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MULTI-AGENT PLATFORM

Relay HQ

A platform for AI agent teams, with a growth product as the first team running on it.

7

agents coordinated through one lead

1

workspace context chokepoint — no cross-tenant leaks

Live

background runs that survive a closed browser

Pixel-art headquarters where Relay HQ agents work, with desks, a conference room, and a research lab

CHALLENGE

A real operational problem, not a demo.

Growth work for a mobile app is spread across analytics dashboards, store listings, competitor research, content calendars, ad budgets, and support inboxes. Most of it is repeatable, but none of it talks to the rest — and the team did not want an AI with free rein over live accounts.

SOLUTION

A system built around the work.

Relay HQ is the platform layer: auth and roles, isolated workspaces, a product registry, and an agent-run executor wrapped around the Claude Agent SDK. Growth Agent is the first product on top. Users only talk to Morgan, the Growth Lead. Morgan plans the work, delegates to specialists in parallel where it can, waits on dependencies where it must, and merges findings into one recommendation.

THE TEAM

One lead. Six specialists.

  • Morgan

    Morgan

    Growth Lead

  • Market Research

    Market Research

    Competitors, ASO, audience

  • Analytics

    Analytics

    Funnels, retention, anomalies

  • Content Growth

    Content Growth

    Ideas, hooks, post drafts

  • Paid Ads

    Paid Ads

    Budgets and forecasts

  • Customer Ops

    Customer Ops

    Reviews and support themes

  • Partnerships

    Partnerships

    Distribution opportunities

WHAT MAKES THIS DIFFERENT

The automation stays accountable.

Every workspace resolves through a single context chokepoint, so one company's data never leaks into another's. Runs queue through Inngest with retries and token accounting. The Knowledge Hub holds brand, competitors, and research — agents can only propose changes; a human approves them.

HOW IT WORKS

A clear path from signal to action.

01

Ask Morgan

A team member asks a question or sets a goal in the chat.

02

Plan and delegate

Morgan builds a dependency graph and hands work to the specialists that fit.

03

Run in the background

Inngest executes each run with retries; progress streams back as a replayable event log.

04

Merge and recommend

Morgan reconciles conflicting findings and returns one recommendation with follow-up tasks.

RESULTS

From fragmented work to a plan people can use.

Phases 0–5 are built: platform shell, office, agent runtime, Knowledge Hub, the specialist team, and Drafts. Automated tests, typecheck, and lint stay green. Integrations and instruction authoring are next — the operating surface is already real.

THE OUTCOME

7

agents coordinated through one lead

1

workspace context chokepoint — no cross-tenant leaks

Live

background runs that survive a closed browser

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