Your AI is running.Your P&L isn't moving.
Their is a point after which the data exists but it never reaches the decision. Even with AI, the leak continues. That point and gap is defined asLogic Leak and I'll help you find and fix the logic behind it.
30 min · no pitch · no deck
$90M+ in AI portfolios · 15 yrs before AI was a buzzword
Systems built for leaders at
What is a Logic Leak?
A Logic Leak is the specific point where data exists and decisions are made but intelligence never flows between them. Most AI does not fail on the models, they fail here.
The method
Three steps. In sequence.
- 01
Test the use case before building it
Before any commitment: is this the right problem given the operational constraint, does the data actually exist to support it, and is it the right priority? Most bad vendor contracts begin in the gap between a good idea and a tested one.
- 02
Specify it in business terms
Every use case worth building names four things: the outcome being optimised, the logic connecting input to decision, the operational constraints, and the data that actually exists. If it cannot be written this way, it is still a hypothesis.
- 03
Put a number on it before spending
A structured model that converts the use case into a P&L figure before a line of code is written — a specific, defensible number a CFO can interrogate without a data scientist in the room.
- £11MAnnual cost recovery using proactive predictions · Telecom
- 94%Forecast accuracy improved from <60% · FMCG
- <30sInference time at the line reduced from 3min · Automotive
- +15%Gross Margin expansion within a year · Perishable Supply Chain
Where it's been applied
$37M impact through promotion-aware D2C forecasting
Read the full case Automotive100%digital inspection coverageFull-coverage quality inspection at production speed
Read the full case Telecom63%pilot churn reduction63% churn reduction through proactive retention
Read the full case Automotive Sales5xlead conversion uplift5x lead conversion through stage-wise sales intelligence
Read the full case“15% profit margin growth in six months. We'd spent 18 months on dashboards that told us what happened. Jitin shifted us to systems that change what happens next.”
“He doesn't deliver a deck and disappear. He stays until the logic is in the system and the team can run it. That's rare.”
Writing as proof
All writing
Strategy
AI in Automotive Quality Control: How ECG-Style Anomaly Detection found Faulty Engines in <5 Secs
A case of AI in automotive quality control where ECG-style anomaly detection caught 20 faulty engines hidden in 1.3M units, in under 5 seconds each, by defining normal instead of chasing rare faults.
Business
Who Should Explore AI Tools Inside a Business?
A practical operating rule for assigning AI tool exploration by temperament, not title, so curiosity creates operating memory instead of distraction.
Business
AI Tool Tourism
Why chasing every new AI tool creates cognitive load, workflow breakage, and fragmented productivity — and the three reasons that actually justify a switch.
The background
I'm Jitin Kapila. A Mechanical engineer turned AI CTO, and have spent 15+ years at the intersection of Business strategy, AI-driven outcomes and Operational delivery across manufacturing, FMCG, logistics, telecom, and automotive.
The companies whose logos appear above are ones I have built systems for. Not advised on with decks. Built for.
I still debug production systems and read the code, and I help translate what the data-science team is actually saying into language a CFO can act on. What I am not: a vendor. I do not sell platforms or take referral fees.
Ways to work
Where are you in the journey?
- 3-day executive sprintAI Profit OSBuild a ranked use-case list, an ROI formula anchored to your P&L, and a board-ready investment memo.View the sprint
- $93 · 8-question diagnosticAI Profit QuotientFind exactly where your problem sits on the AI spectrum — and what to do about it — before you commit to a sprint.Take the diagnostic
- 2-week audit · or embedded leadershipAudit & Fractional CAIOGo deeper: map where the logic breaks in a Logic Leak Audit, or embed part-time senior AI judgment as your Fractional Chief AI Officer.Book a Clarity Call
Common questions
What is a Logic Leak?
A Logic Leak is the specific point in an organisation's operations where data exists and decisions are being made, but intelligence is not flowing between them. The data that could improve a decision is not reaching it — due to structural, architectural, or process gaps. Identifying and closing the Logic Leak is the central diagnostic task in most AI strategy engagements.
What does an AI strategy consultant do?
An AI strategy consultant identifies which operational problems are worth solving with AI, defines those problems in terms a technical team can build from, quantifies the expected return before investment, and provides independent guidance that is not tied to any vendor or platform.
How do I know if I need an AI strategy consultant?
Three signals: (1) your AI pilots produced results in isolation but have not moved the P&L; (2) you are being asked to make an AI investment decision without a framework for evaluating it; or (3) an active AI programme is underway but results are not tracking to the original business case.
How do you calculate ROI before the model is even built?
ROI is calculated by mapping your current operational baseline (defect rates, inventory holding costs, manual processing time) against the known capabilities of standard AI architectures. We don't guess what the model will do; we calculate what the business process must achieve to justify the investment, setting a strict performance target for the build.
Do you build the AI models or just advise on them?
I architect the solution, quantify the expected return, and oversee the build as an advisory lead or Fractional CTO. I do not write the production code or sell proprietary platforms. My value is in independent specification and vendor management — ensuring the technical team builds exactly what the P&L requires, without scope creep or vendor lock-in.