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AI Global Workflows

EnvestnetPrincipal Director / Designer2025–Present

Envestnet's first AI MVP: a shared framework, a set of AI components and two pilot workflows, aligned across products and brand.

Dark-mode dashboard with an AI assistant panel
The problem

The company knew it wanted AI, but not yet where it would add value. Strict governance and fragmented data made every step harder.

  • Moving from “we need AI” to specific user problems
  • Data that wasn't ready for AI
  • Governance, compliance and trust gaps
  • No shared way to build AI across teams
  • Getting from MVP to production
Mapping our data to the components we wanted to build
Data mappingMapping our data to the components we wanted to build
How we did it
  1. 01Compare

    Studied what AI companies and our competitors were building.

  2. 02Map the data

    Worked with data, product and engineering to match data to components.

  3. 03Test with users

    Ran focus groups on AI workflows and compliance concerns.

  4. 04Pilot two use cases

    Service requests and reports, to prove the framework.

The work
A conversation guides users from request to submission
Service requestsA conversation guides users from request to submission
Build a report by prompting, then configure it
Report builderBuild a report by prompting, then configure it
A summary to review before documents are generated
ProposalsA summary to review before documents are generated
Competitive comparison of AI products
ResearchCompetitive comparison of AI products
Data mapping across product and engineering
ResearchData mapping across product and engineering
Up next
Command center
Command centerA daily snapshot of insights and actions
Explainability
ExplainabilityClear answers with their sources
Natural language
Natural languageFind data without complex filters
Workflows
WorkflowsAI that simplifies complex processes

Let's make something users love.

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