Enterprise

AI agents for the whole company, with rules you set.

Team leads set up skills and workflows, define what agents can access, and see every run.

Four commitments, visible in the product

  • Control

    The invoice intake skill may read invoices and write records, nothing else. Posting only happens after Ana approves.

  • Traceability

    Every run records who started it, which data it read and who approved.

  • Revert

    The previous state is saved before every change. You revert a single change or the whole run.

  • Data protection

    Hosted in Frankfurt, data separated per company, encrypted in transit and at rest.

Built for teams, not for solo experiments

  1. 01

    Team leads set up, the team runs

    The team lead builds the skill, connects the systems and defines access. The team starts it and checks the result. Improvements happen in one place for everyone.

  2. 02

    Spaces with roles

    Every department works in its own space. Each space has admins, editors and readers, and workflows can be shared with specific people.

  3. 03

    Bring your existing work instructions

    Paste the work instruction, and the assistant builds the skill and workflow as drafts. Nothing is published before your review.

Your people already work with agents. Here they run by your rules.

  1. 01

    Claude Code, Claude Cowork and Codex over MCP

    The local agent works with the same permissions, approvals and log as the built-in assistant. What a person may not do, their agent may not do either.

  2. 02

    The inbox instead of Slack and private drives

    Agents send each other results and files through one address per person. Everything stays in the platform, and whatever arrives counts as content for the agent, not as a command.

Costs and outer boundaries

  1. 01

    Cost per step and a limit per run

    Every run shows cost and duration per step. A cost limit on the workflow stops the run before it gets expensive.

  2. 02

    Suppliers and customers without access to your account

    External people do their step on a page with its own link, password and expiry date. They only see the rows you open up for that link.

Security

Security principles

No certificate logos, just what technically applies.

  • Encryption

    TLS in transit. Database and file storage are encrypted at rest.

  • Credentials

    Credentials for your systems are additionally encrypted at application level and redacted in logs.

  • Tenant separation

    Every query is bound to your company. No skill, agent or link reads another company's data.

  • Least privilege

    A skill only gets the integrations and record types you give it.

  • Human before effect

    Publishing, deleting and bulk imports are reserved for people. Write actions by the assistant need your approval.

  • Immutable log

    Audit events are only appended, never changed, and are hash-chained per company.

  • Location and backups

    AWS Frankfurt (eu-central-1). The database is not publicly reachable, backups run daily.

  • Sign-in and SSO

    Sign-in through a specialised identity service. We set up SSO over SAML or OIDC for enterprise customers on request.

How we work with you

  1. 01

    Conversation

    We walk through your processes: systems, data flows, approvals, who needs to see what.

  2. 02

    Pilot

    One space, one process, one team. With real documents and by your rules.

  3. 03

    Rollout

    More teams and integrations. Contract, data protection documents and support as agreed.

Common questions

We set up SSO over SAML or OIDC for enterprise customers on request. A self-service setup in the product does not exist yet.

Yes. Every operation creates an audit event that is only appended and never changed. Events are hash-chained per company. An export as a file is not built yet.

Paste the work instruction into the assistant. It builds the skill and workflow as drafts, including the approval steps. You review and publish.

No. The platform runs as a cloud service in Frankfurt with separated tenants.

The model is chosen per skill, and every run shows which model worked. OpenAI, Anthropic and Google Gemini are connected.

A data processing agreement, the list of subprocessors and a description of tenant separation, encryption, retention and deletion. If your questionnaire needs more, we fill it in together.

Describe the task. The rest takes shape on the platform.

Start for free, create your first skill with the assistant, and see what a run looks like before you connect anything.