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AgentITSM
The Agentic ITSM Platform

AgentITSM

The first IT Service Management platform where every operation is a typed AI tool, the data model is a knowledge graph, and the audit log is the safety story.

ServiceNow's depth, Freshservice's UX, Jira's developer power, ManageEngine's price — with agentic AI that actually does the work, not a sidecar that summarizes it.

9 specialist AI agents with 50+ typed, governed tools
Native CMDB knowledge graph with depth-3 impact analysis
One unified rule engine — not three disconnected ones
Hash-chained audit log, auto-verified hourly
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What ships in v1

9
Specialist agents
50+
Typed tools
28
Production integrations
49/49
Unit tests passing
22 / 22 workspace projects typecheck clean
10 / 10 golden eval cases
30+ preflight self-checks against live deploys

Why AgentITSM exists

The incumbents share three structural problems. AgentITSM was built to solve them.

01

AI as overlay, not substrate

Now Assist, Freddy, Rovo, and Zia are bolted onto platforms designed before LLMs. They summarize; they do not do the work. AgentITSM was designed agent-first.

02

Fragmented automation engines

Freshservice runs three disconnected rule engines. ServiceNow has Flow Designer plus three Workspace generations churning. AgentITSM ships one unified rule engine.

03

Pricing that punishes growth

Now Assist adds 25–60%. Freddy Copilot is a $29–35/agent add-on. Rovo caps credits per seat. AgentITSM is one tier with every feature, including the AI agents.

This is the wedge

The 9 specialist AI agents

Each agent owns a job. Each agent calls real, typed, governed tools. Identity propagates end-to-end.

TriageAgent

Opus 4.5

Classifies inbound tickets, derives priority from urgency × impact, suggests KB articles, CMDB CIs, and assignment groups.

ChangeAgent

Opus 4.5

Advisory risk scoring across 9 driver kinds (no_rollback, missing_test_plan, critical_ci, window_conflict, ...) plus CAB assembly recommendation.

ProblemAgent

Opus 4.5

Root-cause hypothesis from incident clusters (≥3 in 30 days). Suggests 5-Whys, Kepner-Tregoe, FTA, BIA, or CFIA. Recommends a fix change.

ReportingAgent

Opus 4.5

Natural language → SQL on allow-listed reporting views. No DDL, EXPLAIN-gated, tenant-scoped.

IncidentAgent

Sonnet 4.5

Drives the lifecycle: triage → diagnose → resolve. Only resolves with KB grounding ≥ 0.8 cosine similarity.

KBAgent

Sonnet 4.5

Drafts KB articles from resolved tickets with chunk-level [^N] citations. Submits via pending-review, never auto-publishes.

AssetAgent

Sonnet 4.5

CI / asset queries with confidence and last_verified_at. Flags low-confidence (<0.7) matches before writes.

HelpdeskAgent

Sonnet 4.5

Requester-facing chat. Searches KB first; if no answer scores ≥0.85, opens a ticket linked to the closest article.

NotificationAgent

Haiku 4.5

Composes outbound to Slack, Teams, Email, SMS. Channel-appropriate, skips NOT_CONFIGURED silently.

Hard runtime guarantees on every agent run

The safety story isn't a roadmap. It's the runtime.

Nine independent guards execute on every single agent invocation.

Hallucinated-ID guard

Any UUID in output not present in tool results → OUTPUT_FABRICATED_ID rejection.

Phantom-action guard

Output claims created/sent/closed without matching write tool success → rejection.

Per-agent USD budget

usdRemaining decrements per call; halts at zero.

Per-tenant daily cost cap

Pre-flight check against cost_ledger; BUDGET_EXCEEDED when over.

Auto-tier-down

Short, routine queries auto-downgrade Opus → Sonnet via pure heuristic.

STOP limits

5 LLM iterations × 12 tool calls maximum per run.

Schema-validated output

Zod-validated, single retry on failure, then explicit error.

