AI wired into the tools
you already run.

Integrations, data pipelines and custom MCP servers, tested against your actual stack.

Connects to

Built for your stack, not a marketplace.

Each connector is written and tested against the system you actually run.

CRM systems
Databases
Custom MCP servers
Practice software

Each connector gets only the access you grant, and nothing past that line.

From the workbench

A real one, running right now.

The inbox reads itself before I do.

Mail lands, gets read, sorted by intent and matched to a contact, and a draft reply is waiting before a person opens it.

See what else runs in the Labs
Source
Incoming mail
AI layer
Read, sorted, matched
Destination
Draft reply, filed and ready
What you get

Something that keeps running.

Not a one-off script that breaks the first time a schema changes.

Built for Data-heavy teams Agencies Anyone stitching exports by hand
  • Tested against your real data, not a demo dataset.
  • Watched, not hoped. Monitoring and error alerts come to me, not you.
  • EU-hosted throughout. The data path stays in Germany. Nothing leaves that you did not send.
The build

Mapped, built, watched, handed over.

01

Map your systems

Where the data lives, where it needs to go, and what shape it is in when it gets there.

02

Build and test

Each connector runs against your real records first, edge cases included.

03

Run and monitor

It goes live with monitoring and error alerts pointed at me.

04

Document and hand over

The map of what connects to what, written down and handed over.

Priced to the pipeline, not per seat.

Once it is mapped you get a fixed price in writing, split into a build and an optional run-and-maintain.

Ask for a quote
What shapes it
  • How many systems connect, and how cleanly they expose data
  • Volume of data, and how often it moves
  • Whether custom MCP or API work is needed

Have data stuck in the wrong places?

Talk about a pipeline