Before you bet a budget on AI,
find out what it really takes.
The Discovery Sprint answers all four for your business — before you commit a rupee to building.
The first call is free · 45 minutes · no obligation
before you
commit
Enterprise AI rarely fails on the model. It fails before the build even starts.
It worked in the demo. Then it quietly stalled.
The proof-of-concept impressed the room and reached no one. The gap between a demo and a deployed system is where most enterprise AI dies — not on the model, on everything around it.
You tried a vendor once. It didn't land.
Infra, consultants, and licenses billed for months while not a single end user touched the thing. You're not against AI — you're against paying to learn the same lesson twice.
You can't price what no one has scoped.
Every vendor quotes a number before they understand your operation or your data. You're left unable to tell a real plan from a hopeful guess.
We don't quote blind. The Sprint is how we find out.
What an AI project costs, how long it takes, and how much of your operation it touches all depend on your problem — so a fixed number upfront would be a guess, not an answer.
Find the problem worth solving
We sit with your team and separate the problem that's actually costing you from the one you walked in naming.
Test it against your real data
We pressure-test what's buildable using the data you actually have — not a clean sample, the real thing.
Return a decision, not a pitch
You get what it takes, what it costs, what it touches, and an honest read on whether it's worth doing at all.
- A problem worth solving, defined in writing
- A real cost and timeline — not a placeholder range
- An honest read on whether your data is ready
- A clear go or no-go, including "don't build this"
Your team can adopt software. AI has to be governed.
- Ship to spec
- Behaves the same every time
- Right or wrong is obvious
- One skill: engineering
- Decide how far to trust it
- It drifts — judgment shifts
- "Wrong" carries business risk
- Engineering + business stakes, one head
We learned this building AI into our own company first — then watched it run hiring, sales and operations at the output of a company many times our size.
We don't pitch AI we haven't shipped. We run it on ourselves first.
InterviewGod
AI hiring at scale — deployed, billing, and run on our own 300-person operation every day. The system we sell is the system we operate.
Vikaas
B2B demand generation — live and growing, the engine we point at our own pipeline first.
vikaas.ai →Vidya
AI personalized learning — in build, v3. Not live yet, and we won't pretend otherwise.
vidya.online →Axon
Reality-check intelligence for founder-led companies — pre-launch, the newest system we run on ourselves.
axonhq.ai →Built into real operations across manufacturing, energy, retail and biotech.
$2M
Kiln shade-matching cut from 7–8 firing iterations to 2–3 — fewer re-fires, far less waste. Roughly $2M saved a year on their own production line.
Catching what humans miss, live
AI anomaly detection running across a production surveillance deployment — monitored and in use, not piloted.
Systems that hold at national scale
Engineering for one of India's largest enterprises — the kind of load and reliability bar most pilots never survive.
Trusted by regulated, high-stakes industries
Work shipped for US biotech and clinical-stage pharma, where being wrong isn't an option.
Trusted across India, the Gulf and the US
Sometimes the honest answer is "don't build this."
A Sprint can end with us recommending you stop — before you've spent a build budget. That's not a failed engagement. It's the answer most vendors won't give you, because they're paid to keep building.
We'll also be clear about what only you can do: get the data ready, and let your team work differently. AI built any other way is the kind that stalls.
Find out what your AI problem actually takes to solve.
A 45-minute call. No obligation. You'll leave knowing whether a Sprint makes sense for you.
- 45 minutes with our engineers, not a sales rep
- A strict NDA before you share anything
- A first read on feasibility for your problem
- A no-obligation view of cost and next steps