Designing the Future of Audit Workflows: From Ambiguity to Agentic AI
Context & Project Overview
TL;DR: Led the end-to-end design strategy for DataSnipper's Agentic AI workflow, transitioning the product from a manual execution tool to an intelligent platform. This initiative eliminated severe user setup friction, secured high validation from 12 partner firms, and drove immediate enterprise seat expansions.
What is DataSnipper? DataSnipper is a platform that helps audit and finance teams work faster by automating repetitive document and data tasks. It started as an Excel-based productivity tool, but today it is evolving into a broader platform that supports end‑to‑end audit workflows. The core idea is simple: reduce manual copying, checking, and cross‑referencing so professionals can focus on analysis and judgment instead of mechanical work.
Why did we start this project? To consolidate the product strategy and identify the next major opportunity for DataSnipper's platform evolution, especially with emerging AI tools.
My Role: Staff Product Designer leading and owning design strategy, research, workflow systems design, interaction design, prototyping, and partner validation.
Timeline: Feb 2025 – Present
Initiative Impact
As the project evolved, it delivered four core outcomes that pushed the DataSnipper platform forward:
- Immediate Business Value: Three design partners proactively reached out for pricing before launch, with one customer requesting to expand from 40 to 1,000 seats.
- Validated desirability: Repeated prototype cycles confirmed strong user appetite for streamlined workflows and revealed the specific friction points that mattered.
- Integrated emerging AI capabilities: The team transformed a complex manual setup process into an intuitive, AI‑driven experience that broadened usability across all skill levels.
- Shaped a real‑world, testable MVP: Through the Design Partner Program, the team scoped and validated a practical first release grounded in real audit workflows rather than theoretical use cases.