Applied AI / R&D Delivery
We ship applied AI systems where real-world constraints matter.
Architect-led teams delivering production systems in high-risk domains, from trading platforms to industrial computer vision.
Key delivery principles
Production-first AI
Latency budgets, observability, drift monitoring from day one.
Risk-aware delivery
Compliance and reliability built into architecture, not bolted on.
End-to-end ownership
Clear milestones, fast feedback loops, accountable leads.
What we actually do
Applied AI delivery: architecture, ML pipelines, system integration, and production ownership with measurable outcomes.
Where it breaks for others
Data drift, latency, compliance, and ambiguous ownership. We build with these constraints as first-class requirements.
Unclear system boundaries
Models work in notebooks, then fail in production workflows.
Hidden latency budgets
Real-time constraints surface late and break the product.
Ownership gaps
Nobody owns monitoring, incident response, or ongoing tuning.
Compliance surprises
Security, audit, and data policies arrive after the build.
How we work
Discovery → Build → Support. Clear milestones, senior-only engineers, and end-to-end accountability.
Phase 1
Discovery & risk map
Architecture, data readiness, constraints that shape delivery.
Phase 2
Build & integrate
Production pipelines, systems integration, staged rollouts.
Phase 3
Support & improve
Monitoring, model governance, continuous improvements.
Trusted by teams under NDA
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Ready to build?
Tell us your constraints and we will design the system around them.