Topic pillar · 3 posts

Building B2B SaaS in India — Engineering Lessons

Frank engineering lessons from shipping VIZIQO Assist and VIZIQO Campaign: stack selection, cloud infrastructure at each scale, RAG in production, and India-specific compliance overhead.

Building B2B SaaS in India means making engineering choices that look different from the typical Silicon Valley playbook. The market accepts simpler infrastructure (a single t3.xlarge can take you to ~200 concurrent users for under ₹15,000/month), but the compliance overhead is heavier — DLT registration alone takes 2–4 weeks, WhatsApp Business API approval has its own timeline, and Razorpay's edge cases around GST and RBI auto-debit will cost you two weeks if you don't plan ahead.

If your product is AI-powered, the production realities of RAG add another dimension: chunking strategy decides retrieval quality, embedding costs grow 10x faster than user count without caching, and hitting sub-2-second voice latency requires aggressive optimization (pre-warming, payload filtering, re-ranking, streaming).

This pillar collects our engineering writing — what we learned shipping two production SaaS products in 12 months, the infrastructure decisions at each growth stage, and the LangChain + Qdrant gotchas that no tutorial mentions.

Key takeaways
  • Spend one week on stack selection, not more — pick technologies your team knows well.
  • Stage your infrastructure: single EC2 → managed RDS + ALB → ECS Fargate → EKS. Don't skip stages.
  • Allocate ~15% of the first six months to compliance — DLT, WhatsApp Business API, data localization, GST.
  • In RAG, chunking strategy matters more than embedding model — spend 40% of dev time on chunking/preprocessing.
  • Never use a technology you can't debug at 3 AM when production is down.