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Request a fit call
For technical founders (pre‑seed → Series A) who need repeatable traction

Operator Founders Bring In to Scale GTM

Operator Founders Bring In to Scale GTM

The GTM Cofounder Technical AI Founders Bring In When Revenue Isn’t Predictable Yet.

Typical Founder Pains

  • Lack of a clear product-market fit
  • High burn rate without revenue generation
  • Lack of a clear and durable enterprise competitive moat
  • Risks of deals stalling, everchanging Ideal Customer Profiles, no clear wedge
Request a confidential fit call
What changes in 45–60 days

Capacity is extremely limited. I work with only a very small number of startups at a time.

Mayur Palta

HBS alumnus • Stanford AI program • Operator across enterprise + startups

Equity‑aligned

Founder‑confidential

Built / Building

Scale CI
Ontobricks
ICI Specialty Carbon Blacks USA
Palta Infocomm

Leadership & pedigree

President, SCIP
Board Member, ASEI
HBS Alumni
AWS • Databricks • Oracle • Dell EMC

Early-stage AI startups don’t fail because of product. They fail because the market never fully clicks. I partner with founders as an equity-aligned GTM operator to sharpen positioning, find the right customer, and build real pipeline fast. If you’re converting pilots or preparing to raise, the next 60 days matter. Engagements are typically 2–5% equity for cofounder-level scope — hands-on weekly execution, not advisory calls.

Why founders bring in a GTM cofounder like me

Proven track record at the intersection of enterprise GTM and early-stage innovation. At early-stage startups and medium to large enterprises, I built the GTM engine that either created the category or created unfair competitive advantage with a durable moat. As a founder and investor, I also see how hard it is to translate a strong product into repeatable and predictable revenue in the current uncertain times. My passion lies in closing that gap.

01

Acceleration in Revenue Generation

Because shipping is not the bottleneck anymore. Converting attention into revenue is.

02

Conversion of Go-To-Market engine into Measurable Outcomes

Replace hope with a weekly cadence that turns learning into pipeline.

03

Building a durable and competitive enterprise moat

Investors and enterprise buyers reward clarity, not noise.

There is No Compression Algorithm for Experience

That is where I come in. Someone who has seen the play before and can help you avoid rookie mistakes.

Builder

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Operator

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Pedigree

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Leadership

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Investor

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Capacity is intentionally limited

I work with only a small number of startups at a time.

Typical engagement:

  • Founder advisory
  • GTM cofounder role
  • Equity-aligned partnership

Engagement structure

Most founders start with:

STEP 1

Founder fit conversation

STEP 2

30-day GTM operating sprint

STEP 3

Equity-aligned GTM partnership

Fit: pre‑seed to Series A, enterprise‑adjacent AI

Especially when you have pilots or early customers — but positioning, ICP, and pipeline are inconsistent.

See the operating system
Request a fit call

Schedule Founder fit conversation

Send three lines: • Stage • Traction • Your biggest GTM bottleneck

Email

mayur@alumni.harvard.edu

Email Mayur

What to include

  • Stage (pre‑seed / seed / Series A)
  • Traction (pilots, ARR, pipeline, key logos)
  • ICP (buyer title + use case)
  • Your #1 GTM bottleneck right now
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