DEPLOY TO PRODUCTION
stop demoing to executives
Everyone’s got a PoC. Nobody’s got production AI. We bridge the gap with
governance, guardrails, and infrastructure that scales.
Sound familiar?
Every enterprise says it. Few fix it. Here's what we hear on day one.
The pilot worked. The rollout didn't.
Lab conditions aren’t production conditions. Different data, different scale, different failure modes. The demo lied.
Real Enterprise Work
Fortune 500 infrastructure. AI at scale. Data platforms that matter. Not toy projects. Real problems.
Governance is an afterthought.
No model registry. No bias testing. No audit trail. You’re one regulator question away from shutting it all down.
Agents are the future. Your stack can't support them.
Autonomous agents need real-time data, secure tool access, and monitoring. Your current infrastructure wasn’t designed for any of that.
0
Delivery Pods
Cross-functional teams
0
Countrie
Distributed globally
0
%
Retention
People stay, teams grow
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%
Remote-Friendly
Work from anywhere
Your journey. Four stages.
Every AI engagement follows the same path. Discover → Prove → Build → Govern. The Govern stage is our structural differentiator — no competitor offers a dedicated AI Assurance Program.
Discover · 2-4 weeks
Use-case prioritization, data readiness audit, and ROI modelling. The honest picture of what’s possible — and what isn’t — before the investment.
Prove · 6-10 weeks
POC with production guardrails, MINT framework, and agent prototyping. Your environment, your data, your compliance requirements. Not a vendor demo.
Build · 3-9 months
Agent orchestration, LLM pipelines, RAG at scale, and prompt ops. Production-grade AI that survives contact with real users and real data.
Govern · Ongoing
Model monitoring, compliance automation, AI governance, and drift detection. The piece every competitor skips — and the reason deployments fail.
Named products. Not generic proposals.
- AI Readiness Assessment report
- Use case prioritisation matrix
- Production AI platform
- Agent orchestration framework
- MLOps + monitoring pipeline
- AI Assurance governance pack
Performance. Not promises.
Real numbers. Real client. Measured after go-live.
Banking
AI Strategy
Major retail bank. AI ambitions. Zero production models.
Twelve months of experimentation, nothing in production. OnStak assessed the AI landscape, identified four high-value use cases, built the governance framework, and deployed the first two models into production within ninety days. The remaining two followed in the next quarter.
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Infrastructure Modernization
Fix the foundations. Cloud, hybrid, AI-ready infrastructure.
Application Modernization
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Data
One platform. Governed. Trusted. Ready for AI.
Assurance & Operations
Managed services that keep it running after go-live.