AI assistant
Company Brain
Ask about a product in plain language and get the answer, with photos, drawings and charts, straight from the company systems.
82%of 318 pilot answers needed live company data, out of reach without the Brain. See the results ↓
- Role
- Designed and built it
- Timeline
- 2026, a few months
- Status
- Pilot, 10 weeks, 7 users
Product information is spread across many systems: technical data, commercial texts, official photos, technical drawings, prototype tracking and manuals. Each has its own login and its own search, so a simple question like "what material is this model?" means opening three or four programs.
Company Brain is one chat for all of them. Ask in plain language and it reads the answer live from the company systems, with photos, drawings and charts and the source of every piece of data. It runs on our own servers: nothing leaves the company.
See it in action
Sample data throughout. A language model picks the tools, and each tool talks to one company system. Pick a question and follow it through.
- ChatInternal web chat, questions in plain language
- Language modelRuns on our own server on a dedicated GPU, understands the question and picks a tool
- ToolsSmall custom programs, one per source: fetch, calculate, prepare the result
- Company systemsTechnical data, catalog, photos, drawings, prototypes, manuals
Chart the price of this season's collection by category
price_stats · season 26 · 0.4 s
Category C is the widest range, Category A the tightest. Median price per category:
Show me the sheet for MODEL_A01
Which colorway do you want to see?
Pick one, or I will choose for you in a moment.
get_model_sheet · MODEL_A01 · Colorway 03 · 0.6 s
- Brand
- Brand A
- Material
- Acetate
- Season
- 26
- Lens
- Grey gradient
Which prototypes of this collection have been stuck the longest?
prototype_status · 4 results · 0.5 s
Four prototypes have not moved in over two weeks:
- MODEL_A01Sampling34 d
- MODEL_A07Review24 d
- MODEL_B02Sampling18 d
- MODEL_B05Tooling15 d
Pilot results
Measured
- weeks of pilot
- 10
- people, one team
- 7
- answers given
- 318
- queries to company systems
- 566
82% of the answers called at least one tool: without the live connections to the company systems, four answers in five could not have been given at all.
Team estimates, a measured comparison is next
- A full product sheet10-15 min, 3 loginsabout 1 min
- A collection price report30-60 min of exports1-2 min, as a chart
- Finding a standard component5-10 min of browsing1-2 min
On the most cautious scenario of the business case, ten questions a day and two minutes saved on each, opening it to the whole product area pays back in about three months. The software stack is open source, with no licence costs.
Built to spread: one model and one tool per system, so sales, supply chain, quality, IT and HR can reuse the same platform by connecting their own sources.
Design choices
The code does the math
Language models are good with words, less with numbers: averages, comparisons and charts are computed by the tools, and the model only explains the result.
Everything in-house
The model runs on an internal server with its own GPU. No question and no data ever goes to an external service.
Read-only, and gated
It reads the company systems but cannot change them, and each group only sees the tools for its own work.
No copies of the data
Photos, drawings and documents are read from the source at the moment of the question, never copied, so they are always current.
Monitoring
An internal dashboard tracks uptime, server load and which tools get used the most, to decide where to invest next.
What the pilot taught me
What I learned
Small and well taught beats big and alone
The real work is in the tools: giving the model data that is already clean, ordered and short.
Less text is better
Long answers confuse the model and eat memory, so every tool returns only what is needed.
Charts need a point
A chart earns its place when it shows a trend or a comparison, not fifty nearly equal values.
Homelab
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