01
AI agents
Software that carries out a task of several steps: reads a request, looks up what it needs, uses your systems through their interfaces and reports what it did. Each agent has a narrow job, limited permissions and a log of every action.
06AI & transformation · Enterprise AI
Enterprise AI development.
Enterprise AI is software that reads, searches, reasons and acts on a company's own data and documents, inside the company's own walls.
We build it to order, around the way you work, or extend and connect the one you already have.
01What it is
In plain words.
Enterprise AI is software that reads, searches, reasons and acts on a company's own data and documents, inside the company's own walls.
Public AI tools know a great deal about the world and nothing about your business. They have not read your contracts, your procedures, your item master or last year's emails, and most companies are rightly unwilling to paste those into someone else's service.
Enterprise AI brings the capability to the data. Models run where the data lives, read what a given user is allowed to read, answer with their sources, and take actions only within limits you set. Built well, it is a colleague who has read everything and forgets nothing. Built carelessly, it is a confident source of errors, which is why the method matters more than the model.
02What it includes
Every part, explained.
10 parts. Each can be built by itself; together they are one system.
02
Multi-agent systems
Several specialised agents working on one problem and checking one another: one extracts, one verifies, one decides, so an error by one is caught by the next. This is the swarm the company is named for.
03
Enterprise AI assistants
An assistant for employees that knows the company's own policies, products, customers and history, answers in context, and respects what each person is permitted to see.
04
AI knowledge systems
The organisation's documents, drawings, contracts, tickets and messages indexed by meaning and kept current, so what the company knows can be found and used.
05
RAG and enterprise knowledge retrieval
Retrieval-augmented generation: the system finds the relevant passages in your own material first and writes its answer from them, citing each source, so answers rest on your documents and not on the model's memory.
06
Intelligent search
Search that understands the question, not only the keywords, across every system and file store, ranked by relevance and filtered by permission.
07
Predictive intelligence
Estimates of what will happen: demand, failure, delay, default, built on your history and reported with their accuracy.
08
Decision intelligence
A recommendation at the point of decision with the evidence, the confidence and the alternatives, and a record of what was decided and why.
09
Natural-language data querying
A question typed in ordinary words, answered from your databases with a figure or a chart and the query that produced it, for people who will never write a query themselves.
10
AI workflow automation
Processes in which a model handles the reading, sorting and drafting, rules handle the rest, and a person approves whatever matters.
Buy, extend or build?
Use a public assistant for general work that involves no sensitive data; it is cheap and capable. Build when the AI must know your own data, act in your own systems, stay inside your network, or be accurate enough that its errors have to be measured and bounded. Where one of our products already fits the problem, start there; it is quicker than building.
Where intelligence fits
Our method is the same throughout: deterministic rules first, semantic understanding next, model reasoning last, and every result carrying a confidence and a record of how it was reached. It runs on your infrastructure with local models by default. It is the approach behind MIDAS, our flagship for material master data, and behind ARGUS, ATLAS and MNEMOS, which are built to apply it to finance, procurement and inventory, and institutional knowledge.
03What it works with
Never on an island.
A system is worth most when it shares its records with the ones beside it.
- Enterprise data platformsA data platform is the place where data from every system in a company is collected, cleaned and kept ready for reporting, analysis and AI.
- Business process automationBusiness process automation hands the repetitive steps of office work to software, so people do the parts that need a person.
- Data analytics and decision systemsAnalytics explains what happened and estimates what will; a decision system puts that estimate in front of the person deciding, at the moment they decide.
- Customer service and help desk systemsA help desk is where every customer question is caught, given to someone, answered and remembered.
- AI transformation and consultingAI consulting answers three questions for a company: where would AI actually help, are we ready for it, and in what order should we do it?
Part of a family
AI, custom software and transformation: Intelligence designed in, software that is yours alone, and the old estate made new.
04How we build it
Five steps, in the open.
- 01
Listen
You describe the work and where it hurts. We look at the systems and the data you have now.
- 02
Specify
A written specification: what the system does, what it does not, what it connects to and how we will know it works. A clear quote before any work starts.
- 03
Build in stages
A working piece at each stage, on real data, so you steer early. The part that matters most comes first.
- 04
Move the data
Existing records mapped, cleaned of duplicates and reconciled against the old system before anything is switched off.
- 05
Hand over
Training, documentation and the keys. Your team can run it, and we keep it working for as long as you want us to.
One set of records underneath
Customers, products, suppliers, people and stock are each defined once. A second system joins the first; it does not start a competing copy.
Runs where you decide
Your own servers, a private cloud or a cloud account that belongs to you. Customer, employee and financial data stays on infrastructure you control.
Yours to keep
You own the code, the data, the configuration and the documentation. There is no licence fee to us and nothing stopping another team from taking it on.
05Questions
Before you ask.
Questions about enterprise AI
What is RAG, and why does it matter?
Retrieval-augmented generation. Before answering, the system retrieves the relevant passages from your own documents and writes the answer from them, with citations. It is how an assistant can answer about your business accurately and show where each statement came from.
What is the difference between an AI agent and a chatbot?
A chatbot answers. An agent acts: it can look things up, call other systems and complete a task of several steps. That power is why agents are built with narrow permissions, limits on what they may do unasked and a full log.
Can it run without sending data to an outside AI provider?
Yes. Local language models on your own servers or private cloud are our default. Data, prompts, indexes and outputs stay on infrastructure you control.
How do you stop an AI system from making things up?
By design and by measurement. Answers are grounded in retrieved sources and cite them, the system is built to say when it does not know, uncertain results go to a person, and accuracy is tested on a labelled sample of your own data before anyone relies on it.
Guides
Plain-language guides on the problems this work solves.
- CRM, ERP, HRMS, CDP, PIM, WMS and the rest: thirty business systems explained in plain wordsBusiness systems · 8 min
- Custom software or off-the-shelf: how to decide whether to build, buy or extendBuild or buy · 3 min
- Custom CRM or off-the-shelf CRM: which does your sales team need?CRM · 3 min
- When does a company need a custom ERP?ERP · 3 min
- All 16 guides on this →
Rather talk it through? Tell us the problem in a few lines and a person will answer it.
Ask us →Tell us how the work runs today.
How the work runs today, what the system must do and what it has to connect to. A person reads it and replies honestly about whether to buy, extend or build.
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