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For engineering teams

Your team has 5 agent frameworks and zero shared visibility.

That's not experimentation — it's technical debt that compounds every sprint. Nobody can debug each other's agents. Nobody knows the real cost. One registry, one pack format, shared traces — and your team stops reinventing and starts shipping.

Try it free

Agent packs: share work in the agentic era

Built to speed up innovation. Fully reproducible, with one-click publish and deploy the entire agent.

Author agent packs and skills, exercise them on any agent engine in the UI or CLI, then hand off — teammates install in one click from your library or the store.

Store catalog pulls curated agent packs your org can adopt without rebuilding the same glue.

What's actually slowing your team down

Standard packs

Publish once, install everywhere. Versioned, reproducible, rollbackable.

Private registry

Internal packs, prompts, MCP tools, and workflows. Your org, your store.

Shared visibility

Every team member's agent sessions, costs, and traces in one dashboard.

When your agents reach production

The moment real users depend on an agent, sharing packs isn't enough. Your team needs an agent control plane: every deployment governed by a lease, so you can kill one agent, deny one user, or cap the fleet from a single console — effective in under a minute. Each agent acts under its user's own permissions with a hard budget, and every action lands in a verifiable record. Enforced in your environment, at the data layer — not in a proxy.

Kill switch & caps

Stop an agent, a user, or the fleet from one console. Caps on turns, sessions, and concurrency.

Per-user authority

Agents act as each user — never a shared superuser. Enforced by your database, not the prompt.

Hard budgets

The request past the cap is refused, not warned about. Spend attributes to the person who asked.

Evidence trail

Who asked, which signed version ran, what it touched, what it cost — reconstructed in minutes.

Why a subscription, not a one-time tool

Agents are ML models. They drift, costs shift, providers ship breaking changes. Agent health is ongoing.

Cost governance

Per-member and per-pack spend limits. Alerts before budgets break.

Version management

Compare pack versions with data. Roll back when quality drops.

SSO & admin controls

Seat management, access policies, audit logs.

Expert support

Priority access to our team when agents misbehave or costs spike.

See plans