SaaS Product Development

A SaaS MVP typically takes ten to sixteen weeks to build after two to four weeks of validation and scoping. The fastest launches cut the first version to one workflow that a specific customer will pay for, then add the rest once real usage data arrives.

Our default SaaS stack is TypeScript end to end — Next.js or React on the front end, Node.js APIs and PostgreSQL — with Python where AI or data work is central, hosted on AWS, Google Cloud, Vercel or Supabase depending on scale and team. We pick well-supported, widely used tools so you can hire for them later, and document every choice.

Multi-tenant architecture means one application serves many customer organisations while keeping each one's data separate. Almost every SaaS product needs it; the real question is how strict the separation is — a shared database with tenant-level security for most products, or separate schemas or databases for customers with stricter requirements. Getting this right at the start avoids a painful migration later.

Indian SaaS companies commonly use Razorpay Subscriptions with UPI Autopay and card mandates for domestic customers, and Razorpay's international payments, Paddle as a merchant of record, or Stripe where their entity is eligible for overseas customers. The right setup depends on where your company is registered, where customers are and how much tax handling you want to outsource. Eligibility and RBI recurring-payment rules change, so we confirm current terms with each provider before wiring billing.

Compliance is something your company achieves through an audit or assessment, not something code alone provides, but we build with the practices those frameworks expect: access controls, encryption, audit logs, backups, retention rules, consent records and documented processes. That makes a SOC 2 audit, a GDPR review or India's Digital Personal Data Protection (DPDP) obligations far easier when customers start asking. We do not issue certifications; we prepare the product and the paperwork for your auditor.

Yes. We add AI where it saves users real time — answering questions over their own data, drafting, classification, summaries and agents that complete multi-step tasks — using Claude, GPT or Gemini models through their APIs. Each feature ships with usage limits, cost tracking, evaluation tests and tenant-level data separation, so AI does not become an uncontrolled bill or a data leak.

You own the code, the IP and every cloud and billing account from day one; the repository and infrastructure sit in your organisation. After launch most clients keep a monthly product-team retainer for releases, monitoring and scaling, while some move development in-house — the system is documented so that handover is straightforward.