Why MAIA BRAIN
Five differences, and none of them is a feature.
Every vendor in this market promises a system built for you. What they mean is configuration: a generic system with your field names in it. Here is what is true of MAIA that is not.
01 · Provable, not probabilistic
Deterministic, not probabilistic.
Most AI platforms generate answers. MAIA generates answers it can prove. The same question gets the same answer twice, with the rule that produced it.
MAIA is not configured for your organisation. It is prepared around it: your rules, your vocabulary, your infrastructure, your models, and what is built is yours.
| MAIA does this | Which is worth |
|---|---|
| Answers the same question the same way twice | A number in a board pack can be re-run in front of the person challenging it. |
| Carries the rule that produced each answer, with the record it read | The evidence an auditor asks for already exists on the day they ask. |
| Derives who may see and change a thing from the rules your business authored | A refusal answers why is this the case, not who set this switch. |
| Stops and names the person who must decide, rather than proceeding on a guess | An exception escalates instead of entering the ledger. |
| Applies the policy as written, not a paraphrase of it | The rule in your compliance manual and the rule in the system are one rule. |
The hidden cost of probabilistic AI is the checking.
An output that might be wrong has to be read by a person before it is used. That person is the cost the business case forgot, and it scales with volume. The saving disappears at exactly the point the deployment gets big enough to matter.
Risk. Work you cannot explain is work you cannot sign. In regulated operations, an answer without a traceable reason is not a cheaper answer. It is an unusable one.
Cost. Remove the verification pass and the arithmetic changes shape. The same task done once, not done and then checked.
Revenue. Decisions land in hours rather than at the speed of the review queue.
How an answer is produced
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A hosted assistant
The most plausible continuation, generated. What you can show afterwards: the conversation.
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MAIA BRAIN
Formal symbolic reasoning over admitted facts, verified before it is delivered. What you can show afterwards: a complete audit trail explaining what it did and why, at all times.
Every recommendation traces back to the exact rule or data point behind it. No black box. No guessing.
You claim 99% accuracy. How does that sit with "it does not make mistakes"?
They are about different things. Determinism is the reasoning being reproducible and inspectable: the same inputs and the same rules reach the same conclusion every time, and the conclusion shows its work. Accuracy is how much of a job the system completes. The architecture measures 98.7 with frontier models at both edges and 98.5 with a fine-tuned open 8B model, against 40.2 for a frontier model working alone.
02 · Your knowledge stays yours
It learns your business. It never trains on your data.
Two things are usually sold together and they should be separated. Getting better over time, and sending your data somewhere it improves a model you do not own. MAIA does the first without the second.
| MAIA does this | Which is worth |
|---|---|
| Accumulates what it learns about your business as facts and rules, not weights | Month twelve is worth more than month one, with no new project and no new budget. |
| Uses your own vocabulary. It does not bring one. It uses yours | Nobody is trained to ask questions in a vendor's language. |
| Takes on a new task as it arrives, rather than in the next release | The thing you needed in March is not waiting for a roadmap. |
| Holds what it knows as one exportable, verifiable object | Exit is a copy, not a project. |
| Transfers intellectual property in bespoke work to you on payment in full | What was built around your operation is yours. |
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With a hosted assistant, the knowledge is in the conversation.
What the system understands about your organisation is assembled inside a session and leaves with it. Nothing accumulates that you own, nothing is auditable afterwards, and the next conversation starts again. That is a property of the architecture rather than a policy anybody chose, and no setting changes it.
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What MAIA derives from your records accumulates as one object.
The company brain stays inside your boundary, can be deployed on your own premises, and leaves with you in full if you go. Your documents, your records and everything MAIA derives from them are yours. They are not training data, they are not a corpus, and they are not aggregated across clients.
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Risk
Your operational knowledge does not leave the building, and no competitor's instance gets sharper on the back of your archive.
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Cost
No retraining means fitting MAIA to a new organisation is delivery work with a date in a contract, not a research project priced like one. That is why there is a fourteen-day figure at all.
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Capacity
What the business knows about itself stops being resident in the heads of the four people who have been there longest. It survives their notice period.
03 · The arithmetic, not the pilot
A fraction of the cost.
2.5 times the task success of a frontier model working alone, at around a thirtieth of the inference cost.
Figures from Spine Is All You Need, Table XI, and the MAIA BRAIN technical brief, Table II.
Cost per token is not the point. What you can afford to point AI at is the point.
At frontier rates the economics only work on a narrow slice, so every deployment gets scoped down to a sample. That is why so many pilots succeed and so few scale: the unit cost that was tolerable over one department is prohibitive over the organisation.
