What we do
MAIA BRAIN builds solutions for businesses and organisations.
Every offering is prepared around you. Not configured for you. One architecture fits a new organisation with no retraining, which is why this is delivery work with a date on it rather than a research project.
The capabilities, as operations
What MAIA actually does on a Tuesday.
Each line is an operation, not a position. The left column is the work. The right column is what it is worth to you.
- Reads the question in ordinary English and answers it against the whole record
- Show me contracts where margin dropped below target this quarter and tell me why. No filters, no setup, and the rule and the document behind the answer come with it. The report nobody had time to build gets asked for instead.
- Reads every document on arrival, in whatever form it turns up in
- Typed, spoken, a file that lands, another system pushing something through. Provenance kept, so the answer arrives with the page it came from. The document set is answerable on the day it lands, not the week after somebody indexed it.
- Reads the order, the contract, the receipt and the invoice together and releases what clears
- Matches carry on automatically. Exceptions go to a person, and the decision and the evidence behind it stay on the record. The three-way match stops being somebody's afternoon.
- Reasons through a real exception instead of escalating it
- A mid-contract change, a partial delivery, an unusual claim. Rule-based automation breaks on these. Pure neural AI guesses. Only the exceptions you defined reach a person.
- Watches every transaction continuously and raises the ones that break a pattern
- Not a sample, and not the ones somebody flagged. The flagging step, which is a judgement and a bottleneck, disappears. Exception-based review instead of investigating everything.
- Checks what happened against the policy as written, and records the check
- The rule in your compliance manual and the rule in the system are one rule, not a paraphrase of each other. The evidence an auditor asks for already exists on the day they ask.
- Triggers the approved action when the data condition is met
- Buying, scheduling, reconciling, drafting, replying. Inside the authority your own rules derive, with human confirmation where you have set it. Routine work closes without a queue.
- Correlates records held in systems that cannot see each other
- Two systems that disagree become visible, because something is finally reading both. The contradiction surfaces before the year-end does.
- Builds the scheduled report, the board pack and the commentary from live data
- Data is not copied, archived or frozen. Every figure reflects your current operational state. The pack is current on the morning of the meeting.
- Forecasts and identifies trends across the whole record rather than a sample
- Re-run when a fact changes rather than when the budget allows. A position is current rather than as at the last review.
- Audits your operations against your own stated specifications, without being asked
- Inefficiencies surface in real time rather than in a review cycle. The improvement is found by the system, not by the consultant you hired to look for it.
- Connects to the BI tools, APIs and custom applications you already run
- Integration is built to the interfaces your systems already expose, or another approved route where there is no API. Nobody is asked to abandon the dashboard they trust.
- Parses a repository deterministically and derives the repair
- One admitted scheme per procedure, from which a fix follows as a conclusion rather than a suggestion. A code review that answers why, not just where.
- Names the person who must decide, and stops
- A refusal is a result. It is a conclusion drawn from your own rules, and it can be explained back to you in terms of the rule that produced it. A system that finished, and stopped, rather than one that guessed.
Two worked sequences
Assistants tell you. Agents act.
An assistant supplies information. An agent observes, analyses, decides, acts, verifies and escalates. An assistant tells you an invoice is overdue.
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An invoice arrives
MAIA watches incoming invoices. It pulls out the relevant information. It checks the invoice against the supplier record, against the purchase order, against what was received. Matches carry on automatically. Exceptions go to a person. The decision and the evidence behind it stay on the record.
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A payment fails
MAIA reads why. It checks the alternatives on file. The customer gets the approved recovery message. The payment succeeds on another route. The CRM records the outcome, and the whole chain is on the record.
How it is built
Neural reads. Symbolic decides.
Reading what a company produces and applying what a company has decided are different problems, usually solved by different systems. MAIA does both at once.
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Neural networks
Understands natural language and context. Recognises patterns across all your data. Learns continuously from your operations. Handles ambiguity, exceptions and edge cases.
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Symbolic reasoning
Applies formal logic and structured rules. Enforces your policies and compliance requirements. Explains every decision with a traceable audit trail. Operates within defined boundaries. Always.
An AI that learns like a domain expert and reasons with the precision of formal logic, in every decision, simultaneously.
One of the twelve
The bespoke AI ERP.
If you are replacing a system rather than adding one, this is the offering that answers you. It is one section of what we do, not the whole of it.
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01
Connect
MAIA links to every data source in the organisation. ERP systems, CRMs, spreadsheets, documents, databases, real-time feeds. All of it.
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02
Comprehend
The data is not stored and queried. It is understood. MAIA builds a complete, living model of how your organisation operates, thinks and decides.
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03
Build
MAIA constructs a bespoke AI ERP built precisely for your organisation. A system built from scratch around your reality.
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04
Evolve
As you assign new tasks, MAIA teaches itself how to complete them. The ERP adapts continuously. No redeployments. No consultants.
Your ERP is not configured. It is built.
No two MAIA ERP systems are alike. The structure, logic and workflows are generated to fit your exact operational model. All existing software across the organisation can be controlled from a single interface, and users assign tasks in natural language.
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What that replaces
Traditional ERP projects run for years. MAIA reaches production from day 9 of 14 days. Every workflow, every exception, every rule, reflected as you actually operate rather than as a vendor's template assumes you do.
Today, and with MAIA
What changes.
| Capability | Today | With MAIA |
|---|---|---|
| Decision explainability | Not available | Full trace, every time |
| Policy and compliance enforcement | Manual override required | Built into the reasoning layer |
| Memory | A retrieved slice | Over 10 TB in active context |
| Exception handling | Falls back to human escalation | Reasoned resolution with an audit trail |
| Cross-department intelligence | Siloed per module | Unified across all systems |
| Self-improvement without drift | Requires manual retraining | Continuous, policy-anchored learning |
| Review | Every transaction investigated | Only the exceptions you defined |
| Auditability | Limited, reconstructed afterwards | The audit trail is the database |
The questions you were going to ask in the meeting
Answered here instead.
Will it work with our existing software?
Integration is built to the interfaces your systems already expose, or another approved route where there is no API. Your existing applications are not replaced. They become surfaces of one intelligence.
What happens when MAIA is uncertain?
It stops and names the person who must decide. A refusal is a conclusion drawn from your own rules, and it is explained in terms of the rule that produced it. It does not proceed on a guess.
Can our people override it, and who is responsible?
High-impact operations require human sign-off before execution. Every action is attributed to a person or a named process, with the approval it moved under. Automate the routine, escalate the exceptions, keep people where judgement matters.
How do we audit a decision?
Every decision carries what was read, which rule applied and what authority it acted under. Because the record is an append-only history rather than a mutable store, the audit trail is not a feature that can lag or be switched off. The audit trail is the database.
How long does implementation take, and how much internal work is needed?
14 days from decision to live, in three phases, with read-only access throughout the initial stages. Your own experts validate the reasoning in days 5 to 8. That session is the main call on your people's time.
What if our processes change?
MAIA takes on a new task as it arrives rather than in the next release. Changing what MAIA is permitted to do is itself governed: proposed, reviewed by a named human, recorded in the history with the approver against it.
Does this mean redundancies?
Not by default, and we do not sell it that way. A team handling 5,000 transactions a month might handle 10,000 without doubling headcount. The capacity is the point.
How do we know it created value?
Pick the task before we start, and measure the same task afterwards. Current annual cost against future operating cost. We would rather argue a conservative case you can check than the best one we can construct.
The next step
Bring a task your team does every week.
Something slow because the answer sits across four systems. We will show you what MAIA reads, what it concludes and under what authority it acted. One session, and you keep what comes out of it.