A team collaborating in a modern office
Projects

Work that moves the numbers.

Selected BalancePro mandates. Client names are withheld to respect confidentiality. We are happy to share more in conversation.

Before BalancePro, our Managing Partner led finance at some of India’s most recognised companies. These outcomes were delivered in those roles.

2024 – 2025

ABD

CFO · 36 plants · US$1B+ revenue

Steered a US$1B+ IPO and the move to listed-company governance; closed and integrated three acquisitions and secured two credit-rating upgrades.

2023 – 2024

Bata

CFO · NSE/BSE listed

Make-or-buy and SKU-margin architecture; FII holding up from 6.0% to 8.8%.

2017 – 2023

Reliance Digital

CFO · 3,600+ stores · US$4.5B+ revenue

Part of the leadership team on Reliance Retail’s landmark global capital raise; +80 bps gross margin; private labels to ₹1,200+ crore.

2015 – 2017

Croma · Tata Group

CFO · US$1.5B+ revenue

Turnaround: +50 bps margin, –250 bps cost, 8 days off the cash cycle.

2010 – 2015

Walmart

Vice President – Finance

Unit-economics engine behind rollouts with a 31% post-audit IRR.

2002 – 2010

Metro Cash & Carry India

Head of Strategy & FP&A – Asia

Transformation across India, China, Japan and Vietnam; US$2M+ annual savings.

1995 – 2001

Reliance Industries

Capital projects & M&A

Project management and controls for a greenfield PTA plant, and work on M&A transactions: capex discipline learned at world scale.

1992 – 1994

Deloitte

Internship

An inventory-optimisation project that reduced working capital, the start of a career-long focus on cash.

US$15M

Series A raise for a high-growth business

PracticeCapital Raising through Equity & Debt
StatusClosed
Challenge
A fast-growing company needed an institutional-grade case that would stand up to diligence from experienced growth investors.
What we did
  • Architected the investment narrative and positioning
  • Built the integrated operating and financial model
  • Developed a value-creation blueprint linking capital to milestones
  • Supported investor Q&A through diligence
Outcome
A successful US$15M Series A capital raise.
AI-first

AI-enabled operating model for a bridge-to-luxury manufacturer-retailer

PracticeAI Intelligence Overlay · Fractional CFO–CIO
StatusIn progress
Challenge
A mid-sized brand that manufactures and retails wanted AI to sharpen pricing, customer engagement and inventory, without rebuilding its systems.
What we are doing
  • Deploying self-learning analytics for dynamic pricing
  • Feeding CRM and SKU-level inventory decisions from one data layer
Expected impact
Better online conversion, fewer markdowns and leaner inventory: decisions made on live data.
Buy-side

Due diligence on a PE-backed transaction

PracticeCapital Raising through Equity & Debt
StatusCompleted
Challenge
An acquirer needed an independent view of a target’s earnings quality and value before committing capital.
What we did
  • Led buy-side financial diligence
  • Tested earnings quality, working capital and debt-like items
  • Quantified synergy potential
Outcome
Critical valuation gaps surfaced ahead of negotiation, giving the buyer an evidence-backed position.
US$9M+

Seed-stage fundraise

PracticeCapital Raising through Equity & Debt
StatusClosed
Challenge
An early-stage business needed to translate its vision into numbers investors could underwrite.
What we did
  • Shaped the investment narrative and milestones
  • Built the financial model and use-of-funds plan
Outcome
A US$9M+ seed round.
Multi-LLM

Secure multi-model AI knowledge vault

PracticeAI Intelligence Overlay
StatusIn progress
Challenge
Business and market intelligence is scattered across documents and systems, and much of it is too sensitive for public AI tools.
What we are building
  • Evaluation of leading models including Google Gemini, Grok and Claude-compatible architectures
  • A proprietary, secure knowledge vault
  • Real-time market and business analytics on top
Why it matters
The foundation for the cognitive layer of the Intelligence Overlay: private, fast and grounded in your own data.

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