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AI Infrastructure Studio

AI infrastructure,
from power to production.

We plan and build GPU compute and the power to run it, get your models serving real traffic, and build production AI for utilities and energy companies.

4 wks
Avg. time to production
Zero
Vendor lock-in
100%
Your cloud, your infra
Day 1
Production-grade delivery

What we do

Compute, power, and production AI. One team.

No strategy decks, no hand-offs — just engineers who've seen what breaks at scale and know how to fix it.

01 · HPC & Power Buildout

The GPUs are the easy part. Power isn't.

Compute and power, planned together.

We size the compute your workloads need, compare buying, colocating and renting, work out the power and cooling it takes, and support the build through acceptance testing. Stamped electrical design stays with licensed engineers; we work alongside yours.

See the Compute & Power Plan
GPU Cluster SizingBuild vs. Rent AnalysisPower & Cooling PlanningAcceptance Testing

02 · AI for Utilities & Energy

Forecasts that survive a heat wave.

Production AI for the power sector.

Load and DER forecasting, asset and outage risk models, and grid analytics for utilities and energy companies — monitored, versioned and built to keep working when conditions change.

Talk to us about grid AI
Load ForecastingDER ForecastingAsset Risk ModelsGrid Analytics

03 · AI Production Launchpad

Pilots don't scare us. Production does.

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.

Read our posts on production AI
Model ServingBlue/Green DeploysEval HarnessesRollback Pipelines

04 · MLOps Foundations

MLOps without the bloat.

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.

Read our posts on MLOps
CI/CD PipelinesModel RegistryExperiment TrackingObservability

05 · Data Platform Hardening

Your data pipeline is lying to your model.

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.

Read our posts on data engineering
Drift DetectionSchema ValidationData LineageQuality Gates

06 · RAG & Knowledge Systems

RAG that works under load.

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.

Read our posts on RAG
Vector Search TuningChunking StrategyHybrid RetrievalEval Suites

How we work

Predictable process.
No surprises.

Fixed scope. Fixed timeline. You know what you're getting before we start.

01
Week 1

Audit

Deep dive into your AI, data and compute stack, and for compute projects, the power behind it. We map every model, pipeline, cluster, and integration point. You get a prioritized list of what's broken, what's fragile, and what's costing you money.

02
Week 2

Blueprint

Architecture decisions documented as code — not slides. A technical blueprint your team can execute on, with clear sequencing and tradeoff analysis for every recommendation.

03
Weeks 3–6

Ship

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

AWSGCPAzureNVIDIASlurmKubernetesDockerMLflowWeights & BiasesLangChainLlamaIndexPineconeWeaviatePostgreSQLTerraformOpenTelemetry

Start here

Two fixed-fee ways to start.

Both end with a plan your team can execute, not a slide deck.

Production AI

$3,000 production audit.

A structured assessment of your AI and data stack with prioritized, actionable recommendations. Not a slide deck — a technical blueprint you can execute on.

  • One week, start to finish
  • No retainer, no commitment
  • Fee applies toward first engagement
Book your audit

HPC & Power

Compute & Power Plan.

Before you buy GPUs or sign for capacity: what your workloads need, what it takes to power and cool them, and what it costs to build, colocate or rent.

  • Two weeks, fixed fee
  • Sizing, power, cooling and cost model
  • Build, colocate and rent compared
Plan your compute

Who we are

Founded in Toronto.
Engineered for the real world.

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 on everything AI runs on: the compute, the power behind it, and the systems that keep models working in production.

FAQ

Common questions.

What size teams do you work with?

Startups to mid-market. We've helped 5-person ML teams and 50-engineer data orgs alike.

Should we buy GPUs or rent them?

It depends on utilization, workload mix, and how quickly you can get power. Working that out, with a cost model, is the core of the Compute & Power Plan.

Do you design electrical systems?

We plan the power side: how much your compute needs, what it takes to cool, and what it costs and how long it takes to get. Stamped electrical design and permits come from licensed engineers, and we work alongside yours.

Do you build models?

For utilities and energy companies, yes: forecasting and risk models, built for production from the start. Otherwise we focus on the engineering that gets the models you've already built into production.

What if we just need an audit?

That's our most popular starting point. $3,000, one week, no strings attached.

Can you work with our existing infra?

Yes. We build on your cloud and your stack. No proprietary platforms or vendor lock-in.

What's your availability?

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

Let's talk
production.

Planning compute, powering it, or getting models into production? Fill out the form and we'll respond within 24 hours.

Toronto, Canada