Applied AI built around one workflow, not a demo.
We build machine learning and generative AI systems scoped to a specific business process — with the monitoring and guardrails to keep them reliable once they're live.
Pilots are easy. Production is where most AI stalls.
A demo that never ships
AI pilots look impressive in a meeting, then stall before production because no one owns monitoring, retraining, or guardrails.
Scoped to one workflow
We scope the system around a single real workflow, build it on your own data, and put MLOps in place from day one, not after launch.
A feature that stays live
An AI feature your team trusts enough to keep running after launch — not a prototype that gets quietly shelved.
Four pieces, built as one system.
Each one works standalone, but they're designed to fit together — most engagements start with one and grow into the rest.
LLM & RAG applications
Assistants and search grounded in your own documents and data, not just a thin wrapper around a public model.
Predictive & recommendation models
Models trained on your operational data to forecast demand, risk, or churn before it shows up in the numbers.
Computer vision & NLP
Document processing, classification, and vision tasks built around your specific inputs, not a generic benchmark.
MLOps & model monitoring
Versioning, drift detection, and retraining pipelines so performance doesn't quietly degrade after launch.
Built for domains where the data has consequences.
This work shows up differently depending on the sector — see the full domain breakdown on the homepage.