Services
We find where AI fits in your product. Then we build it.
For B2B and enterprise teams who want working software instead of a strategy deck. Our team in Chandigarh scopes the opportunity, prototypes it in days, and ships the feature with you.
What we solve
Most teams arrive with a list of ideas and no place to start.
We cut through it quickly, name what’s worth building, and get something running before the next sprint ends.
01
Automate the work nobody enjoys
Manual data entry, repetitive reporting, copy-paste between tools. We start with the highest-return targets, not the most impressive demo.
02
Ship your first AI feature fast
Most vendors scope for months. We aim for something working in your hands within a week, then decide together whether it deserves a full build.
03
Turn your own data into product intelligence
Docs, tickets and years of history can power better features — once there’s a pipeline that makes them retrievable and safe to use.
04
Add AI without replacing your stack
We build inside the architecture you already run. No rip-and-replace, no second platform for your team to maintain.
05
Design features people actually use
A feature that demos well and confuses users in production is worse than none. We design around the real workflow first.
06
Stay current as the tooling shifts
Model and framework choices age in months. We pick what’s genuinely best for the job now, behind an abstraction you can change later.
How we work
Pick a starting point. We’ll handle the rest.
Not sure yet? Start with the workshop — its fee applies toward a sprint or MVP if you continue.
Entry point · One live session
Clarity workshop
Know what to build before you spend anything building it.
- A working session with your product and engineering leads
- Audit of your product and process for AI opportunity
- A prioritised list of three to five use cases, scored on effort and impact
- Model and tooling recommendations for your existing stack
- A summary doc with one clear next step
- The fee applies toward a sprint or MVP if you continue within 30 days
Most popular · One week
Sprint + proof of concept
A real prototype you can put in front of real users.
- Day one: discovery and use-case alignment
- Day two: architecture and model selection
- Hands-on build with the tooling that fits the problem
- A working proof of concept deployed in your environment
- Stakeholder demo plus a recorded walkthrough
- Technical write-up and a cost estimate for the full build
Full engagement · Four weeks and up, scoped after discovery
AI MVP
From first conversation to a live feature, end to end.
- Full product discovery and an AI roadmap
- UX design for AI-assisted workflows
- Production build against your chosen model provider
- Data pipeline, vector store, and risk guardrails
- Deployed, tested, and documented feature
- Post-launch support and an iteration plan
Tools we leverage
We use what’s best right now.
Every choice sits behind an abstraction, so swapping a model or provider later is a config change rather than a rebuild.
Frontier model APIs
Production reasoning and generation, chosen per task and cost profile.
Agentic coding tools
How we get a working prototype in days rather than months.
Fine-tuned open models
For domain requirements a commercial API can’t cover.
Vector search on Postgres
Semantic retrieval without adding a new database to your ops.
Streaming UI toolkits
Production-grade interfaces for token-by-token responses.
Workflow and agent frameworks
Multi-step pipelines with retries, tool use, and audit trails.
Our AI experience
Samples of AI work.
“The prototype they built in a week is what won us budget for the whole platform.”
Product lead, enterprise network strategy
FAQ
Everything worth knowing before a call.
The workshop. In one session we score your ideas on effort and impact against your actual stack, and you leave with a ranked shortlist rather than a longer list.
A proof of concept inside a week is the normal case. It runs in your environment on your data, so the demo is an honest test rather than a staged one.
Yes, and it happens. Sometimes the fix is a query, a form change or plain automation. We’d rather say that than bill you for a model you don’t need.
That’s the default. We fit into your architecture, conventions and review process, and leave documentation your engineers can carry forward.
Data handling is scoped before we build: what leaves your systems, what’s retained, what runs in your own environment, plus guardrails and an audit trail on anything the model can act on.
Each tier is a fixed, quoted fee agreed before work starts — the workshop is a flat rate, the sprint is fixed, and MVP scope is priced after discovery. No hourly surprises.
More services
Pairs well with.
AI product development
AI consultancy
Let’s build something worth shipping.
Tell us about your product. We’ll reply within a day with next steps.