AI-first. Forward-deployed.
We are AI-first. Every one of us acts as a forward-deployed engineer: in your stack, from the intro call through deploy. The person on the call is the person who ships.
For companies that have to live with the system after the demo.
Paid 2-week sprintGo/No-Gothen 6–8 week pilot
Shortest path from your data to a system your team can run.
Business outcomes first. Every engagement starts with an architecture sprint — these are the jobs we take once the path is clear.
Cursor, Lovable, Replit, or Bolt will help you ship. They will not watch uptime, rotate keys, or stay on the repo after users show up.
Where vibe-coded apps stall
01
It will help you ship. It will not page you, rotate keys, or restore a backup.
02
Env files in git, open buckets, unauthed admin. Fine until payments sit on the same repo.
03
No evals, no uptime watch. The first person to notice a hole is usually a customer.
Real projects told as problem, engineering, and result. Not vanity logos.
~50% faster projected development timeline
Audic turns ad scripts into studio-quality voiceovers across major Indian languages. Marketers and agencies ship localized audio without booking a recording session.
Read case study
10k+ attempt events modelled
Edsage is a personal AI mentor for exam prep. Every question builds a profile, weaknesses show up early, and daily plans update from real performance instead of generic schedules.
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1B+ data points · ~90% match accuracy on product eval criteria
Doriot helps startups find aligned investors and run outreach with an AI copilot, so fundraising is targeted instead of spray-and-pray.
Read case studyMost failures are engineering and ownership problems, not model demos.
Where projects stall
The demo works in isolation. Production needs APIs, auth, data access, and real workflows.
Without evals, monitoring, and fallbacks, teams cannot trust the system with real users.
Knowledge is fragmented, access is unclear, and retrieval quality falls apart on real queries.
Models drift, costs rise, and nobody owns upgrades, incidents, or ongoing quality.
Why the lean studio
AI-first. Every person here is a forward-deployed engineer. No sales team making promises engineering can't keep. We ship in your stack and stay after launch.
Hyderabad HQ · Global Timezone
Who you actually talk toWe don't sell workshops. A paid two-week sprint produces architecture, risks, and a Go/No-Go. If it will not work, we say so before you fund the build.
AI-first builders in your repos. No account-manager layer. No architect who only presents. The person on the intro call is the person who ships.
One problem at a time, in your APIs, data, and access rules. Not a parallel delivery org. Not a bench learning your codebase from a ticket queue.
Production means integration, evals, monitoring, fallbacks, and someone who still answers after launch. Vendor-neutral on models. Opinionated on that bar.
Every engagement starts with a paid architecture sprint. Pilot, scale, and ops only follow a Go.
Use case, data, integrations, and constraints. We say if a sprint is the right next step.
Paid ~2 weeks. One problem, architecture, risks, and an implementation plan. Go/No-Go before anyone funds the pilot.
About 6 to 8 weeks: build, integrate, evaluate, deploy, and hit agreed acceptance metrics.
Add integrations, workflows, teams, or features once the first system is proven in production.
Run and improve the live system: reliability, cost, quality, and model updates.
Least-privilege access, encryption, auditability, deployment options aligned with your data requirements, evaluations, and human oversight. No unverifiable certification slogans.
Security approachTrust stack
Built into delivery, not bolted on
Start with a two-week architecture sprint. We reply within 1 business day. Or email hello@neurocell.in.
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