The Operating System for
the War Room.
Causel replaces probabilistic AI summaries with deterministic provenance. We do not hypothesize. We bind every claim to a verifiable coordinate on the evidentiary record.
Gari Boateng
I founded Causel after deploying two high-scale AI-native platforms — one for precision data synthesis, one for autonomous go-to-market orchestration. Through those deployments, I came to a singular conclusion about the AI market: generalist models are structurally incapable of serving defense litigation.
In high-stakes commercial disputes, a 2% hallucination rate isn't an "edge case" — it is a catastrophic system failure. Generalist AI operates on probabilistic guesses; high-stakes defense requires deterministic proof. I built Causel to solve for ground truth.
I moved the intelligence layer from the "generative" to the "adversarial," creating an architecture that doesn't just read documents, but cross-references the entire discovery corpus to surface contradictions that generalist models — and human associate teams — inevitably miss.
Domain Specificity
We don't build wrappers. We build custom inference pipelines that understand the physics of a $50M trial.
Deterministic Work
Our architecture separates reasoning from verification, ensuring every flag is traceable to the source record.
Compounding Assets
Knowledge doesn't reset when associates rotate. Every ingested transcript sharpens your firm's edge.