We take the models your team already built and get them running in prod — with monitoring, rollback, and CI/CD that doesn't break at 2am.
What we do
No strategy decks, no hand-offs — just engineers who've seen what breaks at scale and know how to fix it.
01
From notebook to real traffic.
Most teams can get a model working in a notebook. We specialize in the hard part — getting it serving real traffic with monitoring, rollback, and eval harnesses in place.
02
Your infrastructure, not a vendor's.
Experiment tracking, model registry, deployment pipelines, and alerting — built on your existing cloud infrastructure, not a vendor platform you'll be stuck with.
03
Fix the foundation.
Silent data drift, broken ingestion, schema drift — these kill prod AI systems quietly. We fix the data layer before it poisons your predictions.
04
Relevance, speed, cost.
We optimize vector DB config, chunking strategy, and retrieval pipelines for the metrics that matter: answer relevance, latency, and cost per query.
How we work
Fixed scope. Fixed timeline. You know what you're getting before we start.
Deep dive into your AI and data stack. We map every model, pipeline, and integration point. You get a prioritized list of what's broken, what's fragile, and what's costing you money.
Architecture decisions documented as code — not slides. A technical blueprint your team can execute on, with clear sequencing and tradeoff analysis for every recommendation.
We build alongside your team. Every deliverable is production-grade from day one — tested, monitored, documented, and deployed with rollback capability.
We work with the tools you already use
Start here
A structured assessment of your AI/data stack with prioritized, actionable recommendations. Not a slide deck — a technical blueprint you can execute on.
Who we are
We're engineers who've spent years shipping AI at scale and got tired of watching good models die in staging. Sovont exists to fix that.
With deep experience in production ML and hardened data infrastructure, we focus exclusively on the technical gap between a working demo and a resilient production system.
FAQ
Startups to mid-market. We've helped 5-person ML teams and 50-engineer data orgs alike.
No. We specialize in the engineering required to make the models you've already built production-ready.
That's our most popular starting point. $3,000, one week, no strings attached.
Yes. We build on your cloud and your stack. No proprietary platforms or vendor lock-in.
We only take on 2-3 engagements at a time to ensure high-quality delivery. Reach out early to secure a slot.
Get in touch
Ready to get your AI systems running for real? We respond within 24 hours.
Toronto, Canada