Software development: AI SaaS & business software

AI SaaS development means building software as a multi-tenant online service in which AI features such as LLM workflows, voice agents or knowledge AI are a core part of the product – not bolted on later. It covers roles and permissions, billing by subscription or usage, ERP and CRM integration, audit logs and automated tests and deployments. Whether SaaS product or internal software, the goal is a system that runs reliably and grows with the business. The architecture decides whether new customers and features can be added without a rebuild.

This matters for mid-sized companies and corporations now because off-the-shelf software rarely turns AI into a competitive advantage – that advantage comes from your own processes and products. Such projects often fail in three places: agencies deliver pretty prototypes without a scalable architecture, internal IT is fully booked with day-to-day work, and nobody on the project has ever run AI in production. The result is projects that take twelve months and then have to be rebuilt – often with lock-in, because code and accounts sit with the vendor.

I have built more than 15 SaaS products of my own; seven are live – including aniCRM, anicall.io and anirag.io. Your product is built on the same architecture: a multi-tenant monorepo, worker queues, Stripe billing and Playwright tests for complete demo paths. You click through a prototype in week two, followed by two-week sprints with a working build. The system is typically production-ready after 8 to 12 weeks – and the code and accounts belong to you. I modernise existing software too, from .NET monoliths to microservices.