Solutions · IT OperationsComing soon
No silent failures.
Not help-desk automation. An AI employee that owns the problem until it's resolved.
- Continuously watches the environment, detects failures
- Investigates issues, coordinates the fix
- Keeps systems documented and helps you stay audit-ready
Work in motion · the loop this AI employee owns
Operating
Division of labour
What the AI employee does. What your team keeps.
- Infrastructure and application health, database health, schema drift, missed jobs, stale processes
- Repository and CI/CD awareness: failed deployments, broken pipelines, configuration inconsistency
- Integration, credential and connection failures — including the health of other AI employees
- Investigation with a written root cause; remediation coordination via runbooks and tickets; low-risk fixes where authorised
- System inventory, architecture docs, runbooks, environment maps, recovery procedures — kept current
- Audit evidence: configurations, access reviews, change records, control tracking, incident history
- Approving changes to production and anything authority reserves
- Risk decisions and vendor relationships
- Sign-off on audit submissions — the AI employee prepares the evidence, a person signs
Audit · compliance · documentation
Continuous operational evidence and compliance support.
AxiaForce does not make you compliant. It keeps the evidence current and the gaps visible — so the audit is a review, not a scramble.
Inventory systems and integrations, track configurations, capture evidence, identify missing controls, detect drift, surface gaps, maintain audit trails.
SOC 2 readiness, HIPAA-related technical control support where applicable, access reviews, change tracking, policy and configuration evidence.
System inventory, architecture, runbooks, integration docs, environment maps, recovery and operating procedures, incident and change records — maintained by the AI employee that's connected to the environment itself.
Speed to value
Connect. Configure. Deploy.
Days, not quarters. Common systems connect in a day; the AI employee runs monitored before it runs alone.
- Day 1
Connect GitHub / repositories, infrastructure and cloud with read scopes. The AI employee starts reading the estate the same day.
- Day 1
Connect logs, observability and databases.
- Day 2
Connect ticketing and communication; define authority: what it may fix, what it must ask.
- Day 2
Deploy monitored: first inventory, first documentation draft, first detections.
- Week 1
Incident loop live; documentation baseline and audit evidence started.
Fit
A good fit if…
- Failures get noticed by users, or by the founder at 11pm, before they get noticed by monitoring
- Documentation is out of date the week after it's written
- You have an audit coming and the evidence lives in twelve places
- You'd like your IT employee to understand your stack faster than a new hire finishes onboarding
Straight answers
The questions we get first.
- Does this mean unrestricted access to production?
- No. Read-only by default; every write is an authority decision you make per action. Changes to production are gated unless you deliberately open them.
- Does it replace our MSP or engineers?
- It watches, investigates, documents and coordinates — continuously. Your engineers and MSP get a root cause and a runbook instead of a page at 3am.
- Can it make us SOC 2 compliant?
- No product can. It keeps continuous operational evidence and shows the gaps; your auditor and your people make the compliance call.
Want this AI employee early?
Tell us what the job looks like in your company. Early-access customers shape the role template, the KPIs and the authority defaults.