Give your AI agents a decision layer they can trust

Every regulated process narrows to one step: approve or refer, pay or investigate, compliant or not. That judgement sits with a handful of experts, and there are only so many cases they can reach.

Generative AI can’t take it off them. It’s excellent with language and probabilistic in judgement, so it gives different answers to the same question, can’t guarantee fidelity to your policy, and can’t justify an outcome to a regulator. Adding human review doesn’t rescue it. Reviewers tend to accept what the machine puts in front of them, so the errors go through anyway.

Rainbird captures how your experts reason and applies it to every case, at volume, with the same answer every time.

Language models approximate. Rainbird calculates. Your policy becomes an explicit Rainbird knowledge graph, reasoned over case by case, even where rules interact and the data is incomplete.

Probabilistic systems drift. Rainbird’s outcomes are deterministic by construction: identical inputs always produce identical, policy-faithful results, with no hallucination anywhere in the decision path.

When a customer, auditor or supervisor asks why, “the model predicted it” isn’t an answer. Rainbird returns the exact rules, evidence and reasoning behind each decision as a proof tree, in language a person can read.

Where your organisation’s knowledge is authored, inspected, tested and governed.
AI-powered, no-code, for experts, versioned and controlled for the enterprise.

The deterministic core.
Symbolic inference over your Rainbird knowledge graphs, with calibrated certainty and a clear, complete proof tree attached to every outcome.

The Rainbird Foundry cleanses, organises, codifies and deploys your knowledge at scale, giving agents a policy architecture they can reason over, broad or deep.

Gilad Amir · Digital Operating Partner, Pollen Street Capital

Dan Francis · Director of Innovation and Digital, BDO

Clem Mactaggart · Chief Strategy Officer, Killik & Co

Bring us a decision your business must get right

We will show you the knowledge model, the reasoning and the proof, live, on your own use case.
From first conversation to working decision service in weeks, not quarters.