When the recommendation is "build it", we build it.
Custom AI systems on your stack, handed over. Custom model training on your data, your weights. On-prem infrastructure, sourced to running. You leave with a running system your team owns, and the knowledge to run it.
We build the system the roadmap points to, inside your environment and under your controls. Every output carries its reasoning and its confidence. Handover is part of the build: your team runs the system end to end before we leave, with a written runbook for the cases where it surprises them.
A model trained on your own definitions. We sit with the people who know the domain, encode what they mean, and write the training pipeline. The model and the labels are yours. A continuous-evaluation loop pairs every output with what actually happened, so calibration drifts visibly. When your definitions shift, you re-label and the model retrains.
When the system has to live inside your walls, we take it from sourcing to a running installation. No third-party hosted dashboard. No data leaving your desk.
The roadmap says build it. The build-versus-buy matrix says why. The decision record says what. Played forward in Glasshouse first.
Our sideWe sit with the people who know the domain and encode what they mean.
Our sideOn Brew Chai, the way we build Glasshouse and this site. Plans, PRs with tests your engineers can review, source on your infrastructure.
Our sideDeployed in your environment, on your cadence. Your team owns the pipeline end to end, with a runbook. The engineering track picks up here.
Your sideNot sure whether to build? Start with Advisory.
