Senior engineers from Thoughtworks. Across ZenMinds and our prior work we've scaled GCCs to 550+ people and cut AI platform costs by 85%. From stuck projects to production in 8 weeks.
The same four conversations, every quarter. Here's how we end them.
Great demo, no production path.
We architect for production from sprint one — CI/CD, observability, and rollback built in from Day 0.
Unpredictable token bills.
Semantic caching, prompt optimization, and smart model routing. We push 80% of requests to cheaper alternatives.
Deadlines pushed out forever.
Battle-tested agile with weekly demos and 2-week sprints. Ship on time, every time.
"Is this data safe?"
Data lineage, model versioning, and decision logging — SOC2 aligned. Governance from Day 1.
The same engineering bar across every engagement.
Production-grade AI systems — RAG pipelines, conversational agents, ML recommendations, and vector search. We optimize for cost, latency, and reliability from day one.
End-to-end Global Capability Center buildout — from first hire to fully operational engineering org. Talent strategy, hiring pipelines, onboarding, engineering culture.
From concept to production with velocity. Modern tech stacks, agile delivery, and product thinking. We ship MVPs in 4 weeks and scale to enterprise-grade.
Migrate legacy systems to cloud-native architectures without disrupting operations. Microservices, DDD, and automation that unlocks agility.
One enterprise AI engagement moved from rising model spend and fragile operations to a measurable, production-ready operating model.
The team redesigned model routing, semantic caching, evaluation and production telemetry around explicit cost and reliability targets.
Lower platform operating cost
Production delivery pathway
Routing, caching, evals and telemetry
Rising spend and fragile operations
Measured cost, reliability and release control
“Their technical depth and unwavering commitment to delivery excellence were crucial in our engagement.”
Selected engagement outcome. Scope, baseline and operating environment influence results.
Our AI-native delivery system. Senior engineers in the loop on every line.
Reviewable specs before code. CFRs are spec fields.
Decomposed, owned, dependency-aware.
Senior + agent on every keystroke.
Multi-layer review at PR time.
Code, test, log, security agents weekly.
Your context, codified. Project rules, coding standards, and review checklists travel with every build — so quality holds whether it's day one or release fifty.
Let’s talk through what’s in your way.
