Sorcero
Leading 0→1 product design for an enterprise-ready AI platform.
When I joined Sorcero, the company was an early-stage, venture-backed team of highly skilled data scientists and engineers. They had built powerful natural language processing capabilities and secured pilot engagements in life sciences and insurance, but they did not yet have a cohesive product.
AI tools lived across disparate sandbox environments and proof-of-concept implementations. The company could deliver pilots, but there was no unified platform that enterprise buyers could clearly understand, adopt, or scale.
My role was to help transform advanced technical capability into a structured, usable product.
0→1 Platform UX Strategy
Product Architecture & System Definition
Workflow & Interaction Design
Design System Foundation
Enterprise Data Visualization
Cross-Functional Product Leadership
Scope
Role & Ownership
I joined as Sorcero’s first product and UX hire, serving as Principal Lead Product Designer. I worked directly with the CEO, CTO, sales, marketing, and product stakeholders to define the company’s initial platform experience.
Beyond interface design, I helped shape product structure itself — defining how features surfaced, how workflows were organized, and how enterprise users would interact with complex AI systems. I created Sorcero’s first design system, established foundational interaction patterns, and influenced roadmap direction to align technical innovation with real-world usability.
The Real Problem
Sorcero’s technology was sophisticated, but it lacked product definition.
Capabilities existed, but there was no cohesive workflow model or structured platform through which users could engage with them. Engineers were building layered ontologies and domain-tuned intelligence, but there was no unified experience translating those capabilities into practical business value.
Without product structure, the offering was difficult to scale, difficult to sell clearly, and difficult for non-technical enterprise users to navigate.
The core challenge was transforming AI capability into product clarity.
What Mattered Most
Clarity and explainability were non-negotiable.
I spent months deeply learning the underlying technology to ensure the experience accurately represented what the AI could and could not do. In regulated industries such as life sciences and insurance, enterprise users needed to understand how insights were generated and how outputs related to their data.
Equally important was workflow structure. The platform had to support non-technical enterprise users, not just data scientists. Complex ingestion pipelines and enrichment layers needed to be surfaced in a way that felt coherent, not abstract.
Key Decisions
One of the most important decisions I made was defining the platform’s core workflow model.
Rather than presenting isolated AI features, I structured the experience around projects, ingestion pipelines, and utility sets. Ingestion became a defined product concept: naming projects, selecting sources, configuring pipelines, enriching content, and applying layered processing toward specific outcomes.
Navigation required deep architectural thinking. I designed a multi-tier model that allowed users to move between:
Project-level views
Ingestion lists
Pipeline configuration
Enrichment workflows
Detailed content analysis
I also determined how intelligence surfaced across dashboards, document views, and comparison tools, ensuring outputs were interpretable rather than opaque.
The Work
The process began with collaborative journey mapping in Mural, translating abstract technical capabilities into structured product flows. From there, I created detailed UX designs and high-fidelity prototypes in Figma to validate direction internally and with early users.
We iterated heavily. Complex ingestion processes, multi-layer navigation, and AI output presentation were refined through repeated feedback cycles. While formal usability testing was limited at this stage, continuous stakeholder and pilot feedback informed rapid improvements.
I also indirectly influenced how the platform was positioned externally by shaping how capabilities surfaced within the product itself.
Outcome
As a result of this work, Sorcero had a defined, functional platform where previously there had been only technical capability and pilots.
The company could demonstrate a cohesive product experience to enterprise buyers. Complex AI workflows were translated into structured, navigable experiences that supported real-world business use cases.
The platform established the UX foundation for Sorcero’s transition from experimental implementations to a scalable, enterprise-ready offering.
