Kartik Raj Rewar
Helping companies become AI-native.
I work with leadership teams to identify where AI can create the greatest value, redesign workflows and operating models, and build the systems that turn strategy into real business outcomes.
Most recently, I founded and built Fursa, an AI-native hiring company.
MY APPROACH
Redesign the work, not just the tools.
The useful unit of AI transformation is the workflow.
Start with an outcome worth improving. Understand how the work actually happens. Then rethink the workflow around what AI can reliably do, where people add value, and how the economics change. Build the system around that, measure what matters, and keep improving.
What outcome is actually worth improving?
My most recent work
Fursa
AI-native hiring company
I built Fursa, an AI-native hiring company, as a production AI and data system spanning job intelligence, search, recruiting workflows, and AI agents. The interesting decisions weren't about whether to use AI, but where it actually belonged in the system.
Deterministic foundation
Clean the data first.
Ingestion, normalization, and high-confidence deduplication handled repeatable work before models were asked to interpret anything.
Model-assisted intelligence
Use AI for ambiguity.
Enrichment, classification, and semantic retrieval handled the parts that required interpreting messy language and user intent.
Workflow, not a wrapper
Put intelligence where work happens.
Search, recommendations, explanations, and feedback became parts of the hiring workflow rather than a separate AI destination.
The hardest failures in AI systems are often the ones nobody notices. A wrong result can be reported and fixed. A relevant job that never surfaces cannot. Building reliable systems means actively looking for what they miss, not just measuring what they return.
2M+
jobs processed
~200h → ~10h
monthly operational work
~$0.003
processing cost per record, ~80% lower than an LLM-only approach
Product in practice
A closer look at the job-search workflow.
Thinking
Ideas I keep coming back to.
Notes on AI, business, and what happens when we rethink how work gets done.
Background
How I got here.
Before Fursa, I founded Polynomial Studio to build and test new technology ventures. Earlier, I ran an early-stage technology company as General Manager, owning the P&L and leading a 15-person team. I also advised enterprises and government organizations on AI strategy, automation, and new business models.
I spent five years at Emaar, starting as an entrepreneur-in- residence, building its Digital Innovation function from the ground up, and eventually moving into Group Strategy. I worked with senior leadership, the board, and the investment committee on technology investments, new businesses, and capital allocation.
That journey gave me both sides of the problem: how leaders decide where technology matters, and what it actually takes to build and operate it.
I studied engineering at IIT Bombay and business at IIM Ahmedabad.