Founder & Principal Advisor
Sylesh Ballolla
Enterprise AI Transformation · San Jose, CA
Twenty-five years leading enterprise transformation across HR, Finance, Sales, and Engineering. I design and ship production AI systems — not prototypes, not decks. I know what it takes to make AI work at enterprise scale because I've built the systems myself.
Background
I am an enterprise AI transformation leader and hands-on builder. In my current role as Principal Product Manager, AI Transformation at Intuit, I design and ship production AI systems across HR and IT.
The work I am most proud of at Intuit: a 360° closed-loop agentic quality system that autonomously detects knowledge gaps in HR self-service, drafts remediation content, routes it through human approval, publishes it, and re-tests to confirm the fix. Full quality evaluation cycle: under four minutes. I built an MCP-native HR operating system where employees access pay, time off, and tickets through conversation inside Claude Desktop. I built the NowAssist Testing Bot — a fully automated LLM test-evaluate-report pipeline using LLM-as-judge with multi-dimensional scoring, turning raw AI quality failures into prioritized fix lists for knowledge managers with no engineering background.
Before Intuit, 17 years at Cisco — Fortune 50, approximately $55 billion in revenue and 80,000 employees. I held fiscal responsibility for a $65M+ annual IT portfolio. I put four production AI capabilities into service in a single fiscal year using Llama 3.1 LLM and traditional ML models. I led Cisco's first ERP cloud transformation — Workday — running the full RFP against SAP SuccessFactors and Oracle HCM. I architected and deployed Cisco's unified HR service management operating model on ServiceNow HRSD across 96 countries.
Where I can help: defining AI strategy, designing end-to-end architecture, and proving out concepts before you commit resources. I help organizations understand the real gap — whether you're evaluating a vendor pitch or scoping an in-house build — between what looks good on paper and what it actually takes to make AI reliable, measurable, and trusted at scale. I have designed agentic systems with formal data contracts, mandatory HITL gates, and automated quality loops. I know what enterprise agentic AI requires to work.
Experience
Career history
Principal Product Manager, AI Transformation
Intuit
$15B fintech · TurboTax, QuickBooks, Credit Karma
2025 – Present
- →Designed and implemented ServiceNow HRSD and Conversational Experience
- →Built a 360° closed-loop agentic quality pipeline — the first of its kind at Intuit
- →Defined and prototyped the HR front-door strategy using MCP-native architecture inside Claude Desktop — establishing the blueprint for conversational AI as the primary employee HR interface
- →Built fully automated LLM evaluation pipeline (LLM-as-judge, 4-minute full cycle)
- →Deployed agentic workflow platform for PMO — end-to-end methodology governance across concurrent programs, reducing coordination overhead while maintaining program integrity at scale
- →Deployed agentic workflow system for cross-functional program teams — AI-native support for planning, status, decisions, and risk, enabling complex programs to run with less friction and full execution continuity
Sr. Manager, HR Technology & Digital Transformation
Cisco Systems
Fortune 50 · ~$55B revenue · ~80,000 employees
2008 - 2025
- →Managed $65M+ annual IT portfolio across 6 major business areas
- →Deployed ServiceNow HRSD across 96 countries — 350+ professionals, 54 services, one platform
- →Led Cisco's first Workday ERP cloud transformation (Core HCM, Talent, Compensation, PRISM)
- →Put 4 production AI capabilities into service in one fiscal year using Llama 3.1 and ML models
- →Built Cisco's Digital Architecture practice from zero: 5 senior architects across 3 countries
- →Designed world's first RFID IT asset management program: 2M+ tags, $6.3B assets, 65 locations