Building companies where AI turns small teams into elite operations.

We find domains where delivery is bottlenecked by expensive, skilled labor. Then we build companies that deliver the same outcome - at software margins - powered by AI-amplified teams, automation, or both. The quality stays human-controlled. The economics don't.

LiveOur Flagship

CodeWithSense

India's embedded AI engineering team for growth-stage companies. Senior engineers inside your team, shipping production code.

$1M+ ARR·100% client retention
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Why we build this way

Most “AI companies” are building tools. We are interested in the other thing.

Tools that sit alongside the existing operation - an assistant here, a dashboard there. The operation itself stays expensive. The headcount stays. The margin does not change.

We are interested in the other thing: building companies where AI changes the fundamental economics of service delivery. Pick a domain where a service is delivered by skilled people doing expensive, high-stakes work. Build AI-amplified teams - or in some cases, software that handles delivery directly - and you can produce the same outcome at a fraction of the cost. With quality that conventional headcount cannot match, because the people who remain are focused, leveraged, and accountable for what ships.

CodeWithSense is the first proof point. Engineering talent is expensive, scarce, and slow to hire. We built a model that delivers senior AI engineering work at 50–70% below US rates, with immediate availability and founder-level oversight on every engagement. The client gets the output of a great engineering team. We deliver it with a smaller, AI-leveraged team - and every engagement has human accountability for what ships.

That is the model we keep applying. Different domains, same thesis: find where expensive skill is the bottleneck. Use AI to change the economics. Keep humans in control of quality.

$1M+

ARR

20+

Years in engineering

100%

Client retention since founding

5+ yrs

Longest client tenure

What We Build

The engineering capabilities that power every company we build.

Agentic AI & LLM Systems

Multi-agent orchestration, RAG pipelines, tool-use architectures. Engineers who have shipped these to production at scale - not engineers who've read about them.

Embedded in your team. Accountable for production outcomes.

ML Engineering

Recommendation engines, feature engineering pipelines, A/B testing. Built alongside your data team, deployed into your stack.

Measurable outcomes - not model accuracy scores, but business metrics.

Full-Stack Engineering

Python, TypeScript, React, Ruby/Rails. APIs to UIs. From data model to deployment. No handoffs between specialists.

Senior engineers who own the full problem.

Enterprise Integrations

POS systems, payment processors, CRMs, ATS platforms, data pipelines. The complex glue work that most vendors avoid.

Deep experience across Revel, Square, Toast, Brink, Aloha, and more.

What we are building

CodeWithSense is our primary client-facing brand. Each company we build runs independently with its own market focus - Nimara provides the thesis, the infrastructure, and the founder-level oversight.

Live · AI Engineering

CodeWithSense

A software and AI development studio. Senior engineers who join your team as full members - on your Slack, in your codebase, accountable for what ships. The output of a full-time senior hire without the 3-month recruiting cycle or the retention risk.

$1M+ ARR · Clients in US, UK, India

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In Development

Coming 2026

The next domain where AI changes the economics of delivery.

Recent AI Implementations - CodeWithSense

LunchboxRestaurant Tech
  • Agentic AI chat for restaurant operators
  • ML recommendation engine - measurable order-value uplift
  • Voice AI order capture
  • POS integrations: Revel, Square, Toast, Brink, Aloha
WanderlyTravel Nursing
  • CoRecruit - conversational AI candidate screening
  • Reduced screening time per candidate
  • Integrated with existing ATS workflow

Operating principles

01

Founder in the room

Nikhil personally vets every engineer and stays involved in every engagement. Not as an account manager - as an engineer. He reviews code, asks the hard architecture questions, and can debug a production incident on a Monday morning. You're working with a team the founder trusts because his own reputation, and his own clients, depend on the same work. That's not a tagline. It's a constraint that keeps the bar high.

02

We write code, not reports

Every engagement ends with working software in production. We're not consultants. We're engineers who ship.

03

Embedded, not outsourced

Our engineers join your team. Same Slack, same standups, same pull request queue. You get the output of a senior hire, not the overhead of a vendor.

04

AI in the work, not just the pitch

We deploy AI into our own operations before we recommend it to clients - every pipeline, every agent, stress-tested in production. Our clients get the same stack, because we've already lived with it.

“Routine work runs autonomously. Strategic decisions stay human.”

Nikhil Gupta

Founder · Based in Jaipur, India

I have spent 20+ years at the delivery end of software engineering - building systems that had to actually work, for clients with real deadlines and real consequences for failure.

I did not start with a thesis. I started with a pattern: the most valuable thing you could do for a company was write the code, not the strategy deck. Then I noticed that the domains where that mattered most were the ones where people were doing expensive, repetitive, knowledge-based work. And AI was getting very good at exactly that.

I am still writing code and reviewing PRs. I stay close to the work because that is how I know what is real. The service-as-software thesis is built from what I have shipped, not what I have read.

Restaurant tech

Agentic AI, ML recommendations, Voice AI, POS integrations: Revel, Square, Toast, Brink, Aloha

Travel & Staffing

Conversational AI recruiting, ATS integration, candidate qualification

Fintech & AI

Algorithmic trading systems, AI in financial analytics, crypto infrastructure, cross-domain fintech architecture

AI Architecture

RAG pipelines, multi-agent orchestration, LLM tooling in production

Full-stack

Python, TypeScript, React, Ruby/Rails - end to end, no handoffs

What makes this different

Most staff aug firms are run by salespeople. I still write code and review PRs. That means I can evaluate a candidate's architecture, debug a production incident, and know immediately when something is wrong. That's why the bar here is high - and why clients stay.

Work with us

Hire the team. Or build with the studio.

We work in long-term relationships, not short-term contracts. Every engagement is built to compound - technically and commercially.