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Zero-to-one Build

Ai Native Workflows

End-To-End Features

Complex data

Customer Facing & B2b App

Ontra Atlas

AI-Powered Data Management Application

Overview

Modernizing Legal Entity Management by building a digital "single source of truth" for corporate records, generating $1M+ in sales within the first year.

Impact

$1M+ Sales

Timeline

9 Months

Platform

Desktop Saas

Collaboration

Product Trio

Partnered with Product and Engineering teams to define strategy and priority.

"Legal Intelligence" Team

Worked with former lawyers and subject matter experts to break down complex compliance logic.

Co-Dev Partners

Regular and frequent validation sessions with beta customers throughout the design phase.

Background

Legal entity management systems act as a single source of truth for corporate records (ownership, governance, tax, M&A), primarily used by legal, finance, compliance, and tax teams.

Before this product, teams relied on fragmented spreadsheets and email threads, leading to inaccurate data, inefficiencies, and limited visibility for leadership. Managing compliance across multiple jurisdictions added further complexity without a centralized system.

With 96% of organizations reporting challenges in this space, Ontra identified a clear market gap. Customer research validated strong demand for a centralized, purpose-built solution.

Research statistics from 3rd party Report

Cross-Functional Collaboration

I worked within a core "Product Trio" (myself as Lead UX, a Product Manager, and an Engineering Manager) on a regular basis to define the product strategy, prioritize features, and determine project scope. I collaborated closely with an 8-person engineering team, which notably included a Quality Engineer and a Machine Learning Engineer to support our data integrations. Additionally, we partnered directly with co-development partners—key customers who agreed to review and provide continuous feedback on beta versions of the app prior to our public launch.

My Responsibilities: I owned the end-to-end UX process across the entire product lifecycle, including:

  • Research & Discovery: Competitor analysis, and problem discovery and solution validation with external users and internal stakeholders (Sales & Implementation teams).
  • Strategy & Architecture: Story mapping, workflow diagrams, and defining the complex information architecture.
  • Data Visualization Strategy: Defined the UX for complex information displays, including massive data tables, advanced filtering logic, and centralized dashboards.
  • Design System Integration: Leveraged our existing design system (which I previously built from scratch) to quickly create clean, scalable layouts and user flows that remained completely visually and functionally consistent with Ontra's other applications.
  • Design & Prototyping: Wireframing, UX copywriting, and building high-fidelity mockups and interactive prototypes.
  • Edge Case & Error Documentation: Extensively mapped and documented all "unhappy paths", edge cases, and error states to ensure a robust engineering implementation.
  • Testing & Iteration: Leading continuous feedback and testing sessions with our co-development partners.
  • Delivery & QA: Iterating closely with Product and Engineering, handling developer handoff, and conducting Design QA prior to launch.
  • Post-Launch Monitoring: Leveraged Pendo to set up tracking and monitor user adoption, engagement, and feature usage after the initial launch.

Process & Challenges

Lack of Standardization

During discovery we quickly noticed that there were no standardized workflows or terminology across customers. This was identified a critical issue. Each organization approached entity management differently, often requesting highly customized solutions. This created a core tension: balancing flexibility for diverse user needs with the need to design a scalable, maintainable system.

To address this, I partnered with internal legal subject matter experts to break down customer requests into underlying needs. Instead of designing for edge-case customization, we focused on identifying shared patterns across users. This approach allowed us to create standardized, flexible solutions that satisfied legal requirements while remaining scalable for the product.

Core UX Challenges

  • Large-scale Data Management: I had to design scalable data tables and advanced filtering logic capable of displaying thousands of dense data points (jurisdictions, ownership structures, compliance deadlines) without causing cognitive overload.
  • AI Integration: We needed to seamlessly weave machine learning features into the core workflows so they felt intuitive, helpful, and trustworthy to legal professionals, rather than intrusive or confusing.
  • Standardizing the Unstandardized: Building an information architecture that felt custom enough to handle individual client workflows while remaining scalable enough for our engineering team to efficiently maintain.

Workflows & Story Maps

Solution & Key Features

AI-Powered Single Source of Truth

I designed workflows that leverage machine learning to automatically ingest and organize entity records. This eliminated over 40 hours of manual data entry per month for our core users.

I then created a centralized dashboard that aggregates and structures entity data from multiple sources, allowing users to manage relationships, documentation, and records in one place. This reduced manual data entry and improved trust in data accuracy.

Dynamic Structure Charts with Scenario modeling

I created a robust visualization tool that algorithmically generates complex ownership and capitalization charts. I also designed a "Pro Forma" sandbox mode, allowing users to model proposed changes to existing structures.

This transformed hours of manual diagramming into an instant, interactive visual experience that allows teams to guide strategic transaction decisions and gather internal alignment before executing deals.

Centralized Governance & Automated Workflows

I created a scalable system to track directors, officers, and authorized signatories, complete with codified, multi-step task workflows to keep stakeholders accountable.

This solved a major regulatory headache by allowing teams to execute mass personnel changes (e.g., removing a director across 50 entities) in a single, seamless action, drastically reducing compliance risk.

Sample Screens from New App