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AI Products

AI SaaS DevelopmentAI Products With Users, Billing, Margin.

AI SaaS development for products that need AI at the core and a SaaS business model around it — multi-tenant, billing, usage metering, per-tenant evaluation, the admin console and the engineering rigour a SaaS business needs to last.

10+Years Experience
100+Projects Delivered
50+Expert Developers
20+Industries Served

Overview

AI SaaS is a SaaS product with AI at the core

AI SaaS is a SaaS product that uses AI as the primary feature. The model is one component. The other components — the multi-tenant architecture, the auth, the billing, the usage metering, the admin console, the per-tenant evaluation — are the same as any other SaaS product, with the AI twist on top.

We build AI SaaS products against the same engineering rigour as any other SaaS product, with the AI components (model, data, evaluation, guardrails, cost controls) designed as part of the architecture from sprint one. The output is a product that lasts, not a demo that breaks the day after launch.

This is the wrong engagement if the goal is a one-off AI use case, not a product. For a use case, the right answer is a custom AI solution, not an AI SaaS.

  • Built to Last — Multi-tenant, API-first, with the evaluation suite that scales with the product.
  • Cost-Defensible — Per-tenant cost, the token budgets and the metering that keep the margin honest.
  • Evaluated at Scale — An evaluation suite that runs per-tenant, with the regressions caught early.
  • GTM Ready — The docs, the SDK, the landing pages and the launch the AI product needs.

What we deliver

Everything included in our ai saas development

AI Product Strategy

Use case selection, the product brief, the architecture and the roadmap, before the first commit.

Multi-Tenant AI

Multi-tenant AI with the isolation, the per-tenant evaluation and the per-tenant cost controls.

AI API & SDK

A public API and an SDK so customers can build on the AI product.

AI Admin & Console

The admin console, the usage dashboard, the per-tenant cost and the eval view.

AI Pricing & Billing

Usage-based pricing, the metering, the billing integration and the dunning.

AI GTM & Launch

The go-to-market, the landing pages, the docs and the launch the AI product needs.

Our process

A proven process for successful delivery

  1. 01

    Discover

    We agree the use case, the product brief, the architecture and the roadmap.

  2. 02

    Plan & Design

    We design the multi-tenant architecture, the API, the admin and the evaluation suite.

  3. 03

    Develop

    We build in two-week sprints with a working slice every Friday.

  4. 04

    Deploy

    We ship to production with the billing, the metering and the observability live.

  5. 05

    Optimize & Grow

    We read the data, the cost and the evaluations, and ship the next iteration.

Technology

Built with a stack that stays maintainable

Models

  • OpenAI
  • Anthropic
  • Google Gemini
  • Open source

Backend

  • Python
  • Node.js
  • Laravel

Database & Search

  • PostgreSQL
  • Pinecone
  • Weaviate
  • Elasticsearch

Billing & API

  • Stripe
  • Razorpay
  • Kong
  • Tyk

What you can expect

To First Production Release
12-20 wksTo First Production Release
Target Uptime
99.9%Target Uptime
Cost & Eval
Per-TenantCost & Eval
Architecture
Multi-TenantArchitecture

FAQs

Questions we get asked

Something not covered here? Ask us directly.

A custom AI solution solves one business problem for one customer. AI SaaS is a product with many customers, billing, a roadmap and a go-to-market. The engineering rigour is the same as a SaaS product, with the AI components on top. The investment is worth it when the use case is reusable across many customers.

It depends on the value, the cost and the competitor landscape. Usage-based pricing (per token, per request, per outcome) is a common default. Seat-based pricing works for products where the AI is a feature of a workflow. Outcome-based pricing is the most ambitious, and the hardest to operate. We will say so on the call.

Per-tenant cost, the token budgets, the caching, the batching, the model routing. The cost is a non-functional requirement, not an afterthought. We design against the cost from the first sprint, and the dashboards show the per-tenant cost against the budget.

The evaluation suite runs per-tenant, with a baseline test set that the product ships with and the per-tenant evals that the customer can add. The regressions are caught early, and the eval results are surfaced in the admin console. The product gets smarter with each tenant, without leaking data across tenants.

Ready to start your ai saas development project?Let’s scope it together.

Tell us the outcome you need. We’ll come back with an approach, a timeline and a written estimate.