Millhaus Technology Services
Most AI Projects Fail
Despite their utility, many businesses struggle to realize a return on their language model investments. This capability overhang between what frontier models can do and the reality on the ground is the gap we help our clients close.
Language models alone don't create business value.
The companies getting value from AI are the ones that are re-thinking business models around it, not merely treating it as a new tool.
We help clients bridge the gap between language model and business model.
39%1
report enterprise-level EBIT impact from AI
5%2
reach AI value at scale; ~60% see little to none
30%3
of GenAI projects abandoned after proof of concept
50-90%4
of code at Anthropic is now written by AI
Sources: 1 McKinsey 2025, 2 BCG 2025, 3 Gartner 2024, 4 LessWrong 2025.
The leverage comes from the harness.
A language model by itself is like a horse without a saddle. Incredible power, but impossible to ride. The real work is in building the harness around the model: connecting it to data, designing the workflows, adding guardrails, and making it observable. That's what separates a party trick from a production system.
That's what we build.
We fit the harness.
Four focused services — each addressing a different part of what it takes to go from language model to working system.
Context Engineering
Connect the model to your data and tools so it gives grounded answers and executes real actions with traceable context.
Generative Media
Set up a media pipeline your creative team can actually run day-to-day — prompt kits, model routing, review flows, all of it.
Agentic Advisory
Figure out which agents to build, who owns them, and how to govern them — before you commit engineering time.
Rapid Apps
Build a production AI app around one priority workflow, with clear milestones and a clean handoff.
How we work
We focus on one workflow, measure from the start, and deliver a system your team can operate.
Discover
Map one workflow end to end. Define what good looks like. Set the baseline we'll measure against.
Design
Lock in architecture, data sources, approval gates, and who owns what before a line of code is written.
Build
Ship a production system on real data — monitored, documented, and ready for your team to run.
Next step
Tell us the workflow.
We'll help you plan next steps.
Bring the problem, the people, and what good looks like. We'll respond with a clear recommendation and next steps.