Used in practice by foundational.law
Used on real matters.
- Every system on this site is used by a working law firm first.
- Output is produced by this system and put through its checks.
- As it's tested in practice, the system constantly improves.
We build AI legal technology. Engineered to distrust AI.
Models hallucinate, fabricate, and contradict themselves. We don't ask you to trust the output. We assume it's wrong until it survives everything we throw at it: claims fact-checked, cross-checked, and stress-tested by multiple independent AI systems, nothing taken on trust. The result is knowledge bases you can audit, and deliverables built on them, each with an audit trail showing what the system did, so you never have to take our word for it.
Built on distrust
Fact-checks, cross-checks, and stress tests at every stage.
Living knowledge bases
Deliverables that can stay current instead of going stale, updating as the underlying laws and regulations change.
Stress-tested deliverables
Customized to your needs.
You can make the old work faster. Or build for the new medium.
The old medium, faster
Faster traditional work
Most legal AI accelerates what humans already did: faster document review, faster drafting, faster research. Useful, but it trusts the model, ships one-shot output, and is limited to imitating the old medium.
What we build
Infrastructure for a new medium
Systems that enable fundamentally new work product: living knowledge bases that stay current, compliance guides that update as the law changes, multi-jurisdiction insight at speed, and queryable knowledge systems your team can ask directly. The knowledge base comes first, so everything built on it is fast and already grounded.
This is slower and costs more than one-shot AI. That is the trade, and it's the point.
Distrust isn't a step in our pipeline. It is the pipeline.
In legal work, a hallucinated citation or a fabricated summary is unacceptable. We start from the assumption that the output is wrong, and architect for it, end to end.
- Multi-model fact-checking Claims route through independent agents built on models from different vendors, with different prompts and retrieval paths. A claim advances only if it survives the fact-checks.
- Adversarial testing Every analysis is tested the way opposing counsel would test it. If a position can be broken, our systems are designed to break it first.
- Sealed audit trail Every deliverable documents each check, flag, and fix, so you can see what the system did. Anything the checks couldn't settle is labeled.
Modular systems, combined to meet your needs.
The risk in legal AI comes down to the quality of the knowledge the model works from. Get the knowledge base right and a whole family of deliverables becomes possible.
One stress-tested knowledge base. A family of deliverables.
Living compliance guides
Multi-jurisdiction guides that update as the law changes.
Governance corpora
Frameworks, policy templates, and case studies maintained as regulations evolve.
Jurisdiction reads
The baseline answer plus virtual insight to help you understand the law and the context it operates in.
Built for your audiences
The same analysis shaped for the board, the engineers, or the legal team.
Training materials
Practitioner's guides, onboarding curricula, and companion podcasts drawn from the knowledge base, kept current as it updates.
Ask the agent
Teams ask questions and get answers grounded in the knowledge base, with the audit trail behind them.
Written work product
Research memos, analyses, and contract language with provenance for every claim.
Deep research and analysis
Multi-jurisdiction surveys, novel questions, and comparative analysis, run across the knowledge base and the sources behind it, with every conclusion adversarially tested.
Used in live legal practice.
Foundational Works builds the technology used by foundational.law: live client matters with real deadlines, where deliverables are produced by this system and put through its checks.
Building for the new medium?
If you're a firm or legal department that wants knowledge infrastructure you can actually trust, because it was built not to trust anything, we'd like to hear from you.
Confidential work stays confidential. Zero-retention providers only, no client data in training, privilege boundaries enforced in the infrastructure. How that works