Your agents, live.
ROI in the first quarter.
30%Cut in IT costs
80%Of repetitive tasks automated
<6 weeksTo deploy — zero data leaves your environment
For the Office of the CIO · SOC 2 Type II · ISO 27001
Autonomous triage. Self-healing runbooks. Change-risk scoring the CAB actually trusts.
Agentic AI above your ITSM record system (ServiceNow, Freshservice, Jira SM, BMC Helix), deployed inside your VPC, with HITL gates on every high-risk action and a full audit trail written back to the ticket. No rip-and-replace. Live in 90 days.
The Challenge
Triage
Resolution
Governance
How It Works
The agentic loop, governed. Every action lands as an audit-bearing record in the ITSM platform. High-risk steps stay behind an HITL gate in the change record.
Agent watches APM, logs, synthetic monitors, and infrastructure alerts. Correlates across sources to open a pre-triaged ticket when a real incident is forming, not after a user calls.
Reads the requester, the affected service from the CMDB, and open incidents on the same service. Routes to the right queue with a defensible priority the first time.
Executes the approved runbook for recurring failure modes with minimal human interaction. High-risk steps stay behind a human-in-the-loop gate in the ITSM change record.
Drafts the knowledge-base article from the ticket, the chat transcript, and the runbook trace. Senior analyst reviews and publishes. The KB stops rotting.
Five Use Cases Landing First
Concentrated, proven patterns. Each one sits above the existing ITSM record system and delivers measurable outcomes inside a quarter.
Correlate telemetry across monitoring sources and open a pre-triaged ticket before the first user call. Reduces time-to-detection and removes the first hour of human log reading.
Incidents open pre-triaged, not pre-ignored
Read the ticket, the CMDB, and the business-criticality of the affected service. Route to the right queue with a defensible priority that matches actual impact, not stated urgency.
Misrouted tickets fall, SLA compliance rises
For recurring failure modes (service restart, cache flush, cert rotation, disk cleanup), execute the approved runbook end to end with HITL gates on high-risk steps.
MTTR drops, analyst hours redeploy to strategic work
Every normal and emergency change record gets a draft risk assessment built from historical outcomes, recent incidents, and blast-radius analysis from the CMDB.
CAB reviews structured risk, not unstructured data
When an incident resolves, the agent drafts the KB article from the ticket, the chat transcript, and the runbook trace. A senior analyst reviews and publishes.
Institutional memory compounds instead of decays
Every capability below is configuration, not custom development. The agentic runtime inherits the no-code surface the rest of the lowtouch.ai platform runs on.
The agent runtime deploys inside your VPC or on-prem. Incident content, CMDB data, and telemetry never leave your environment; no external LLM calls in the default posture.
Every high-risk action is an approval inside the ITSM change record. The agent proposes; a named human approves; the audit trail captures the full chain.
Every prompt, tool call, action, and approval is logged to the ITSM platform and forwarded to your SIEM. Designed for SOC 2 Type II and ISO 27001 readiness.
Separate agents for triage, runbook execution, and change review. Each carries only the permissions its role requires. No monolithic super-agent, no blanket write access.
Accuracy is tracked per incident category. Categories that fall below target automatically pause and route to human review until retuned. No silent drift.
No rip-and-replace. The agent layer sits above ServiceNow, Freshservice, Jira SM, and BMC Helix through their native APIs, attributed to a dedicated service account.
Directional ranges from published research on mature AIOps and agentic ITSM deployments. Outcomes compound over six to twelve months of iteration.
No rip-and-replace. Native API connections to the ITSM record system, the monitoring surface, and the communication tools your teams already use.
ServiceNow
ITSM record system
Freshservice
ITSM record system
Jira Service Management
ITSM record system
BMC Helix
ITSM record system
Datadog
APM + telemetry
New Relic
APM + telemetry
Dynatrace
APM + telemetry
Splunk
Log + SIEM
Elastic
Log + observability
Grafana
Metrics + dashboards
PagerDuty
Incident orchestration
Slack
HITL approvals
Microsoft Teams
HITL approvals
CMDB (native)
Service-to-criticality map
AWS VPC
Private cloud deployment
Azure VNet
Private cloud deployment
On-premises
Air-gapped deployment
The playbook, the architectural white paper, and the stack context.
Playbook
The full playbook. Five use cases, integration pattern, outcomes, and a 90-day roadmap.
White Paper
Architectural deep-dive on agentic release management: blue-green deployments, feature flags, and patch workflows.
Context
The stack progression behind agentic ITSM, and why AIOps alone does not close the loop.
Use Cases
Related SRE use-case surface: predictive detection, anomaly correlation, automated RCA.
Questions CIOs, IT directors, and ITSM platform owners typically ask before starting a pilot.
Yes. ServiceNow's Flow Designer, IntegrationHub, and REST APIs expose every hook an external agentic runtime needs to read incidents, write comments, update fields, trigger approvals, and call outbound tools. The governed pattern is to keep ServiceNow as the system of record and let the agent layer act through its APIs, with every agent action attributed to a dedicated service account and logged to the audit trail. The same pattern applies to Freshservice, Jira Service Management, and BMC Helix.
AIOps is primarily a detection and correlation layer: it reads telemetry, surfaces anomalies, and proposes probable causes. Agentic AI is an action layer: it can execute approved remediation, update the ticket, route approvals, and close the loop. Most mature programs use both. AIOps narrows the signal; the agent acts on it. Buying one without the other leaves half the value on the table.
No. The agentic runtime deploys inside your VPC or on-prem environment. Incident content, CMDB data, and telemetry are processed by a locally-deployed private LLM; zero data is sent to external APIs in the default posture. This is foundational architecture, not optional configuration. Regulated industries (BFSI, healthcare, public sector) land on this posture for data residency and audit reasons.
A recurring service restart or certificate rotation with the agent running behind a human-in-the-loop gate. The runbook already exists, the failure mode is well understood, and the reliability bar is achievable inside a 60-day window. From there, narrowing the HITL gate to high-risk steps is a policy change, not a re-platform, and the same runtime scales to the next category.
Days 1-30: audit top incident categories by volume and analyst hours, pick two with existing runbooks, freeze the measurement baseline. Days 31-60: sandbox deployment with every remediation behind an HITL gate, full audit trail captured. Days 61-90: graduate categories that hit the reliability target (typically 95%+ on proposed actions) to narrowed HITL and let the agent execute the rest with minimal human interaction. Most enterprises graduate one or two categories in the first quarter and queue three to five for the next.
Structurally, not prompt-side. Untrusted inputs (ticket descriptions, inbound emails, third-party API responses) are sandboxed and validated before they reach the reasoning step. Tool scopes are narrowed so even a successful injection cannot cross agent boundaries (the triage agent cannot execute runbooks, the runbook agent cannot approve changes). Full audit trails make post-hoc forensics possible. Prompt injection is a real attack surface, and the defense is architectural.
