From routine tickets to deep, cross-system incidents — specialist agents that understand your organization's context, find the root cause, weigh the risk, and propose the fix. Whatever your stack. You direct, they execute, and nothing happens without your approval. Every step logged.
Routine requests and password resets, tricky debugging, incidents that span several systems and data sources, brand-new implementations — the full range, L1 to L3 — all handled the same way: following your organization's rules and standards, with every step of the reasoning and execution logged. That includes the deep L3 work: diagnosis across several systems, root cause, and the fix applied end to end.
It doesn't just suggest — it resolves. With your hand on the brake.
The agent reads the context of your environment.
It reasons through the diagnosis and proposes the action.
You approve — or not. It touches nothing without your OK.
It executes, resolves, and leaves a full audit trail.
It captures what it learned into a knowledge article — so the next time is faster, and the knowledge stays in your team.
These agents don't just answer questions — they become part of your team. They learn how your organization works, follow your governance model, respect your approval processes and progressively earn autonomy, like any new member joining your IT department.
Once they know your environment and consistently meet your standards, you can let them run specific tasks on their own — on your terms, reversible anytime. For example:
The platform is designed to integrate with your existing ecosystem — not replace it.
Agents work with your ITSM, CRM, ERP, identity provider, cloud and internal tools through APIs and your existing workflows, adapting to the way your organization already operates.
Every agent goes through an onboarding process, just like a new team member.
Before performing any task, agents are given your documentation, procedures, internal knowledge and organizational context. They begin by observing, understanding your environment, and gradually taking on more responsibility as trust grows.
Every action is evaluated before execution.
Agents weigh the requested operation, its potential impact, the permissions it needs, your organizational policies and the context available. Based on your autonomy policy, they either execute the action or request human approval.
Agents integrate with your organization's source of truth for identities and organizational structure.
That lets them understand reporting lines, ownership, managers and approval chains before executing sensitive operations or granting access.
Agents operate within configurable guardrails.
Each organization defines which actions can be executed autonomously and which require approval. Every decision and every execution is fully logged and auditable, so there is complete traceability of what happened and why.
Customer data remains isolated and protected. Deployment and data isolation strategies are adapted to meet your organization's security and compliance requirements.
Customer data remains the customer's property. We do not use customer data to improve or develop our platform.
AI requests are processed according to the policies of the language model provider configured by your organization.
You keep full control over your AI provider and API credentials.
The platform supports a curated set of language models that have been validated to guarantee the expected behaviour, reliability and quality of service.
Yes — that's the default starting point. Agents observe, reason and propose actions without making any changes.
As confidence grows, agents can progressively execute low-risk operations, while sensitive actions continue to require approval according to your policies.
Agents don't start with production access. Like a new employee, they first learn your organization: they ingest the documentation you already have and audit your live systems to build the real inventory — not the one the documentation claims.
The first deliverable is a report of what the agent understood about your environment, for you to correct. Only then does it start handling work, read-only and supervised at first, earning autonomy as confidence grows.
The platform helps organizations increase operational capacity — resolving more work with the same level of control. Where the gains come from:
Reduced MTTR · better process consistency · improved knowledge reuse · higher documentation quality · less operational friction across teams.