Consulting
We make AI dependable in production.
Most machine learning fails in production, not in the notebook. We help teams get it running, keep it running, and make it pay for itself.
Available for select work
What we do
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AI in production
Models are the easy part. We help you serve them at real scale and keep them there: latency, cost, drift, and the distance between a demo that impresses and a system that earns its keep.
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Developer velocity with ML
Probabilistic software breaks the habits that served deterministic code. We help your engineers build, test, and reason about ML systems, so the team moves faster instead of flinching.
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Distributed systems
The hard parts live under the model: state, consistency, and failure under load that does not let up. We design, scale, and operate the distributed systems that keep AI services fast and correct.
How we work
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Speaking
Conference talks, workshops, and internal sessions on AI in production, the systems beneath it, and building probabilistic software well. Plain, specific, with the hard parts left in.
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Diagnostic
A short, focused review. We dig into the system, find where it actually hurts, and hand back a plain plan you can act on, with us or without us.
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Embedded build
We work inside your codebase alongside your team, building and hardening the parts that matter, and leave it in better shape than we found it.
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Fractional advisory
A standing line to senior help: architecture calls, reviews, and the occasional save, on a steady retainer rather than a crisis rate.
Start a conversation
Tell us what you are building, what is quietly falling over, or what you want us to talk about.
A short, specific email beats a long form. We read every one.