— Careers

Build the performance layer for the agentic shopping era.

We are a small team building Lantern in New York. The work sits at the intersection of model evaluation, commerce systems, and design for serious operators.

— What we work on

Three threads of work, one operating loop.

Each thread compounds. The systems team makes the answers observable; the commerce team turns signals into shippable work; the measurement team proves what moved.

Thread 01

Make AI answers observable

Build the citation telemetry that runs buyer-intent prompts across ChatGPT, Claude, Perplexity, and Gemini — and explains why a recommendation moved.

Thread 02

Translate signals into commerce work

Turn Citation Score, External Signals and Industry Changes into recommendations a DTC team can ship this week.

Thread 03

Prove what moved

Connect every Applied recommendation back to the Brand AI Health delta it produced. The audit log IS the product.

— Operating principles
  1. 01

    Write down the argument before building the interface.

  2. 02

    Prefer a small loop with real customer evidence over a large abstract roadmap.

  3. 03

    Treat design, data quality and reliability as product work, not polish.

  4. 04

    Keep the output useful to the operator who has to make a decision this week.

— Run the loop

See where AI recommends competitors. See what to fix first.

No store access. No signup. The first scan lands as a board-ready brief, not another dashboard.

— What to include
  • The role or area you are interested in
  • Examples of hard work you made clearer
  • Where you are based and when you could start