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customer storiesCustomer stories

Teams building with agents remember more with ULTRAMEMORY.

From multi-agent platforms to coding assistants and customer-facing bots — see how teams gave their agents one shared memory, and what changed.

What real teams remember — corroborated
  • user
  • agent
  • tool / web
  • Production region is eu-central-1conf 0.97×4
  • Customer is on the Enterprise planconf 0.93×3
  • Approvals go by email, not Slackconf 0.81×2

Teams building with agents.

  • Northwind AI
  • Carbon Labs
  • Helix Dev
  • Forge Agents
  • Vela Support
  • Atlas Knowledge
  • Loop Robotics
  • Pier 9
Customers[1 / 5]

One team, told well.

Lead with a multi-agent team — the wedge in a customer's voice.

Stories[2 / 5]

Proof across every use case.

Pick a use case to see who it's for — each story links to its own page.

  • All stories
  • Agent teams
  • Coding assistants
  • Chatbots
  • Personal / Knowledge
  • Coding assistants

    Their coding assistant remembers project conventions across sessions instead of relearning them each time.

    TBDcontext re-reads avoided
    Read the story →
  • Chatbots

    A support assistant remembers each customer, so replies feel personal and pick up where the last chat left off.

    TBDrepeat-question rate
    Read the story →
  • Personal / Knowledge

    One memory across a knowledge worker's tools, so the assistant recalls what was decided weeks ago.

    TBDrecall on older facts
    Read the story →
  • Agent teams

    Peer agents stay in sync on shared facts, with conflicts resolved to the current truth instead of contradicting each other.

    TBDfewer contradictions
    Read the story →
  • Coding assistants

    The right memory surfaces fast enough to stay in the editing loop, every keystroke.

    TBDp95 retrieval in the loop
    Read the story →
  • Chatbots

    Private and shared memory kept separate, so a customer-facing bot only recalls what it's allowed to.

    TBDprivate/shared boundary
    Read the story →
The numbers[3 / 5]

Real teams, real metrics.

Each figure ties back to the story it came from. Production-speed numbers come straight from the benchmarks.

  • -63%repeated work across agentsA multi-agent dev-tools team
  • sub-200msp95 retrieval, maintained in productionSee the benchmarks
  • 1shared memory across the whole agent teamA multi-agent dev-tools team
  • TBDfewer contradictions between agentsForge Agents
In their words[4 / 5]

One quote that says it.

“Our agents stopped contradicting each other. One shared memory, and the whole team finally agreed on what was true.”

Engineering lead · multi-agent dev-tools team (anonymized until permission lands)

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