logical multi-tenant with audited HIPAA + SOC 2 controls; BAA available
- 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.
- NVIDIA ReMEmbR T3
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
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- ASAPP GenerativeAgent T1
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- BenevolentAI T1
Target identification / drug repurposing / mechanism tracing. 85+ data sources, petabyte-scale, rebuilt every few weeks. Wet-lab results re-enter the graph and shift downstream predictions — institutional experimental memory closing a feedback loop.
- Causaly T1
Drug discovery / target identification / causal mechanism tracing. The graph is the memory: 7 years of curated biomedical cause-effect relationships compounding with each new ingestion. Scientific RAG retrieves from a versioned causal substrate.
- Character.ai T1
Chat Memories (user-defined facts), auto-memories for c.ai+ subscribers, pinned memories, in-context retention. PipSqueak 2 model (April 2026) reduces in-conversation drift. Memory Visualization meter forthcoming.