Sahaj Kothari has spent two decades on every side of the table that matters in technology. He built and sold two companies, managed over $100M in revenue across 42 brands, advised inside Bain and EY, and today invests in and operates alongside growth-stage AI companies across telecom, BPO, hospitality, real estate and healthcare.
That combination is rare on a stage. Most panels get a founder selling a product, or an investor describing the market from a spreadsheet. Sahaj runs an operating arm alongside the fund, so he speaks from what actually happens: what ships, what dies in procurement, and what year one really costs. Audiences leave with the patterns most people miss, not theory.
Three ways in.
An investor angle, a market overview, and an operator angle by sector. Each point is a talk Sahaj has given or can build for your audience.
What we actually underwrite in an AI company
Why most that look investable are not.
Both sides of the table
Winning commercially and in the eyes of investors.
The story that unlocks a raise
Fundable versus forgettable, and the gap between.
Reading an AI company in one meeting
The signals that separate signal from noise.
Where AI valuations break
What the numbers hide and what they reveal.
Operator-led investing
Why capital with sleeves rolled up outperforms.
AI in the real world
Winners versus the 99% that stall.
The eighteen-month gap
Where value is lost, pilot to deployment.
The execution premium
Why capital is not what AI is short of.
Voice AI as a revenue frontier
An operator revenue line, not a cost centre.
Scaling a nationwide voice programme
What it takes past the pilot.
When machines answer the phone
Production voice AI. What broke, what it costs.
The economics of automated calls
Capacity, margin, and year-one reality.
AI that lifts guest experience
Multi-language response over the funnel.
Voice and booking, done right
Beyond the chatbot bolt-on.
Scaling and restructuring ventures
Repositioning story and numbers to scale.
From product to investable company
Closing the commercial gap.
AI in regulated settings
Deployment when the stakes are clinical.
Trust, safety, and adoption
What moves AI from trial to standard care.
Sovereign AI is not sovereign data
For infrastructure-track audiences.
Buy, build, or partner
How enterprises should source AI.
Entrepreneur, operator, investor, and on the stage.
Two decades across building, advising, governance and the investment table. A well-rounded profile, recognised along the way.
Bring the operator-investor view to your stage.
Keynotes, panels, fireside sessions and pitch judging. Tell me the audience and what you want them to walk away with, and I will tell you straight whether I am the right voice for it.