A few examples from recent engagements. Some details changed for confidentiality.
A client had generated a 25k LOC webapp with no users, no monitoring, no clear path to production. We built pipelines and processes for everything from the ground up and executed a successful launch with over 1000 concurrent users.
An ops team was getting paged constantly. Most alerts were false positives or duplicates of the same underlying issue. We replaced their threshold-based alerting with anomaly detection and correlation, so they get fewer, better alerts.
An engineering team wanted to use AI tools but didn't want to sacrifice code quality. We helped them set up AI-assisted code review, test generation, and canary analysis in their deployment pipeline. Everything plugged into their existing workflow, nothing bolted on the side.
"We'd been talking about AI for a year. Within six weeks of working together, we had a model in production that our team actually understood how to maintain."
"The biggest value wasn't the system itself — it was that our team could run it independently after the engagement ended. No ongoing dependency."
"Straightforward, no hype. Told us where AI made sense and where it didn't. Saved us from a six-figure mistake on a project that didn't need ML."
Real-world lessons from AI deployments, delivered when we have something worth sharing.
Happy to talk through it. No pitch — just a conversation about whether this makes sense for you.