AI Models
AI for Information Technology

Resolve, automate and secure your estate.

Service-desk agents, runbook automation and instant knowledge for IT teams that need to do more with the people they have.

Information Technology assistant
Summarise last night’s alerts and tell me what needs attention first.
Two alerts matter: disk pressure on a reporting server (trend rising) and repeated sign-in failures from one region. The rest were transient. Suggested actions follow.
Ask anything…
The challenge

What holds information technology teams back

  • Ticket backlogs

    Repetitive requests bury engineers and slow everyone down.

  • Tribal knowledge

    Answers live in people’s heads and scattered wikis.

  • Alert fatigue

    Too many signals, too little context to act quickly.

Use cases

Six ways to put AI to work, today

Resolve, automate and secure across your estate.

  • Service-desk agent

    Resolves password, access and how-to requests end to end.

  • Knowledge assistant

    Answers grounded in your runbooks and docs.

  • Incident summaries

    Turn noisy alerts and logs into clear timelines.

  • Script generation

    Draft and explain automation scripts safely.

  • Change reviews

    Summarise risks and impacts for change approvals.

  • Asset insights

    Ask natural-language questions about your inventory.

How it works

From first prompt to everyday workflow

  1. 01

    Connect knowledge

    Load runbooks, KB articles and policies.

  2. 02

    Grant safe skills

    Allow approved actions with clear permissions.

  3. 03

    Triage & resolve

    Agents classify, answer and act on tickets.

  4. 04

    Escalate cleanly

    Hand off to engineers with full context.

Agents & skills

Agents built for information technology

Give an agent a goal and it plans the steps, uses the skills you grant and reports back — with approvals wherever you want a human in the loop.

  • Service-desk agent: Resolves password, access and how-to requests end to end.
  • Knowledge assistant: Answers grounded in your runbooks and docs.
  • Incident summaries: Turn noisy alerts and logs into clear timelines.
Explore agents
Agent run · live
  1. Understand

    Intent & context

    Done
  2. Plan

    Break into steps

    Done
  3. Act

    Run skills & tools

    Running
  4. Deliver

    Verified result

    Queued
Outcomes

What changes when you switch it on

  • Outcome 1

    Shorter queues

    Routine tickets resolved without waiting for a human.

  • Outcome 2

    Knowledge on tap

    Everyone gets expert answers, instantly.

  • Outcome 3

    Calmer incidents

    Faster context means faster, better decisions.

Under the hood

Foundational models, plus proprietary architecture

Every leading open model family, made sharper by the layer we built around them.

  • Routing

    The best model for each request, automatically.

  • Memory

    Your information technology context, remembered securely.

  • Skills

    Search, read, write and call your own tools.

  • Agents

    Goal-driven workers with guardrails.

Security posture

All controls healthy

Continuously monitored

  • Encryption in transit & at rest
  • SSO & scoped API keys
  • Audit logs for every action
  • Your data never trains shared models
Security & control

Enterprise-grade from day one

  • Your data is never used to train shared models
  • Encryption in transit and at rest
  • Roles, scoped API keys and approval steps
  • Audit logs, SSO and private deployment options on higher plans
FAQ

Information Technology questions, answered

Can agents take actions in our systems?

Yes, through skills you approve, with human sign-off for sensitive steps.

Do you support SSO?

Yes, SSO and SCIM are available on Enterprise.

Are actions logged?

Every agent step is logged and audit logs are available on Scale and above.

Can we keep data isolated?

Workspaces are isolated, and Enterprise offers private deployment options.