Multi-tenant foundations
Isolation, roles and per-tenant configuration built in from the first sprint.
AI SaaS Products
Launch your AI SaaS
faster than ever.
From architecture to launch — we build multi-tenant AI SaaS platforms with everything founders need: AI pipelines, billing, dashboards, and production-grade APIs.
What we deliver
- Multi-tenant architecture with role-based access
- AI pipelines — LLM, embeddings, vector search
- Billing integration (Stripe, Razorpay)
- Admin and customer-facing dashboards
- REST & GraphQL APIs for third-party integrations
- Scalable cloud infrastructure on AWS / GCP / Vercel
What we build into AI SaaS products
AI pipelines
Retrieval, generation and evaluation wired as a system you can reason about.
Usage-based billing
Metering that reflects inference cost, so pricing survives scale.
Admin and customer dashboards
The surfaces your team needs to operate and your customers need to trust.
FAQ
Frequently asked questions
- How long does it take to build an AI SaaS MVP?
- A well-scoped first version covering one workflow end to end is typically weeks rather than quarters. Multi-tenancy, billing and permissions are what stretch a schedule, so we sequence them deliberately rather than bolting them on later.
- How should we price a product with AI inference costs?
- Design pricing alongside the architecture. Inference scales linearly with usage and never amortises, so per-seat pricing on a heavy AI workflow can invert your margins as you grow. Model cost per session before you publish a price.
- Can you work with our existing codebase and team?
- Yes. We regularly join an in-house team to build the AI layer while they continue on core product, with the interfaces between the two agreed up front.
- Which cloud do you build on?
- Usually AWS, with Node.js and TypeScript. We design so the model provider is a swappable component rather than a dependency welded into the product.
- Do you help after launch?
- Yes — the useful phase is usually after real usage arrives, when evaluation data tells you what to fix. We support ongoing iteration rather than handing over and disappearing.