The pilot did not fail. The arithmetic did.
At around a thirtieth, the slice stops being necessary. That is what turns AI from a demonstration into an operating system for the business.
What that buys you
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Runs the whole archive, not a sample of it.
The exception you were going to find next quarter is found tonight.
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Reads every document that arrives, every day, rather than the ones somebody flagged.
The flagging step, which is a judgement and a bottleneck, disappears.
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Re-runs a full analysis when a fact changes instead of when the budget allows.
A position is current rather than as at the last review.
04 · Institution-sized, not retrieved
Institution-sized memory.
Over 10 TB of your material in active memory, against a one million token ceiling elsewhere. Reasoning over an institution, not over a retrieved slice.
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1,620
documents read
Documents, with 1,620 of 1,620 checksums matched
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278,768
facts admitted
Admitted facts derived from them
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1 ms
median response
Median response across 61 timed capabilities. 52 of them under 1.5 seconds
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10.4 million
lines of source read
Source lines read, admitting 2.31 million schemes
MAIA BRAIN technical brief, Section I, and Spine Is All You Need.
| MAIA does this | Which is worth |
|---|---|
| Holds your whole organisation's record at once while carrying out a task | The question that spans finance, legal, procurement and operations gets an answer. |
| Reads documents against each other rather than one at a time | Two systems that disagree become visible, because something is finally looking at both. |
| Answers against a densely cross-referenced body of records in milliseconds | The fortnight of somebody emailing four departments does not happen. |
| Keeps the provenance of every fact it holds | The answer arrives with the page it came from. |
The limit nobody prices is the selection step.
If a system can only be shown a million tokens, somebody has to choose which million. That choice is a judgement made before the analysis starts, by a person who does not yet know where the answer is, and it is the step that hides the thing you were looking for.
A system that sees everything does not make that choice.
There is no middle of the context to be lost in.
A fact admitted at ingestion has an address rather than a position. Retrieving it is a lookup whose cost does not depend on how much other material surrounds it, because the store has no middle.
The advantage is widest exactly where the work is densely cross-referential. That tells you precisely which of your problems this is for.
05 · Inside, not beside
You get the AI itself, not software wired to one.
Every other enterprise AI sits beside your organisation. MAIA BRAIN sits inside it. Your data is not queried by the AI. It becomes part of it.
| MAIA does this | Which is worth |
|---|---|
| Runs every function from one reasoning engine rather than one AI link per application | One system to buy, govern and audit, not a vendor per department. |
| Is prepared around your rules, vocabulary, infrastructure and models | The difference between a system built for you and a system with your field names in it. |
| Runs fully private inside your perimeter, in your own tenancy and region, or managed in a region you nominate | Where the record sits is a decision you make. |
| Supports air-gapped operation as a configuration, not a special build | The deployments other vendors cannot bid for. |
| Offers four key-custody models, up to hold-your-own-key in your own HSM | The keys do not have to leave. |
| Treats the language model as a replaceable component, which can be one you own and run on your own GPUs | You are not buying a position on one vendor's roadmap. |
| Hands over intellectual property in bespoke work on payment in full | What was built is an asset on your side of the line. |
An AI link is somebody else's product with a wire attached.
It can be repriced, deprecated or changed under you, and when it changes your process changes with it and nobody asked.
Three departments running three such tools is three vendors, three sets of data-processing terms, three audit surfaces and no single place where the organisation reasons about itself.
Bespoke reaches the infrastructure, not just the software.
Risk. Your dependency is on a component you can replace, not on a supplier you cannot.
Cost. One system rather than an integration estate that grows faster than the value it carries.
Capacity. Functions that currently cannot see each other start operating as one.
The five on one page
If you read nothing else.
| The advantage | What it means for your business |
|---|---|
| Deterministic, not probabilistic | The same question gets the same answer twice, with the rule that produced it. Work you can sign, and an audit trail that exists before the auditor asks. |
| Learns your business. Never trains on your data. | It gets more useful every month as it learns how you work, and none of it leaves to improve a shared model. What it learns is yours and portable. |
| A fraction of the cost | 2.5 times the task success of a frontier model working alone, at around a thirtieth of the inference cost. You stop rationing which data the AI is allowed to look at. |
| Institution-sized memory | Over 10 TB against a one million token ceiling elsewhere. The only AI that holds your whole organisation's data while it does the work. |
| The AI itself, not software wired to one | One system reasoning across every function, prepared around your rules and your infrastructure, on your premises if you want it. Not a vendor per department. |
The next step
Pick the one you doubt most.
Each of the five above ends in something we will show you rather than tell you. Choose whichever you least believe, bring the work it names, and we will run it in a single session.