AI software that works in the real world.
We build AI-powered products and features that ship to real users and hold up under real use. Not prototypes. Not demos. Production software with intelligence at its core.
DigiRashtra AI
intelligence engine
What we build
Six ways AI shows up in your product.
AI-powered web & mobile apps
Products where intelligence is the feature, not a bolt-on. Recommendation engines, smart search, predictive dashboards, content generation.
LLM integration & fine-tuning
GPT, Claude, Gemini, Mistral, or an open model fine-tuned on your data. We handle the plumbing so your team just uses the output.
AI chatbots & assistants
Customer bots that actually resolve queries, internal assistants that know your docs, and voice interfaces built for real use.
Computer vision & image AI
Object detection, classification, visual try-on, quality inspection. If it involves a camera and a decision, we can build it.
Data pipelines & embeddings
RAG setups, vector search, structured ETL, and real-time inference. The data layer that makes AI work in production.
AI into existing products
Already have a product? We add the AI layer without breaking what works. Smart autofill, anomaly detection, summarisation.
How it works
From idea to production AI.
Discovery & scoping
We learn the problem deeply before recommending a model. Most AI projects fail because the wrong tool was picked.
Prototype in 2 weeks
A working proof of concept with real data, not a slide deck. Test it, and decide if it solves the thing you needed solved.
Build for production
Once validated, we harden it: error handling, rate limits, caching, cost controls, monitoring, and deployment.
Measure & iterate
AI improves with use. We set up evals, track accuracy, and iterate on prompts, models, and architecture.
Fit check
Is this the right fit? An honest check.
A good fit if
- A task your team repeats every day eats hours, like triaging support tickets or pulling data out of documents.
- You want AI inside a product you already run, without rebuilding it.
- You have documents, tickets, or records the AI should answer from.
- You would rather see a working prototype on your own data in 2 weeks than sign off a big budget on a promise.
Probably not a fit if
- You want an AI strategy deck and no software. We only take on work we build ourselves.
- Every answer is high stakes and there is no room for a person to review it, like a final medical or legal decision.
- You need a chatbot live by Friday with no time spent on your data.
Cost and timeline
What shapes the cost and the timeline.
AI work is priced like any other software, with one extra variable: how messy the data is. Adding AI to an existing product usually takes 4 to 10 weeks. These four things move the number most.
How much it costs to add AI to your software01
Your data
Clean, well-organised documents make a RAG build quick. Scanned PDFs, duplicates and outdated files add a cleanup phase first.
02
How accurate it has to be
A draft that a person checks is cheaper to build than an answer that goes straight to a customer. Higher stakes mean more testing and review steps.
03
Where it runs
Calling a hosted model like GPT or Claude is the fastest route. Keeping everything on your own servers for privacy takes more setup.
04
Running costs
Each AI answer costs a fraction of a cent to a few cents in model fees. We estimate this before you commit and add caching so the monthly bill stays predictable.
Further reading
Worth reading before you start.
Get a fixed quote for your AI project
Answer a few quick questions. You'll get an honest read on scope, and a fixed price if we're a good fit. The scoping call is free.
Ready to ship something intelligent?
Tell us the problem. We will tell you what is actually possible.
Start the conversation