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AI SaaS Development

AI SaaS Development: From Idea to Launched Product

We help founders and product teams turn an AI product idea into a working, secure, subscription-ready SaaS — covering product scoping, AI features, the application itself and the infrastructure to run it.

Discuss your project

An AI demo is not a product

It is easy to build a prototype that calls a language model. Turning it into a product people pay for is harder: you need user accounts and teams, data isolation between customers, billing, usage limits, reliable AI output, cost control and an interface people want to use every day.

Many teams also face a tight budget and timeline, and need to validate the idea with real users before investing in everything at once.

A product team for your AI SaaS

We work with you from the first scoping session to launch and beyond. We help define a focused first version, build it on a scalable foundation and add AI features in a way that is measurable, cost-aware and easy to improve.

What we deliver

  • Product scoping and an MVP feature plan
  • Web application (Next.js / React) and APIs (Node.js, NestJS or Python)
  • Multi-tenant architecture, authentication, roles and teams
  • Subscription billing and usage-based limits
  • LLM features: chat, RAG search, generation, extraction and agents
  • Cloud deployment, monitoring and AI cost tracking

How it works

  1. Step 1

    Scope the MVP

    We identify the one problem your product must solve brilliantly and cut everything else from version one.

  2. Step 2

    Design the core flows

    Wireframes and UI for onboarding, the main workflow and the AI interaction.

  3. Step 3

    Build on a solid foundation

    Accounts, tenancy, billing and infrastructure are built properly from the start so you don't have to rebuild later.

  4. Step 4

    Ship, measure, iterate

    We launch to early users, track usage and AI quality, and plan the next releases from real feedback.

Business benefits

Faster route to real users

A focused MVP gets your product in front of customers sooner, so decisions are based on evidence.

Architecture that scales

Tenancy, security and billing are designed for growth, not bolted on later.

Controlled AI costs

Caching, model selection and usage limits keep inference costs predictable as you grow.

One team, full stack

Product, AI, frontend, backend, mobile and DevOps skills in a single team reduce hand-offs.

Use cases

Vertical AI tools

AI assistants for a specific industry or profession, built around its documents and workflows.

AI customer engagement platforms

Multi-channel AI support and lead capture products — the category of our own SmartAgent platform.

Document intelligence products

Upload, search, summarise and extract data from large collections of documents.

Adding AI to an existing SaaS

New AI features inside a product you already run, without disrupting current customers.

Our process

  1. Discovery

    Goals, users, competitors and constraints; agreed MVP scope and estimate.

  2. Design

    User flows, UI design and technical architecture.

  3. Agile build

    Short iterations with working software you can review every week.

  4. Launch & growth

    Deployment, monitoring, analytics and an ongoing roadmap.

Read more about how we work.

Technologies we use

  • Next.js
  • React
  • Node.js
  • NestJS
  • Python
  • PostgreSQL / MySQL / MongoDB
  • OpenAI API
  • LangChain
  • Stripe
  • Docker

Frequently asked questions

Have you built an AI SaaS product yourselves?

Yes. We built and run SmartAgent, a multi-channel AI customer support platform with subscription plans. That experience — tenancy, billing, AI quality, cost control — goes into the products we build for clients.

How much does it cost to build an AI SaaS MVP?

It depends mainly on the number of user roles, integrations and AI features. After a discovery call we provide a scoped estimate for a focused first version, with optional later phases priced separately.

Who owns the code and IP?

You do. On completion and payment, the source code and intellectual property for your product are transferred to you under the contract.

Which AI models do you use?

We choose per feature, balancing quality, speed, cost and data requirements — commercial APIs such as OpenAI, or open-source models where self-hosting is preferable.

Can you support the product after launch?

Yes. We offer ongoing development, maintenance and monitoring so the product keeps improving after release.

Related services

Custom AI Solutions

Custom AI software development and AI integration services: language models, search, prediction and computer vision added to your existing systems and data.

Web Development

Custom web application development with React, Next.js and Node.js: fast, SEO-friendly websites, customer portals, dashboards and SaaS platforms.

AI Agents Development

Custom AI agents that answer customers, qualify leads, book meetings and complete multi-step tasks using your own data and tools — on web, WhatsApp and email.

Planning an AI SaaS product?

Share your idea and target users. We'll help you define a realistic first version and how to get it to market.

Contact us