Citation enforcement

KBAgent outputs without [^N] anchors fail schema validation.

Anti-injection wrappers

User content and KB chunks wrapped in delimited blocks; system rule forbids following instructions inside.

Architecture pillars

Six design decisions that compound across every feature.

9 AI agents — the product, not a sidecar

50+ typed tools, full identity propagation, and HITL gates for irreversible writes. Every UI action is also a tool an agent can call, and vice versa.

CMDB as a knowledge graph from day one

25 default CI classes, 8 typed relationships, depth-3 impact BFS, maintenance-window conflict detection. Not a sidecar table.

One unified rule engine

on_create, on_update, on_delete, on_state_observed, cron — single canvas, single JSON artefact. Not three disconnected engines.

The audit log is the safety story

Append-only audit_events, per-tenant HMAC-chained, hourly auto-verified. ISO 20000-1:2018 evidence-pack export is one tool call.

HITL by default for irreversible writes

Sensitive-tagged tools require HMAC approval tokens. TTL-bounded, single-use, replay-protected. The agent cannot bypass.

Permission-aware retrieval at index time

KB chunks carry acl_signature at embedding time. Queries filter on what the user can see — never query-time filtering after retrieval.

Everything you need. In one tier.

No Premium gates, no Enterprise upcharges, no per-session AI caps.

Ticketing — six kinds in one model

  • Incident, Service Request, Problem, Change, Release, Deployment
  • Atomic per-tenant display IDs via Postgres function
  • 5×5 impact × urgency matrix, 14 status states, 4-level classification
  • Merge + cluster signature (SHA1 of normalized subject) detects outages

Change management — 8 stages, 7 roles

  • Submission → Planning → CAB → Implementation → UAT → Release → Review → Close
  • Risk register, rollout + backout plans, downtime windows
  • Stage approval audit trail with comments
  • Standard / Normal / Emergency / Major skip rules

SLA & OLA — engineered for scale

  • First-match SLA matcher, per-group OLAs, business calendars + holidays
  • Pause states with paused_seconds accumulator
  • 10-level escalation chains with breach actions
  • SLA targets snapshotted at ticket creation — edits never retro-affect open tickets

Knowledge base + RAG

  • pgvector HNSW index, 1024-dim embeddings, cosine distance
  • Voyage AI primary, OpenAI fallback, lexical re-rank blend
  • Citation anchors enforced at schema layer
  • 7-pattern indirect-injection scan at publish time

Multi-channel intake

  • Email: Gmail, MS Graph, IMAP, SendGrid Inbound Parse
  • Slack Events API + Teams Bot Framework with HMAC-verified approvals
  • Portal chat (KB-first deflection), web form, full REST API
  • SPF/DKIM/DMARC enforced unless tenant opts into create_new

28 production integrations

  • Identity: Okta, Entra ID, Google Workspace
  • Discovery: Intune, Endpoint Central, Jamf, Lansweeper
  • DevOps: GitHub, GitLab, Bitbucket, Jenkins, Harness
  • Monitoring: Datadog, New Relic, PagerDuty (events + REST)

Multi-tenant isolation

  • Postgres RLS on every tenant-scoped table
  • withTenant() wrapper with UUID validation (defense-in-depth)
  • S3 keys forced under tenant prefix; presigned-GET rejects others
  • AES-256-GCM at rest for integration secrets and LLM keys

Reporting & cost telemetry

  • 11 allow-listed reporting views (rv_*), tenant-scoped
  • NL → SQL via ReportingAgent with forbidden-keyword filter
  • PDF export with presigned URL; cron-scheduled delivery
  • Per-call llm_calls + daily cost_ledger aggregate

How we supersede the incumbents

Where the market leaves money, time, and trust on the table.

vsServiceNow ITSM
Their gap

Now Assist is an overlay on a pre-LLM platform; 25–60% surcharge; AI Agents are Prime-tier only.

