01
Access provisioning & password resets
Resolves routine identity and access requests directly against your documented policy, without a technician touching every ticket.
Agentic AI for ITSM
Resolve tickets, do not just route them .
We build agents that read incidents and service requests against your knowledge base and systems, resolving what they can and routing the rest with context attached.
Trusted by operators
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+11.76% orders from day 1 of the Australian launchThree-agent product advisor guiding customers through print-order configuration.
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Supply chain intelligence agents reducing manual coordination overhead.
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37 kernels ported from CUDA to Intel GaudiProduction AI workloads moved to new hardware for on-prem LLM deployment.
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AI agent implementation for a global automotive enterprise.
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2 hrs → 3 min to generate a workflowText-to-workflow agents building validated node graphs inside the platform.
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0 hallucinations across 329+ validation scenariosHIPAA-compliant agentic RAG over proprietary clinical triage guidelines.
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Why agentic AI
Most ITSM automation routes the ticket and stops there
Workflow rules match a ticket to a queue based on a fixed pattern. An agent reads the actual incident, cross-references your knowledge base and system state, and either resolves the standard case directly or routes the exception with the reasoning attached — handling the variation a rule set cannot.
every resolution traces to a documented runbook
Use cases
Where agents earn trust in IT service management
Ticket categories with a documented resolution path.
02
First-line incident triage
Reads incoming incidents against your knowledge base, resolving documented cases and routing the rest with a summary attached.
03
Change-request documentation review
Cross-checks change requests against policy and prior incidents, drafting a review summary instead of a manual read-through.
04
Knowledge-base grounded answers
Answers employee questions from your actual runbooks and documentation — sourced, not generic advice.
What the mechanism delivers
Routing and resolution under load, measured in production
None of these numbers come from an ITSM deployment — we have not shipped one yet, and we are not going to dress up a proxy as one. They come from Mixam (print on demand), Synera (engineering software) and Schmitt-Thompson (healthcare). They are here because each measures a mechanic a service desk runs on: evaluating and routing work in real time across many tools, executing a multi-step procedure on top of systems that already exist, and stopping rather than guessing when the source material runs out. Every figure links to the case study behind it.
Agents do not close a major incident, approve a change, or grant standing access on their own. They read the ticket, pull system state and runbook coverage, draft the resolution or the routing decision — and log every step for the technician who signs off.
Manual setup per multi-step workflow
2 hrs
Engineers on Synera's platform assembled each complex workflow by hand, node by node.
95.4%
Success rate in workflow results
Not an ITSM deployment — A three-agent product advisor guiding customers through print-order configuration — 15 tools working against more than a billion product combinations.
0 hallucinations
across 329+ nurse-validated scenarios
Nurse-triage guidance where a wrong recommendation is a patient-safety event — staged retrieval and validation rather than one model answering in a single pass.
Client results
Proof from production agentic deployments
We have not yet shipped a production agent inside an ITSM organization. These are the closest structural references we have — a multi-agent system evaluating and routing work across 15 tools, multi-step automation running on top of existing systems, and an agent that escalates instead of answering when confidence drops.
Delivery path
From workflow audit to a production agent
TriStorm keeps resolution accuracy and engineering aligned.
Map ticket categories and knowledge base
We audit ticket volume, resolution patterns, and knowledge-base coverage — ranking automation candidates by volume and documentation quality.
- Ticket & KB audit
- System integration map
- Prioritised use case
Build and validate the agent
We implement against real ticket data, with an evaluation suite scored for resolution accuracy before production.
- Working prototype
- Evaluation suite
- Escalation rules
Deploy with monitoring
Production rollout with monitoring and audit logging, plus a structured handoff so your IT team runs the system independently.
- Production deployment
- Audit trail & monitoring
- Operator runbook
Not sure where to start?
A 30-minute call is usually enough to find your highest-value use case
Talk directly to our founders and PhD AI engineers. We will show you real results from 30+ agentic projects and walk through how to apply them to your own ticket-triage and change-management workflows. Every example is something already running in production.
Independence
How we help you stay independent
Your team owns what we build. We work on open-source foundations, and the agent logic, the integrations and the evaluation harness transfer to you at the end of the engagement.
Technological sovereignty
We have delivered systems that run with no connection to a big-tech platform: sovereign AI, engineered in Europe.
Small language models
Smaller models keep token costs predictable in day-to-day operations and let the system run on your own internal or on-premise infrastructure.
Open source
We build on open-source software as contributors and as an official Pydantic implementation partner, so the stack stays inspectable and your team keeps the source.
FAQ
Agentic AI for ITSM, answered
Where does agentic AI fit into IT service management?
In the ticket triage and resolution layer — reading an incident or request, cross-referencing it against your knowledge base and systems, and either resolving it directly or routing it with the right context attached.
How is this different from the workflow rules our ITSM platform already runs?
A workflow rule routes a ticket that matches a fixed pattern. An agent reads the actual ticket content, reasons across your knowledge base and system state, and resolves what it can — handling the variation a fixed rule set cannot.
What ITSM workflows are realistic first projects?
Routine service request fulfillment (access provisioning, password resets), first-line incident triage with knowledge-base grounding, and change-request documentation review.
Can an agent actually resolve a ticket, not just route it?
Yes, for the categories where the resolution path is documented — an agent reads your runbooks and knowledge base and completes standard resolutions directly, escalating anything outside that scope.
Can this integrate with our existing ITSM platform?
Yes, through your existing APIs — we connect to your ticketing and CMDB systems without requiring a platform migration.
Do we own the system after it is built?
Yes. Full ownership of agent logic and integrations — no proprietary runtime lock-in.
Start with one workflow
Map one ticket category worth automating
A 30-minute call identifies ticket volume, knowledge-base coverage, and a realistic path to a working agent.