AI layer
AI that works from your real data.
Assistants, connectors, and customer-facing apps, wired to the systems you already run.
Assistants that answer from your live systems.
What gets built
- Assistants on live data
- Graph-grounded answers
- MCP tool servers
- Demand forecasting
- Customer-facing ChatGPT apps
- Copilot and Claude connectors
- Coding agents wired to your stack
- Guardrails and audit trails
Built with Claude, ChatGPT, Cursor, GitHub Copilot, Claude Code, MCP, Python, TypeScript
Inventory assistant
Demo data
Ask it something.
AI apps built around your business.
An estimator for a house painter. The customer describes the job, your price book does the math, and they see the result before anyone opens a can.
A customer writes
Demo data
Our two-story house is about 2,400 square feet and the paint is peeling on the south side. We want something warmer than the gray.
What the model picked out
- 2 stories
- 2,400 sq ft
- Peeling paint
- Wants a warmer color
Drag to compare. Illustration: a real build previews the customer’s own photo.
Estimate
$13,300 to $15,600
- Heavy prep and repair
- $4,500
- Paint and materials
- $2,700
- Labor
- $7,245
Rates come from the price book, never from the model.
Color
A price and a preview in seconds.
- Quote estimators
- Before-and-after previews
- Product finders
- Intake and triage
- Proposal drafts
- Support assistants
Meet people where they already work.
One connection to your systems, switched on inside the assistants your team already has open.
Microsoft 365 Copilot
Example
Draft a reply to the vendor about the late shipment.
Draft email
Late shipment for DL-204
The 120 desk lamps due on the 14th have not arrived, and 9 open orders are waiting on them. Can you confirm a new delivery date today?
Your engineers ship faster too.
Coding agents guess when all they can see is the code. Connected, they check the real thing and get it right the first time.
Cursor
Example
Add the backorder date to the product page.
- Working
- MCP servers for your data and tickets
- Repo rules agents follow
- Tests agents can run
- Read-only, scoped access
AI builds
AIData
Inventory assistant
Staff ask ChatGPT what is in stock and get the answer from the system of record.
MCP, TypeScript
AIData
Demand forecasting
Every product shows where stock is heading, not only where it is.
Databricks, Python
Have a question your team asks every day?
Thirty minutes to work out whether an assistant could answer it.