What an AI automation system actually costs.
One flagship service, ₹35,000 - ₹90,000. Published ranges, not "contact us for a quote". Where a project lands inside its range depends on which application and how much of the workflow it covers - you get a single fixed number after the discovery call, before any work starts.
Side by side.
Leads are qualified and followed up on by hand, and some go cold before anyone gets to them
Drives cost: Number of trigger events, CRM complexity, enrichment sources
Invoices, forms, or contracts are still re-typed into a system by hand
Drives cost: Document variety, validation rules, downstream systems
A request needs reasoning across multiple internal systems before anything can happen
Drives cost: Number of tools connected, reasoning complexity, approval steps
Institutional knowledge is scattered and your team keeps answering the same questions
Drives cost: Knowledge sources, access control, agent actions
Every project is quoted as a single fixed price once scoped. The ranges above reflect how much project size varies between clients - not variable billing within a project. Many workflows span more than one application; the proposal reflects the actual scope, not a category.
Why one project costs more than another.
Price tracks what it takes to ship a correct version of the system, not how many hours it takes to write. These are the factors that move a project up or down inside its range.
Scope depth
How many distinct workflows or modules the system has to cover. One well-defined process costs less than five interconnected ones.
Integrations
Every external system - your CRM, ERP, WhatsApp, payment gateway - adds authentication, error handling, and a failure mode that has to be tested.
User roles and access control
A single-user tool is straightforward. Multiple roles with different permissions multiply the testing surface, and in RAG systems they change what the AI is allowed to answer.
AI complexity
Retrieving an answer is simpler than reasoning over it, which is simpler than an agent taking actions on your behalf. Each step up adds build and verification work.
Production hardening
Monitoring, audit trails, exception queues, and retraining pipelines are what separate a system that runs unattended from a demo. They are priced in, not added later.
Data readiness
Mostly relevant to ML. Clean, well-labelled historical data shortens the work considerably. Messy or thin data means preparation before any modelling starts.
What the price always covers.
- A fixed price agreed before any work begins
- Full source code ownership on handover
- Deployment documentation and a recorded walkthrough
- 30 days of post-launch support, included
- A live staging environment throughout the build
- No monthly fees and no vendor lock-in
No hourly billing. No monthly retainer. Anything outside the agreed scope is quoted separately and starts only once you approve it.
Bring the problem rather than the solution. If a simpler tool or a better process would solve it faster than anything I build, I will tell you that on the call.
Book a Discovery CallKnow roughly what you need? Let's scope it.
Book a free 30-60 min discovery call. You'll get a fixed-price proposal within 5 business days.