@Human forManaged service providers
Offer governed AI to every client from one platform.
Run service desks, knowledge assistants and client applications for many customers, each on its own @Human instance with its own policies, risks and sign-offs, and a hub that shows you exactly where every client stands.
- Multi-client hub
- Real-time alerting
- Rule-based fallback
What's slowing AI down in managed services
The pressure is real, and so are the rules. Here's what teams like yours are up against.
Customers demand governed AI
Your clients' boards and regulators now ask how AI in their service desk is governed. You need an answer for every one of them.
You are in scope too
Managed service providers are covered by the EU's NIS2 Directive, with duties for risk management and incident reporting.
Per-ticket AI costs eat margin
Agentic workflows that call a model on every ticket turn your best contracts into your least profitable ones.
Applications you could build with @Human
Beautiful, everyday tools for your teams and the people you serve, each one a governed project from the first line.
Client Governance Hub
Every client's governed apps, evidence, incidents and pending sign-offs on one screen.
Service Desk
Tickets are routed by rules, and a knowledge assistant drafts replies with sources for the engineer to check.
On-call
Real-time alerts with suggested steps. Pause an assistant with one tap and fall back to rules.
Example apps with illustrative data, showing what can be built on @Human.
Governance built for managed service providers
Every @Human app moves through six stages, from setup to compliance evidence. These are the parts that matter most to you.
An instance per client
Each client gets its own @Human instance, with its own data, policies, risk scenarios and approval gates.
Client sign-off
Your client's governance owner can sign releases that affect them.
Event logging
Every assistant answer, change and release is logged for client audits.
Incidents and alerts
Real-time alerts open incidents, with owners, actions and reviews tracked to closure.
Rule-based fallback
Pause any assistant and keep services running on programmatic automation.
Evidence per client
EU AI Act, ISO/IEC 42001 and GDPR evidence packs, exported per client.
AI can propose. People decide. In @Human, AI can prepare work but can never approve or publish a release.
Cheaper to run. Impossible to lock in.
@Human favours tested, programmatic automation wherever the choice exists, so your apps cost less, behave the same every time, and keep working without AI.
Protect your margins
Routing, escalation and reporting cost nothing in tokens, at any ticket volume.
Always on
If an AI provider fails, your desks keep running on rules.
Safe rollouts
Changes go through a draft and sign-off for each client before release.
Reuse across clients
Build a service once and roll it out to the next client with its governance intact.
Can one @Human instance serve many clients?
It can, but we recommend one instance per client. Projects in the same instance share a database and are kept apart by role-based access rules rather than database-level isolation, and they share automations and access control. A separate instance per client keeps each client fully apart.
Can clients approve their own releases?
Yes. Add the client's governance owner to the project's approval gates.
What happens when an assistant misbehaves?
Alerts open an incident, and you can pause the assistant while rule-based automation keeps the service running.
Where is client data hosted?
Wherever you or your client choose: your cloud, theirs or on-premises. @Human is not SaaS.