How do we make it work here?
We build AI into the systems you already run and into your people’s working day.
We put working software on your own data in front of your users, prove it against your measure and take it into production in steps, each ending in a decision.
We build through the Intelligence Delivery Life Cycle.
Every system we build goes through four phases. Each one answers a question, shows you working software and the evidence so far, and ends with your decision.
A software development life cycle describes building software. Ours covers what else has to go right for intelligence to work inside an operation: the decision it supports, the data behind it, the people who use it and the evidence that it works.
See it working on your own data.
A prototype uses extracts of your data once a data-protection decision is recorded. Your team can see the software working and help shape what comes next.
How we built Meissner’s planning platform.
It started with a morning beside the Castlebar planners, went live to the agreed timeline and is now in daily use at two sites.
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On the floor
Sitting with the Castlebar planners to learn how they plan, before any code was written.
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The model on trial
Large language models tested against a purpose-built statistical model on Meissner’s own production history.
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Working software in every release
Each release in front of the planners, with operations, IT and finance involved throughout.
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Acceptance
Refined through acceptance testing with the people who would sign it off.
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Go-live
Live for Castlebar and Camarillo. Meissner’s own teams own and run it.
- 17 weeksfrom concept to go-live
- Any assemblycosted in seconds, including ones the site has never made
- 2 siteswhere planners, supervisors and finance use it every day
The purpose-built model was more accurate than the large language models, so that’s what runs, and it drives every chart and estimate. Read the Meissner case.
Three systems we built that are in daily use.
Live bin occupancy in a biopharma warehouse, Laya Healthcare’s receipt-reading claims system, and a daily service that stops a device maker’s materials expiring on the shelf.
- A biopharma warehouse stopped counting bins by hand.We gave a biopharma warehouse live bin occupancy and daily reports from its own systems, and the morning count that took about three technician-hours has gone.A biopharmaceutical manufacturerAbout 3 hours of technician time returned every day, now the morning bin count has goneTwice the volume the warehouse can now plan for, without adding headcount2 hours to 30 minutes the target for each shift lead’s daily reporting
- Laya Healthcare’s claims system recovered over €800,000 in four months.We built Laya Healthcare’s receipt-reading claims system and call summaries, and we support four production capabilities under contract, up from one.Laya Healthcare€800,000+ recovered in the first four months, against a €300,000 business case6,000 receipts an hour absorbed at peak member upload3 seconds from the end of a call to its summary, category and sentiment
- Expiring stock matched to the orders that will use it.We built a daily service that tells a device maker where to move material before it expires. It was writing off over €40,000 a month.A medical device manufacturerEvery morning movement recommendations, in production under a maintained support contract7 days the window in which recommendations from confirmed production orders carry full confidence€40,000+ a month in expired materials, the write-off the service was built to cut; some months reached €75,000
What IT and compliance teams ask before a build.
Will it work with the systems we already have?
Yes, and it can draw on several at once. In one biopharma warehouse the system draws from SAP Extended Warehouse Management and Oracle Warehouse Management through Databricks.
Where does our data go?
Where you decide. Meissner’s platform runs in Meissner’s own Azure environment, with Entra ID single sign-on. Every project uses a segregated environment and named identities, and no client’s data is reused for another without a documented legal basis and your explicit authorisation. Security and compliance.
Which model do you use?
Whichever tests best on your own records. We test frontier and local models against each other before we choose, and use a local model when your data can’t leave.
Will it count as regulated software?
We start with decision support that reads from your systems and writes nothing back, and your compliance owners decide how it’s classified and tested. Being read-only doesn’t settle that on its own. Each sector page covers the rules that apply there.
How long does a build take?
It depends on the decisions involved more than on the size of your organisation. Meissner’s planning platform, above, took 17 weeks from concept to go-live.
How do you price it?
How we contract depends on how much we know. Up to and including the Controlled Trial we work on time and materials or a fixed time box. Once the trial has settled the unknowns, the build has a firm price. With clients we already know, it can come sooner.
Do you start from scratch each time?
No. We reuse components, such as an LLM integration core, a content extractor and a knowledge agent, so each new area costs less to integrate than the last. Your core systems and the platforms you’ve already bought stay as they are.
Who looks after it once it’s live?
The team that built it, under Operate, or your own teams with our support. How Operate works.