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Selected work

Proof from the field.
Where the stakes were real.

Data platforms, AI rollouts, and due diligence for organizations where the stakes were real.

Some projects below were delivered in partnership with a prime contractor, with Remix Ventures supporting the delivery team. Client names are withheld to respect confidentiality.

Enterprise analyticsAnalytics & BI

An enterprise analytics platform built from dozens of sources

Dozens of disconnected systems turned into one governed, self-service analytics platform.

Stack
FivetranAirbyteSnowflakedbt CloudLookerLookML
The challenge

Data sat in dozens of SaaS tools, databases, partner feeds, and spreadsheets. Reports took days to build and rarely agreed.

What we did
  • Ingestion with Fivetran for SaaS sources and Airbyte for custom and long-tail feeds
  • Raw data landed in Snowflake, secured with key-pair service accounts and role-based access
  • dbt models in dbt Cloud: tested staging, intermediate, and mart layers with lineage
  • A LookML semantic layer in Looker for governed, self-service metrics
Results
  • One source of truth with shared metric definitions
  • Automated refreshes, with tests that catch issues before dashboards do
  • Self-service exploration, and a foundation ready for AI
Member organizationAI Transformation

Making an organization queryable with AI assistants

Scattered documents and know-how turned into knowledge staff can query, with AI assistants rolled out on top.

Stack
Anthropic ClaudeOpenAIMicrosoft 365 Copilot
The challenge

Know-how lived in scattered documents, inboxes, and people’s heads. Staff tried AI on their own, with no plan for tools, guardrails, or training.

What we did
  • Mapped existing processes and where knowledge actually lives
  • Consolidated and structured documentation so assistants can answer from it
  • Rolled out Anthropic, OpenAI, and Microsoft 365 Copilot agents, with licenses sized to roles
  • Set guardrails and wrote a practical staff guide
Results
  • Plain-language answers grounded in the organization’s own documents
  • Processes and documentation mapped and kept in one place
  • AI used in everyday work, not as side experiments
InvestmentTechnical Due Diligence

Investor due diligence on a consumer health pivot

An independent read on whether a digital health company could deliver its product pivot.

The challenge

An investor needed to know whether a digital health company’s product pivot was technically credible.

What we did
  • Reviewed the product, technology, and plan behind the pivot
  • Assessed what delivery would realistically require
  • Translated findings into investment risks
Results
  • A plain-language view of what the pivot would take to deliver
  • Risks framed directly for the investment decision
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