Intelligence-Led Operations

AiOps at infinite scale.

Per-Operation Agents — research, decide, resolve every workflow. Patented dual-mode governance. Omnichannel with configurable agent behaviour. OnPrem and Air-Gapped deployments. Human-in-the-Loop on the Autonomy Dial you control. 24/7even when your team is asleep.

01 Observe 02 Recommend 03 Assisted 04 Autonomous 05 Evolve
The thesis

Operations stacks were built to watch. We built one to act.

Most operations teams aren't being augmented — they're being buried. Ten thousand alerts a day, a hundred tickets, and humans investigating the five they had time for.

Autonowmy changes the unit of work. Instead of a person reading dashboards, a Per-Operation Agent works every incident proactively — researching, deciding, and resolving — and your team governs the trust dial.

You go from one engineer reactively covering 200 systems to 200 agents working every single one, across NOC, SRE, IT Ops, and platform teams simultaneously.

The platform · 33 services

Modules contribute. The platform composes.

Every service ships a typed ModuleKit — its metrics, datasets, streams, actions, and entities. Agents, widgets, and workflows bind to those contracts. No point-to-point glue.

33 modules · 6 clusters · One typed contract

Works with what you already run

No connector rewrites. Read your stack as-is.

Agents read from your existing observability, ticketing, runbook, and chat tools — write back through the same paths your team already trusts.

DD
Datadog
Observability
PD
PagerDuty
On-call
SN
ServiceNow
ITSM
SL
Slack
Chat
MT
Teams
Chat
JR
Jira
Tickets
SP
Splunk
Logs
NR
New Relic
APM
GR
Grafana
Dashboards
OG
Opsgenie
On-call
GH
GitHub
Runbooks
K8
Kubernetes
Runtime

40+ integrations live. Native MCP support — explore the platform →

The governance model

Autonomy on your terms.

Per agent, per action, per risk level — five steps from zero-risk observation to closed-loop self-healing. You set the dial. Your board signs off on the dial. The agent earns the next click.

01 / Step
Observe
Zero Risk

Watches your environment silently. Builds the baseline. No write access. Zero blast radius.

02 / Step
Recommend
AI Proposes

Suggests actions with risk scores. Your team approves every one. One click. Full control.

03 / Step
Assisted
AI Initiates

Low-risk actions run automatically. High-risk gets approval gates. You set the boundary.

04 / Step
Autonomous
AI Executes

Self-healing at machine speed. Trust earned, not assumed. You got here because it proved itself.

05 / Step
Evolve
Closed Loop

Every resolution feeds the next decision. Runbooks write themselves from proven actions.

Five steps. One dial. The board approves the dial — the platform earns the next click.

Built for every role in operations

An agent for the work, a model for the people who run it.

CIO / CTO

Chief Information Officer

An operations organization that isn't limited by headcount. Execution that survives turnover and gets smarter every quarter.

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SRE / Platform

Site Reliability

An agent on every system, every shift. Proactively triaging, prepping context, and running runbooks — so your on-call sleeps.

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NOC / IT Ops

NOC & IT Ops

From 10,000 alerts to 5 signals. Agents that monitor topology, prioritize incidents, and resolve before your team opens a ticket.

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Internal AI Teams

Internal AI Teams

Build on a continuously-updated graph of your environment. Ship new agents in days, not months — one platform, not twelve point tools.

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Use cases from the field.