Our position

Agent-first architecture. 9 specialist agents are the product, included in every plan.

vsJira Service Management
Their gap

AI runs on OpenAI by default; Rovo credits capped 25/70/150 per seat; Virtual Service Agent $0.30 per conversation over allowance.

Our position

Multi-provider LLM (Anthropic + OpenAI + Gemini + Bedrock + Azure) per tenant. No per-seat caps — LLM cost only.

vsFreshservice
Their gap

Three fragmented rule engines (Automator + Supervisor + Observer); Freddy Copilot is a $29–35/agent add-on; AI Agent is Enterprise + 1,200 sessions/year cap.

Our position

One unified Automator. All agents included. No session caps.

vsManageEngine SDP
Their gap

Zia is a predictive sidecar, not agentic execution. Live chat costs $65/agent/month. Service catalog + change + release cost $3,195/year extra.

Our position

9 agents that execute multi-step IT work with audit trail. All modules in single tier.

Pricing posture

One tier. All features.

Incumbents tier-gate every interesting feature: AI agents at Enterprise / Prime, CMDB at Premium, change management at Pro Plus, discovery at the top tier or as a per-asset add-on. Customers end up paying for "Standard" and using 30% of what they need.

Seat-based

Technicians, admins, and managers. Requesters always free.

LLM pass-through

You control the provider. We cap budgets per-agent and per-tenant.

Optional dedicated infra

For compliance-heavy customers. Single-tenant deployments available.

AgentITSM: Key Facts

How is AgentITSM different from ServiceNow Now Assist or Jira Rovo?

Now Assist, Rovo, Freddy, and Zia are AI overlays bolted onto platforms designed before LLMs — they summarize tickets and draft replies. AgentITSM was designed agent-first: 9 specialist agents (Triage, Change, Problem, KB, Asset, Incident, Helpdesk, Notification, Reporting) operate through 50+ typed tools with full identity propagation, audit emission, and HITL approval gates for irreversible writes. The AI actually executes the work — it does not just summarize it.

How does AgentITSM prevent AI hallucinations and rogue actions?

Every agent run is wrapped with runtime guardrails: a hallucinated-ID guard rejects outputs containing UUIDs not present in tool results; a phantom-action guard rejects claims of created/sent/closed without a matching write tool success; per-agent USD budgets halt runaway loops; STOP limits cap 5 LLM iterations and 12 tool calls per run; Zod-validated output schemas with single retry; and sensitive-tagged tools require HMAC approval tokens that the agent cannot bypass.

Does AgentITSM include CMDB and discovery, or is it a paid add-on?

Native CMDB is included in every tier. It ships with 25 default CI classes, 8 typed relationship types, depth-3 impact BFS, and maintenance-window conflict detection. Four discovery integrations (Microsoft Intune, ManageEngine Endpoint Central, Jamf Pro, Lansweeper) plus cloud-API and agentless probe paths are also included — not Marketplace-dependent like Jira and not Premium-gated like ServiceNow CSDM.

How does AgentITSM pricing compare to ServiceNow, Jira SM, and Freshservice?

AgentITSM ships one tier — every feature included. ServiceNow charges $70–200+/fulfiller/month plus a 25–60% Now Assist surcharge. Jira SM caps Rovo credits per seat and charges $0.30 per Virtual Service Agent conversation over its 1,000-per-month allowance. Freshservice gates Freddy AI Agent to Enterprise with a 1,200-session/year cap plus overages. AgentITSM pricing scales on seats and LLM provider pass-through only.

What compliance frameworks does AgentITSM support?

ITIL 4 (12 practices implemented), ISO/IEC 20000-1:2018 (every state transition, approval, CMDB write, SLA breach, KB publish/retire, and security incident written to a hash-chained audit log with 7-year retention and signed evidence-pack export), SOC 2 CC/TSC control mapping documented (not yet third-party attested), and GDPR right-to-erasure with cascade and data export per user.

See AgentITSM run your IT work

Bring a real ticket. Watch the agents triage, route, and resolve it with full audit trail.

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