Our manifesto
Small, instant, invisible.
You don’t need a frontier model for every task
We build small, specialized AI models so that intelligence can be fast, affordable, and invisible — embedded in the products that already do the work.
Engineering notes, field reports, and the thinking behind the systems we build. We publish what worked and what didn't.
case study
Conscious Engines
How NOVO Construction used OpenSpace to reduce photo documentation time by 95%, avoid five travel hours weekly, and map 100 times more images.
article
Conscious Engines
Explore AI for energy and utilities across field service, load, assets, customer operations, documents, safety and optimization.
article
Conscious Engines
How a utility field-service AI copilot combines domain speech, asset history, procedures and controlled work-order actions.
article
A technical guide to energy consumption AI models for meter reconciliation, forecasting, anomalies and constrained optimization.
case study
How Enel used Amazon Bedrock to reduce selected service-desk resolution from one day to under two minutes, with metrics and implementation lessons.
case study
How a European energy operator used sovereign AI to draft field reports in under two minutes using 30,000 historical reports and controlled procedures.
article
Conscious Engines
See 13 companies replacing frontier AI models in production, the savings they report, the tradeoffs they found and the architectures that worked.
article
The Ito open-weight model migration cut median LLM cost per QA run 55%. See the token, latency, failure and provider tradeoffs.
article
The Checkr small language model case shows an $800 monthly estimate versus $7k-$12k GPT-4 paths, with better difficult-case accuracy.
article
This Dropbox open model AI case study shows 45% lower judge error, 1-2 day adaptation and 10-100x more labels at the same cost.
