AI Engineering Lab · Delhi, India

We Build AI
That Ships.

Production-ready AI systems and MVPs for startups — delivered in 2 to 4 weeks. No hype. No half-finished prototypes. Just working software in the hands of real users.

Start a Project See how we work
100+
Apps Shipped
7+
Years Experience
2–4
Weeks to Production
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Capabilities

The systems
we engineer.

We specialise in the parts of AI that most teams get wrong — the production layer. From architecture to deployment, every system is built to survive real users.

GenAI
Generative AI Systems
LLM-powered applications built for production — not demos. Structured outputs, fallback logic, cost control, and evaluation pipelines from day one.
RAG
Retrieval-Augmented Generation
Grounded, accurate AI that works over your private data. We engineer the full pipeline: ingestion, chunking, embedding, retrieval, and re-ranking.
Agents
Agentic AI Systems
Autonomous agents that work. We design for the hard problems: error compounding, non-determinism, tool reliability, and silent failure detection.
ML
ML Pipelines
End-to-end machine learning infrastructure — from data prep and training to model versioning, monitoring, and continuous retraining in production.
Auto
Intelligent Automation
Replace brittle rule-based workflows with AI-driven automation. We identify where intelligence reduces cost and ship it with measurable ROI.
MVP
AI MVPs in 2–4 Weeks
A fixed-scope, weekly-demo process that takes your idea to a production-grade MVP. Real users. Real infrastructure. No surprise scope creep.

Process

From idea to
production.

01
Scope Definition
We start with a single, well-defined use case. No vague briefs, no sprawling requirements. The cleaner the scope, the faster the ship.
Day 1–2
02
Architecture & Build
We design for production from the first line of code — authentication, data handling, error states, monitoring. Not features added later.
Week 1
03
Weekly Demos
Every Friday, a live working demo. Not a status update. Not a Figma file. Working software you can interact with, week by week.
Weekly
04
Production Handoff
Infrastructure, documentation, and a system built to last. We hand off something your team can maintain and your users can depend on.
Week 2–4
The WOD Labs Promise
2–4
Weeks to Production
Every project follows a fixed-scope, demo-driven process. This is not a timeline estimate — it is an engineering constraint we design around.
Fixed scope, no hidden variables
Weekly working demos, not progress reports
Production-first architecture from day one
Real users within four weeks
No offshore surprise teams

The Person Behind the Work

Built by someone
who has shipped.

KM
Kaushal Malhotra
Founder, WOD Labs
"AI should be intentional, not hype-driven. Every system I build starts with a real problem and ends with a real user."

I am an Electronics Engineer with over seven years of experience building software that runs in production. I have shipped more than 100 applications — from consumer products to enterprise pipelines — and led engineering teams of 25 or more.

I started Will of Dawn Labs on a single conviction: most AI projects fail not because the technology is wrong, but because the process is. We fix the process.

Electronics Engineer 7+ Years Experience 100+ Apps Shipped Teams of 25+ Delhi, India GenAI · LLMs · RAG

Insights from the field

What we are learning.

All posts
Production Reality
Why Most AI Projects Fail Before They Ship — And How We Fix That
After building 100+ applications, I have identified exactly three traps that kill AI projects before they reach a single user.
May 3, 2026
 Engineering Craft
Context Engineering: The Skill That Replaced Prompt Engineering
Prompts are only one layer. Context is five. Most builders are optimising the wrong thing — and their AI systems show it.
May 7, 2026
 Industry Analysis
Everyone Is Building AI Agents. Most Will Never Work in Production.
The agent demos are impressive. The production failure rate is not. Four specific problems are breaking agentic systems before launch.
May 5, 2026

Let's Build

Your AI.
Production-ready.

Tell us the problem. We will scope it, architect it, and ship it — in a timeline your investors will not believe and your users will appreciate.

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