Latest from the Team
Building a Healthcare AI MVP in 6 Weeks: Architecture, Lessons and What We Got Wrong
Lessons from scoping, building and shipping a clinical AI product from zero to production.
LLM Agents in Production: What Actually Breaks and How We Fixed It
What actually breaks when you run AI agents in enterprise workflows — and how we fixed it.
Edge AI on Industrial Hardware: Real Latency, Power and Accuracy Numbers
Real performance numbers from deploying edge AI on constrained industrial hardware.
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RAG vs Fine-Tuning: A Decision Framework for AI Product Teams
When to retrieve, when to train and when to do both — a practical guide from building LLM products in production.
Multi-Tenant SaaS Architecture for AI Products: What We Learned the Hard Way
Tenant isolation, shared AI inference costs and data security — the architectural decisions that matter most.
Deploying AI in Veterinary Clinics: A Product Engineering Case Study
From prototype to production across 10 clinics — the workflow integrations, staff adoption and model accuracy challenges.
PoC to Production in 6 Weeks: Our Sprint-by-Sprint Delivery Framework
The exact process, checkpoints and go/no-go criteria we use to take AI products from idea to deployed SaaS.
Why Generic AI Underperforms in Indian Retail — and How We Fixed It
Domain-specific models vs general-purpose AI — the performance gap we measured and the product decision it drove.
Federated Learning in Production: Training AI Without Centralising Industrial Data
Cross-facility model improvement without moving sensitive operational data — architecture and results from a real deployment.