AI SaaS development for founders shipping AI-native products.

AI SaaS development is building software-as-a-service products where AI is a core differentiator — multi-tenant architecture, auth, billing, admin, audit, observability — combined with AI features (agents, RAG, LLM copilots) instrumented inside the stack rather than imported as a third-party black box. The hard part is the SaaS surface and tenant isolation; the AI piece is usually the easier half once retrieval and evals are in place.

Yes. Our reference deployment, Mockinto, was built from zero to working v1 in six weeks, then to $200k ARR within 90 days post-launch. We handle product architecture, front-end (Next.js or Flutter), back-end (Node or Python), database (Postgres + pgvector), auth (Auth0 or Clerk), billing (Stripe), observability (Datadog/Sentry/Langfuse), and the AI logic — one senior team, one codebase, one accountable engagement.

Yes — this is the more common engagement. We embed agents, RAG copilots, semantic search, document intelligence, or LLM workflows inside your existing SaaS codebase. Architecture audit first, then a fixed-price one-pager for the AI feature scope. Usually 4-8 weeks per major AI feature depending on integration depth. No rip-and-replace of your existing stack.

Three patterns. Tenant-scoped retrieval — each tenant's RAG runs against an isolated namespace in the vector store. Per-tenant prompts and templates — admin can configure tone, refusal thresholds, and tool whitelists. Per-tenant fine-tuning — for the rare case a tenant needs a customised model, we run LoRA fine-tunes against their data with versioned weights. Usage metering ties into billing.

Three common patterns we implement. Per-seat with usage caps — predictable revenue, sets soft limits. Usage-based (per agent run, per document processed, per token) — aligns cost with value. Hybrid — base subscription + usage credits with overage. We wire Stripe metering to the AI logic so revenue ops can audit per-tenant cost vs revenue.

Most AI SaaS v1 builds at Aiinfox land between $60,000 and $180,000 fixed-price for a focused, single-segment product. Mid-market AI SaaS with multi-tenant, SSO, and advanced billing typically reach $150,000 to $300,000 over 4-6 months. Pilots and v0 MVPs ship in 3-4 weeks for $20,000 to $40,000 — useful for VC pitch demos.

Yes. Every engagement ends with a code handover, runbooks, eval harness, and on-call documentation. Your repo, your AWS/GCP/Azure account, your operating team. We do not lock customers into a managed-by-Aiinfox model. Optional retainer for ongoing feature work and AI tuning — but always optional, never required for handover.

Yes. Mutual NDAs are signed before any technical detail is shared. For pre-seed founders worried about idea theft, we are happy to walk through our prior shipped products under NDA — execution and engineering depth matter far more than the product idea, and the shipped portfolio is the proof.