Artificial intelligence products · Abu Dhabi
Software for organisations that have outgrown how they decide
Red Bear builds three products. One governs how an organisation makes decisions. One helps private equity firms turn their own expertise into something they can prove. One helps architects design systems without losing the reasoning along the way. All three are built on the same engines.
Start here
An organisation measures everything it does, and almost nothing about how it decided to do it
Your systems record the transaction in exhaustive detail: what was spent, shipped, booked and approved. They record almost nothing about the judgement that produced it — who decided, on what evidence, under whose authority, and whether it turned out to be right.
For a long time that did not matter much, because decisions were made by a small number of people who could be asked. It matters now, because authority has been distributed far faster than judgement: to front-line staff, to outsourced teams, and increasingly to AI agents making decisions with real commercial and regulatory consequence.
All three products come from the same observation, applied in three different places.
01
For large organisations
Red Bear: Enterprise Decision Intelligence
For any large organisation trying to move faster without losing control of what gets decided in its name — including the decisions now being made by AI agents.
What it is
A single record of the decisions your organisation makes — by people, by software and by AI agents — holding who decided, why, under what authority, and what happened next.
What it changes
- You could list, this afternoon, the ten decisions that have been waiting longest and who they are waiting on.
- A senior leader can stop being the approval queue without losing sight of anything — under an approval model you see what reached your desk; under this you see everything, including what was settled locally.
- You can widen a good team's latitude with an argument instead of a feeling, and tighten oversight openly, with a stated reason and a date it ends.
- You can let agents decide inside limits, because each has an owner, a scope, an off switch and a record.
How it works
- Decisions get recorded where they are already made In meetings, email, your business systems, a portal, and through an interface agents must call before they act. Recording costs the decider seconds, and must never be the reason a decision is slower than it was before.
- Each one is checked and sent to someone who can settle it A rule sets the hard limits, a per-person setting says how much room that individual has inside them, and routing finds someone who is both authorised and actually available. Inside someone's own discretion it passes; at the edge it becomes a human step.
- What happened is attached afterwards, and compared with what was expected How well the decision was reasoned is scored separately from how it turned out, so a sound decision that got unlucky is not treated as a bad one.
02
For private equity
Red Bear: Alpha Engine
For sector-focused private equity firms whose edge is repeatable — the same operating playbooks, applied company after company — and who cannot currently prove it.
What it is
One workbench for the whole deal-to-value lifecycle, in which every figure carries where it came from, and what the firm learns owning one company is written down for the next deal.
Status. In development. We are looking for two firms to work with as design partners.
What it changes
- Hours per company before judgement begins become minutes to a sourced profile.
- Coverage stops being capped by headcount, so the good business nobody reached becomes reachable.
- Reasoning outlives the analyst who built it.
- The firm can state its own contribution to an outcome and show the working — to an investor, to a board, or to itself.
How it works
- The analyst starts from a populated profile, not a blank page Every value carries its source, its date and whether it was verified, inferred or supplied by an analyst. Where sources disagree, both are kept. Any figure can be overridden with a reason, and the original stays underneath.
- The firm's own judgement gets recorded as it is applied What the firm's money would add beyond what would happen anyway; what it does not know, ranked by whether it would change the decision; and the alternatives and evidence frozen at the moment the committee calls it.
- The prediction is scored against what actually happened Over the hold, with the firm's contribution separated from sector and market movement — and the playbooks that worked become reusable, reviewed before they go live and matched to the companies they actually fit.
03
For consultancies, service providers and large IT functions
Red Bear: Architecture Engine
For consultancies, managed service providers, systems integrators and large organisations running enterprise architecture, enterprise ontology, and AI or cloud solution design.
What it is
A workbench that carries a solution architect from the first customer conversation to an approved design pack, keeping every requirement traceable to the thing the customer actually said.
Status. Prototype. Being built out area by area with a starter catalogue of reference packs.
What it changes
- The understanding captured in a workshop stops being thrown away after the proposal is written.
- A disputed requirement is settled by looking rather than remembering.
- Design quality stops depending on which architect happened to run the workshop.
- For a group or federation, the same capability funded in three places becomes visible before it is funded a fourth time.
How it works
- The workshop runs in front of the portal The architect picks a pack — a reference architecture plus the design decisions it forces, and therefore the questions that must be asked — and captures the customer's answers as stated needs, marking what is an assumption and what is a dependency on the customer.
- Requirements are derived from those needs, and stay linked to them Requirements, user stories, assumptions, dependencies and risks are drafted from what was captured; the architect edits and accepts each one. Every requirement points back at the thing the customer said.
- Documents are generated in sequence, through approval gates Proposal, then requirements, then the architecture, then detailed designs — each built from what was accepted before it, so the documents agree with each other. Reviewers see only their own sections, with severity-rated feedback and routing that goes round whoever is away.
What they share
Nine engines, three products
The three are not separate products that happen to share a logo. They are assembled from the same engines — a model of what an organisation is, a record of how it decided, and an honest measure of whether that worked. Each engine is described in full, with how it is built.
The thinking behind it
Enterprise Decision Governance
A four-book series on governing decisions across an organisation, whether a person or an AI agent makes them. Written by Dr Dan Oliver, Red Bear AI's Chief Technology Officer.
Four books: The Framework, The Use Cases, The Architecture, The Culture. None is published yet.
Getting in touch
Tell us which of these sounds like your organisation
There is no form on this site and nothing asks for your email address before it will show you anything. If one of the three is close to a problem you actually have, write to us and say which — a paragraph about your situation is enough to get a straight answer about whether we can help, including when the answer is no.