RAN AiOps Telecom NOC
From 8,000 daily alerts across 12,400 cells to 23 risk-scored signals each shift. The agent consolidates duplicate cell-drift signal, auto-remediates the obvious ones, and only pages humans for genuinely ambiguous cases. RACH success up 3.2% inside the first quarter.
RA
RAN Anomaly Resolution
Autonomous mode · sector-scoped
SCM Intelligence Consumer Goods
Stockouts predicted 14 days ahead across 12 distribution centers. POs auto-drafted for human approval. $2.4M in working capital rebalanced in the first month — and zero stockout incidents on the SKUs the agent flagged.
SP
Stockout Prevention
Assisted mode · multi-DC
Compliance AiOps BFSI
The risk committee needed full traceability before approving any automated action. Observe-mode for 30 days produced every reasoning step, tool call, and decision log — visible to InfoSec from day one. The conversation went from "if" to "how fast" after the first audit review.
AT
Audit-Trail Compliance
Observe mode · regulator-ready
Ordering AiOps National Retail
1,247 orders/day processed with 98.2% EDI auto-clearance. Exception ticket volume dropped 60% in the first quarter. Customer SLA hit rate moved from 91% to 97.4% — same headcount on the order desk.
EO
EDI Exception Resolution
Autonomous mode · 800 stores
Invoice AiOps Shared Services
$4.1M in invoices reconciled against POs in a single overnight cycle. 92 invoices cleared 3-way match without human touch. 14 variances flagged with reasoning and a draft journal entry attached — closing cycle compressed from 6 days to 2.
IM
Invoice Match & Variance
Assisted mode · AP shared services
Common questions

What every operations leader asks first.

What if the agent does the wrong thing?

That's what the autonomy dial is for. Every new agent ships in Observe mode — zero write access, zero blast radius. Your team watches it think for 30 days before approving the first action. From there, every step up the dial is earned by demonstrated behavior on the step below, per agent, per action class, per risk score.

If an agent ever proposes something outside its boundary, the platform refuses to execute — period. Every reasoning step, tool call, and approval is logged and replayable.

How does this work in regulated environments?

Single-tenant deployment is available. Data stays in your region. SOC 2 Type II is in progress (Q2 2026); ISO 27001 targeted Q3 2026. DPDP and GDPR aligned out of the box. We publish a sub-processor list and offer a standard DPA at procurement-time.

For BFSI, telecom, and healthcare customers we ship with an audit-trail mode that satisfies most regulator queries with one SQL view.

How long until our first agent is in production?

Two weeks to first agent in Observe. One month to first action under approval. The reason it's that fast is that we don't ask you to rewrite your connectors — agents read your existing Datadog, PagerDuty, ServiceNow, Slack, Splunk, and runbook tooling as-is.

Our forward-deployed engineers embed with your team for the first 30 days. You don't get handed a platform and told to figure it out.

Does Autonowmy replace my observability or ITSM stack?

No — it sits above it. Autonowmy is the intelligence layer that reads from your stack and writes back through the same paths your team already trusts. Datadog stays Datadog. ServiceNow stays ServiceNow. The agent just works the queue.

What models do the agents use? Can we bring our own?

Default is a multi-model setup tuned for operations reasoning (a mix of frontier and specialized models, with routing based on action class). Customers in regulated industries can run with their own model endpoints — Azure OpenAI, Bedrock, or self-hosted — and we'll match SLA against your endpoint.

How is pricing structured?

Per-agent, per autonomy-step, with volume tiers. Observe-mode pilots are free for the first 30 days. Most customers start at one production agent and scale based on resolved-operations-per-quarter rather than seats. Talk to sales for an enterprise quote.

Enterprise-ready from day one

Transforming operations from human-led firefighting to Intelligence-Led Operations.

Technology Platform

Knowledge graph

Per-Operation Agents

Built on your knowledge graph, your runbooks, your SLAs. Reasoning that survives turnover and improves every quarter.

Proven Enterprise Scale

SOC 2 ISO GDPR SINGLE-TENANT · IN-REGION Compliance posture

Built for regulated environments

SOC 2 in progress · ISO 27001 target Q3 2026 · DPDP & GDPR aligned · single-tenant deployment available · data residency in-region. Read the trust page →

Deployment & Partnership

2 weeks to first agent FDE EMBED YOUR TEAM D0 W2 M1 M3 Deployment timeline

Forward-deployed engineers

Agent product managers and engineers embed with your team for the first 30 days. Two weeks to first agent in observe. One month to first action.

Agents working every operation, even while your on-call sleeps.

30-minute walkthrough · No commitment · First agent in observe mode by week two