Most AI
projects die
at the demo.
What we offer
Indicative placeholder pricing. Every figure on this sample site is written as a placeholder.
Discovery sprint
Two weeks to establish whether the problem is worth solving.
Evaluation harness
A measurable baseline and a test set before any model is chosen.
Retrieval systems
Document search and question answering over your own material.
Workflow automation
Extraction, classification and routing built into existing systems.
Model operations
Monitoring, drift detection and a rollback path that works.
Team enablement
Your engineers own it when we leave, with documentation and handover.
Applied machine learning for unglamorous problems
Baselines first
We measure the current process before proposing anything, so improvement is provable.
Runs in your environment
Deployed into your cloud, your data boundary, your access controls.
A rollback path
Every system we ship can be turned off without taking the business with it.
Handover is the deliverable
Documentation, tests and a team that can maintain it without us.
What people say
These quotations are invented for this sample and are not real customer feedback.
“They told us not to build the first thing we asked for. That saved the budget.”Sample client
“It has been in production for a year and nobody has had to call them.”Sample client
“The evaluation harness outlived the project and we still use it.”Sample client
Three steps, no mystery
Measure
Establish the baseline before anything is built.
Build
Into your environment, with monitoring and a way to turn it off.
Hand over
Documentation, tests and a team that owns it.
Before you ask
That is the only measure we accept. Demos are not deliverables.
In your environment. We deploy into your boundary, not ours.
The discovery sprint exists to find that out for a small fixed cost.
Your team, with documentation, tests and a handover period.
Book a discovery call
Bring the problem, not the solution. We will tell you honestly if it is worth building.
Book a call →Send a message
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