AI-native strategy consulting
AI strategy, built to ship.
Most AI work stalls between a promising demo and a system in production. Stratessence closes that distance. We help companies turn generative and agentic AI into strategy that reaches the real world, and help investors tell what is durable from what is a wrapper.
Advising founders since 2009 · Now AI-native
For companies
Work with us
Set your AI direction, then rebuild the workflows that matter around it. Strategy that reaches production, not another shelf of pilots.
Explore servicesFor investors
Invest with confidence
Independent technical and market diligence on AI companies. Tell a durable advantage from a thin layer over someone else's model.
AI diligenceFor everyone
Learn with us
Frameworks and essays on building with AI, written by an operator. The thinking we use in the work, in the open.
Read insightsOur point of view
The gap is not the model. It is everything around it.
The models are good enough for most of what companies want to do with them. The reason AI programs disappoint is rarely capability. It is the distance between something that works in a demo and something a business can rely on: evaluation, integration, cost, trust, and ownership.
We call that distance the Production Gap, and closing it is the whole job. We work as senior operators, in the plan and in the build, so AI becomes part of how you work rather than a project that quietly ends.
Read the Production Gap frameworkEvaluation
Can you measure whether it is right, every time, before and after each change?
Integration
Does it live inside your real systems, data, and permissions, or only a sandbox?
Cost
Do the unit economics survive the volume you are hoping for?
Trust
Are there guardrails and human review where being wrong actually matters?
Ownership
Is there a named owner and a runbook for the day it breaks?
What we do
Four ways to work together
For leadership teams
AI Strategy & Roadmap
A clear, sequenced plan for where AI creates value in your business, and how to get there without betting the company on a demo.
For operating teams
AI-Native Transformation
Redesign the operating model so AI is part of how work happens, not a tool bolted onto the side of it.
For founders and CEOs
Fractional AI Leadership
Senior AI leadership on a fractional basis: the judgment of a Chief AI Officer without the cost or the wait of hiring one.
For investors
AI Diligence for Investors
Independent technical and market diligence on AI companies: what is real, what is a wrapper, and what is defensible.
Selected work
Engagements across three continents
Illustrative, anonymized examples of our work across India, the United States, and Asia-Pacific.
Bringing focus to a scattered AI effort at a B2B SaaS company
A product org running a dozen disconnected AI experiments needed a way to choose what to actually build.
Rebuilding a sales workflow around AI at a B2B SaaS company
Slick demos of AI sales tooling never translated into a change in how the team sold.
An enterprise generative AI strategy for a bank
A bank needed to turn broad generative AI enthusiasm into a governed, prioritized plan.
The thinking
Frameworks we work by
Our point of view, made concrete. The same models we use inside engagements, published in full.
The Production Gap
The distance between a working AI demo and a system in production, described as five specific gaps.
The AI-Native Ladder
Four stages of AI maturity, from ad-hoc experiments to an operating model rebuilt around AI.
The Use-Case Value Map
A way to rank AI opportunities on value and feasibility so priority is a decision, not a preference.
The Wrapper Test
Five questions that separate a durable AI advantage from a thin layer over someone else's model.
Insights
Recent writing
2026-06-28
How to build an AI strategy that actually ships to production
A practical method for turning AI ambition into systems that reach production, built around value mapping, honest prioritization, and closing the Production Gap.
2026-06-20
Why generative AI pilots fail to reach production
Most AI pilots work in the demo and die on the way to production. The reason is rarely the model. It is the five gaps between a demo and a system a business can rely on.
2026-06-12
What "AI-native" actually means
AI-native is used to mean everything and therefore nothing. Here is a precise definition, a maturity ladder to locate yourself on, and why the rung you are on is the first honest strategic fact.
Turn your AI ambition into something that ships.
A first conversation is the fastest way to find out whether we can help. No pitch deck, no obligation.