← Selected work
Enterprise AI / workforce intelligence2026 — ongoing, reduced involvement

Trackwize

Co-founded a privacy-first workforce intelligence platform — from the first whiteboard to a live product and an investor pitch.

Role

Co-founder, product & design

idea to pitched MVP

0→1

The problem

Most workforce-intelligence tools ask companies to choose between visibility and employee trust — more monitoring for more insight. That trade-off is the reason timesheets and activity trackers get gamed instead of used. We set out to build something that gives operators real visibility without asking employees to be watched.

Approach

  • 01

    Framed the product thesis around differential privacy — statistical noise that protects individual records while keeping team-level patterns useful — before a single screen was designed, because the trust model had to be structurally true, not a privacy policy bolted on later.

  • 02

    Designed the core workforce-intelligence dashboard around outcomes and work patterns instead of hours logged or keystrokes tracked.

  • 03

    Built and presented the MVP narrative for the D2C Founders x Investors pitch event (NMIMS, Mumbai) — translating a technical privacy mechanism into a story a non-technical investor room could trust in six seconds.

Decisions

Privacy as the product thesis, not a settings toggle

Instead of collecting raw activity data and adding privacy controls afterward, the product only ever surfaces aggregate, noise-calibrated patterns — so there's no raw individual record to protect in the first place. This shaped the data model, the dashboard's information architecture, and what the UI is structurally incapable of showing.

Measuring outcomes, not hours

Rejected the default timesheet/activity-log UI pattern. The dashboard reasons about context and work patterns instead, which meant designing a new visual vocabulary — there was no existing pattern library to borrow from.

Designing with AI

Trust calibration is the product's entire premise: showing organizations only what differential privacy allows through, and being explicit with users about what is and isn't visible to their employer.

Outcome

Live MVP, pitched to investors and operators at a Mumbai founder event; product decisions now guided by direct founder/CTO conversations rather than a fixed spec.

Outcome as reported at the time of the engagement.