ServiceNow
ITSMBi-directional change records, CMDB reconciliation and approval routing.
- CMDB sync
- Change requests
- Approval routing
- Incident linkage
NewCopilot now writes and validates its own rollback plans
Autonomous infrastructure operations for modern enterprises
Automate discovery, provisioning, patching, upgrades, migrations, compliance, incident response and self-healing across databases, operating systems, middleware, cloud and Kubernetes — from one intelligent platform.
- Deploys inside your network in under a day
- No agents required for discovery
- SOC 2 Type II · ISO 27001 · PCI DSS ready
Dependency topology Complete In flight Queued Attention
Execution waves1,284 / 2,104 instances
EMEA · wave 1
EMEA · wave 2
AMER · wave 1
APAC · wave 1
Running production change at
The operating problem
Estates grew. Operating models did not.
Most enterprises now run more infrastructure than any team can hold in its head — across more platforms, in more places, under more regulation. The work did not get harder. It got wider.
Change moves at the speed of coordination
A quarterly patch cycle is rarely limited by execution time. It is limited by how long it takes to agree a sequence, secure a window and find the person who knows what depends on what.
The map is always out of date
CMDBs describe what was intended. Production describes what happened. The gap between them is where the outages live — and it widens with every undocumented change.
Expertise does not scale linearly
The engineers who can safely upgrade a WebLogic cluster or an Oracle RAC estate are the same ones you need for everything else. Hiring more of them is not the answer available to most organisations.
Measured outcomes
What changes when operations run themselves
Figures below are medians across enterprise deployments with estates above 10,000 instances, measured against each customer’s own pre-deployment baseline.
92%Patch automation coverage reachedFortune 100 bank, from a 34% baseline, across 18,400 instances
41m → 3.2mMean time to restoreHospital network, 340 clinical applications across 62 sites
400Database migrations in eleven weeksTier-1 telecom datacentre exit, delivered four months early
$4.2MAnnual operating cost avoidedSingle customer, measured against their own prior baseline
The platform
Four capabilities, one control plane
Discovery feeds the workflow engine. The policy engine constrains it. The intelligence layer learns from every run and makes the next one safer.
Know the estate
A live model of everything you run
Automation is only as safe as the map it works from. Infrapilot builds and maintains that map itself — continuously, without agents, across every layer of the stack.
- Agentless discoveryNetworks, hypervisors, cloud accounts and clusters scanned on a schedule with no software to roll out first.
- Evidence-backed dependenciesEvery inferred relationship shows the traffic, configuration or query that produced it.
- Impact analysis on demandSelect any node and see precisely which services, teams and SLAs a change would touch.
Live dependency graph
Change with confidence
Workflows that behave like production systems
Scripts fail quietly. Infrapilot workflows are durable, resumable and reversible, with the same guardrails applied whether a change touches one instance or twenty thousand.
- Visual and code, one objectAuthor on the canvas or in YAML. Both views edit the same definition and diff cleanly in Git.
- Rollback as a first-class pathEvery step declares its inverse. Rollback is rehearsed in lower environments, not written during an incident.
- Wave-based executionSequencing derived from real dependencies, with health gates between waves and automatic halt on regression.
Workflow · sql-server-cu-rollupv14YAML in sync
Window opensSchedule trigger
Policy evaluation7 guardrails
Snapshot & verifyBackup chain
Drain trafficLoad balancer
Apply updateWave 1 of 9
Health gate12 assertions
RollbackOn gate failure
main · 3 approvals requiredRollback rehearsed 4h ago
Stay inside the lines
Guardrails that run before anything else does
Control is enforced at execution time, not reviewed afterwards. Policy decides what may run, where, by whom and in which window — and explains every denial.
- Zero standing privilegeCredentials are brokered per execution from your vault and expire when the step completes.
- Continuous control testingRegulatory and internal controls tested on a schedule, with evidence packaged for audit.
- Tamper-evident auditAppend-only, cryptographically chained records of every action, approval and output.
