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Legal OSINT platforms
AI-driven collection, entity resolution, dossier assembly, and citation-grade retrieval for counsel and investigators. Built for indefinite retention, chain-of-custody thinking, and operator workflows — not chat demos.
Ellabara · neural ops division
AI systems that see, reason, and execute for high-stakes work.
We design OSINT research platforms for legal teams, multi-agent architectures that stay coherent under load, and private AI infrastructure that does not leak, flake, or handwave.
Legal OSINT Evidence-grade research systems
Agent stacks Orchestration that survives prod
Private GPU DGX-class local inference
What we build
Three lanes. One standard: systems that hold under pressure.
No slideware. We ship research tools, agent platforms, and infrastructure your team can operate.
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Multi-agent architecture
Parent/child orchestration, durable task graphs, model routing, tool confinement, and review gates. Agents that finish work, hand off cleanly, and leave an audit trail.
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Private AI infrastructure
Local LLM serving on DGX-class hardware, mesh networking, CI/CD for model + app releases, and hardened production hosts. Own the stack. Control the data.
Humans in the loop
AI does the grind. Operators keep the judgment.
Ellabara systems are built for people who run high-stakes work — counsel, analysts, and engineers — with clear handoffs between model output and human decisions.
Human judgment gates
Shared review between counsel and operators — not siloed chat windows and unbounded agents.
Operator consoles
Research and agent surfaces designed for humans: provenance, review gates, and work you can stand behind.
Owned infrastructure
People who can walk the racks, read the telemetry, and promote releases without guessing.
Why teams call us
Because generic AI shops cannot run the hard path.
- Counsel needs research systems that cite, retain, and survive discovery pressure — not unbounded chat.
- Agent demos collapse the first week in production. We design for isolation, retries, and human gates.
- Cloud-only inference is the wrong trust model for sensitive legal and investigative work.
- We already operate multi-host private meshes, release pipelines, and research factories end-to-end.
Engagement shapes
How work usually starts
Spike (1–2 weeks)
Architecture + threat model + working prototype on your data sample.
Build lane (4–12 weeks)
Production system with operators, monitoring, docs, and handoff.
Embedded lab
Ongoing architecture, agent fleet, and infra ownership for complex programs.
Method
From signal to shipped system.
Map reality
Sources, constraints, legal posture, and what “done” means for operators — not for a pitch deck.
Design the machine
Data plane, agent graph, model routing, storage tiers, and failure modes drawn before code sprawl.
Ship with proof
Working software, evals, audits, and runbooks. Screenshots are not acceptance.
Operate & harden
Monitoring, backup, least privilege, and iteration loops that keep improving after launch.
Ready when you are
Bring the hard problem.
If you need a legal research system, an agent platform, or a private AI stack that does not embarrass you in production — Ellabara builds it.