Policy · production-database-changePermitted
policies/production-database-change.yamlsigned · v9
# Evaluated before any step runs
apiVersion: policy.infrapilot.io/v1
kind: ExecutionPolicy
match:
environment: production
assetClass: database
require:
- approvedWindow()
- riskScore(max: 40)
- verifiedBackup(within: 24h)
- preserveQuorum()
- blastRadius(max: 15%)
credentials:
broker: cyberark
ttl: 15m
onDeny: explain- Approved maintenance windowCW-2841 · 02:00–08:00 UTC
- Change risk below threshold18 / 100 (limit 40)
- Backup verified within 24h2,101 of 2,104 · 3 remediated
- Quorum preserved per wave38 availability groups
- Blast radius within limit238 of 2,104 per wave
- Credentials brokered just-in-timeCyberArk · 15 min TTL
- Production freeze not activeFreeze begins in 6 days
Zero standing privilegeDecision written to audit chain
Compound the learning
AI grounded in your estate, not the internet
Models are trained and prompted on your topology, your change history and your outcomes. Every recommendation shows its evidence, and nothing executes without an approval path.
- Risk scored from your historyChange risk modelled on comparable prior changes in your own environment, not an industry average.
- Runbooks drafted, humans approveCopilot writes the procedure and its rollback; an engineer reviews before it can run anywhere.
- Root cause with reasoning shownRanked candidates with the correlating evidence exposed, so engineers can confirm rather than trust.
CopilotGrounded in your estate
RA
Why did checkout latency spike at 02:14, and what should I do about it?
Checkout p99 rose to 4.8s at 02:14:08, against a 1.2s threshold. The most likely cause is stale statistics on four objects in pay-sql-01 following the index rebuild in CHG0048790 at 01:52.
- Query plans regressed on the four objects touched by the rebuild
- Connection pool saturation follows the latency rise by 40s — symptom, not cause
- Network path and consumer lag both flat through the window
Proposed remediation · requires your approval
UPDATE STATISTICS ... WITH FULLSCANEvidenceDependency graph14 nodes on pathChange history3 changes in 6hQuery storepay-sql-01Runbook RB-0412Index maintenance
Cannot execute without an approval pathYour data is never used for model training
See it work
Six real scenarios, running now
These are scripted replays of production workflows — the same phases, gates and evidence an operator sees in the console. Pick one and watch it run.
Self-healing
🎬 Demo Video — Self-HealingINC0048122 · RB-1108 · policy-bounded, unattended
Paused
A SQL Server service stops on a production host. ServiceNow raises the incident, runbook RB-1108 restarts the service and verifies every database came back, and the incident closes itself — with no engineer paged.
PLAYBACK · 1280×720 HDPHASE 1 OF 4: Detect
Tweaks
00:00:08MSSQLSERVER service stopped on SQL-PRD-14
- Detect
- Policy check
- Run RB-1108
- Validate & close
Terminal Event Ledger0 / 13 logs
Engineers paged1—
Time to restore~35 min—
Databases verified——
Incident recordManual—
Coverage
77 technologies under one operating model
Breadth is the point. An automation platform that covers only the modern half of your estate leaves the risky half exactly where it was.
Databases
17 supportedRelational, document, key-value, graph, search and warehouse engines under one lifecycle.
- SQL Server
- Oracle
- PostgreSQL
- MySQL
- MariaDB
- MongoDB
- Redis
- Cassandra
- Couchbase
- Elasticsearch
- OpenSearch
- Neo4j
- Cosmos DB
- Snowflake
- Db2
- SAP HANA
- Sybase ASE
Operating systems
9 supportedCurrent Windows and Linux distributions alongside the legacy Unix estates most tools skip.
- Windows Server
- Linux
- Red Hat Enterprise Linux
- Ubuntu
- CentOS
- SUSE Linux Enterprise
- IBM AIX
- Oracle Solaris
- Unix
Middleware & platforms
17 supportedWeb tiers, application servers, message brokers, containers and virtualisation.
- IIS
- Apache HTTP
- NGINX
- Tomcat
- JBoss EAP
- WildFly
- Oracle WebLogic
- IBM WebSphere
- Apache Kafka
- RabbitMQ
- ActiveMQ
- IBM MQ
- Docker
- Kubernetes
- OpenShift
- VMware vSphere
- Hyper-V
Cloud
5 supportedConsistent governance and lifecycle across every hyperscaler you operate in.
- Microsoft Azure
- Amazon Web Services
- Google Cloud
- Oracle Cloud
- Alibaba Cloud
Infrastructure as code
5 supportedGenerates and consumes the definitions your platform team already maintains.
- Terraform
- OpenTofu
- Bicep
- CloudFormation
- Pulumi
Automation & config
7 supportedRuns alongside existing tooling rather than demanding a rewrite.
- Ansible
- PowerShell
- Python
- Bash
- Chef
- Puppet
- Salt
Observability
9 supportedSignals pulled in for correlation; findings pushed back out as events.
- Dynatrace
- Datadog
- SolarWinds
- Prometheus
- Grafana
- SCOM
- Splunk
- Elastic Stack
- Zabbix
ITSM & delivery
8 supportedChange records, approvals and pipelines stay where your organisation already works.
- ServiceNow
- Jira Service Management
- Freshservice
- ManageEngine
- Azure DevOps
- GitHub
- GitLab
- Jenkins
Integrations
Fits the stack you already operate
Certified connectors for the systems that own your change records, your secrets, your pipelines and your telemetry.
Certified
Ansible
AutomationExisting playbooks execute as workflow steps with full audit capture.
- Playbook execution
- Inventory sync
- Vault integration
Terraform
Infrastructure as codePlan, review and apply within governed change windows.
- Plan preview
- State inspection
- Drift detection
- Module catalogue
Microsoft Azure
CloudSubscription governance, resource lifecycle and Entra ID integration.
- Resource lifecycle
- Policy sync
- Entra ID
- Cost signals
Amazon Web Services
CloudAccount-level automation with Organizations and IAM role assumption.
- Multi-account
- IAM assume-role
- Systems Manager
- Cost signals
GitHub
DeliveryWorkflows, policies and runbooks versioned as code with pull-request review.
- GitOps sync
- PR checks
- Actions triggers
- Secret scanning
Dynatrace
ObservabilityProblem events trigger automation; topology enriches the dependency graph.
- Problem events
- Topology enrichment
- Metric queries
Datadog
ObservabilityMonitors initiate remediation and receive execution events in return.
- Monitor webhooks
- Metric queries
- Event stream
CyberArk
SecretsCredentials brokered per execution — nothing stored by the platform.
- Just-in-time credentials
- Session isolation
- Rotation events
HashiCorp Vault
SecretsDynamic secrets issued at step start and revoked at step completion.
- Dynamic secrets
- Transit encryption
- Lease revocation
Customers
Estates that stopped waiting on change windows
Banking, insurance, healthcare, telecommunications and manufacturing — organisations where an unplanned outage is a regulatory event, not an inconvenience.
We were spending eleven weeks a quarter on database patching and still finishing late. The first automated cycle took six days, and the second took four. The difference was not speed of execution — it was that nobody had to negotiate a sequence any more.
11 weeks → 6 daysQuarterly patch cycle
The dependency graph paid for the platform on its own. We had four services nobody could account for sitting in the path of our signalling stack. Two of them were single points of failure.
71%Reduction in MTTR
Our regulator asked for evidence of control over privileged database access. Previously that was a six-week exercise across four teams. We exported it in an afternoon, and the auditors accepted it without a follow-up request.
6 weeks → 1 dayAudit evidence preparation
Common questions
Answers before the first call
The three questions that come up in almost every evaluation.
How long does it take to see value from Infrapilot?
Discovery typically returns a complete estate inventory within 48 hours of deployment, without agents. Most customers run their first governed automated change in week two of a proof of concept.
Does Infrapilot replace our existing automation tooling?
No. Infrapilot orchestrates the tooling you already run — Ansible, PowerShell, Terraform, Python — and adds the dependency awareness, policy enforcement, approval routing and audit record that scripts alone do not provide.
Where does Infrapilot run and where does our data live?
Infrapilot deploys as a self-hosted control plane inside your network, or as a dedicated single-tenant cloud instance in the region you choose. Credentials are never stored by the platform; they are brokered per execution from your existing vault.
Get started
See it run against your own estate
A proof of concept takes two weeks. We deploy inside your network, discover a scoped part of your estate, and run a real change end to end — with your team holding the approvals.