Agentic Business Automation
Autonomous, goal-directed AI systems that reason, plan, use external tools and execute multi-step workflows with human-in-the-loop oversight.
An Agentic Engineering Company
Autonomous systems that do the work. Governed so you can trust them.
AegisOps builds goal-directed AI agents that reason, plan, use your tools and finish multi-step work, with people in control where judgment matters.
- Human-in-the-loop
- Sandboxed
- Private models
- Full audit trail
Trigger
Plan
Act
Verify
Human review
What we build
Three ideas behind everything we engineer
Cognitive Loops
Robust execution patterns that reason, target, adapt and run complex tasks end to end: plan, act, observe, critique, retry, escalate.
Autonomous Infrastructure
Moving workflows from legacy configurations to proactive, self-managing agent fleets that triage, patch and document themselves.
Solutions
Where agents go to work
One loop and governance platform, applied to three domains.
Financial services
Invoice reconciliation, fraud detection and procure-to-pay exception handling.
IT & customer support
Self-service desks, incident triage and automated diagnostics.
Human resources
Candidate screening, onboarding journeys and case management.
Healthcare & supply chain
Claims processing, prior authorization and disruption mitigation.
Autonomous bug patching
A ticket opens; the agent branches, reproduces the failure, fixes it, tests it and produces a patch.
Feature branching
User stories and Jira issues become working code with unit tests.
Build-error remediation
Failing pipelines are diagnosed from logs and fixed with a hotfix pull request.
Intelligent PR audits
Reviews enforce architecture and style, log their reasoning and hand off to a senior engineer.
Vulnerability remediation
Continuous scans for leaked secrets and vulnerable dependencies, with automatic fixes.
Patch lifecycle
Prioritize, configure and safely verify upgrades against production findings.
Authorized red teaming
Continuous, scoped penetration testing and attacker simulation to validate defenses.
Compliance automation
Access audits, data classification and evidence trails for regulatory reviews.
How it works
From ticket to reviewed pull request
Every task runs through a cognitive loop inside an isolated sandbox. A person approves the result before anything ships.
- TriggerA commit, bug ticket or compliance request.
- TriageA router opens a tracked state machine and a sandboxed workspace.
- LoopCoder and tester agents iterate until every check passes.
- ReviewA clean PR and full diagnostics go to a human supervisor.
trigger ticket BUG-412 opened: "checkout total off by one cent"
triage sandbox ready, repo cloned (no network egress)
coder reproduced failure in test_rounding.py
coder patch applied to pricing/round.py
tester 2 tests failed, reading logs
coder adjusted tie-breaking, re-running suite
tester 148 passed, 0 failed
gate lint, types, security scan passed
review PR #903 opened, awaiting human approval
Trust by design
Autonomy you can audit
Trust is an engineering property. These are the rules we build to.
01PlatformGitHub / GitLab, webhooks, event streams
02OrchestrationLangGraph state machines and multi-agent teams
03Isolated executionEphemeral Docker / Kubernetes sandboxes, no intranet access
04IntelligencePrivate models, self-hosted or in your own cloud tenant
Human in the loop
Agents act freely in low-risk scopes and escalate high-risk decisions to people.
Sandboxed execution
Work happens in ephemeral, isolated workspaces, never directly on production.
Private intelligence
Your code and data stay inside your boundary on private models.
Explainable and logged
Every step records its reasoning, inputs, outputs and approvals.
Deterministic skeleton
State machines govern the flow; models fill in the steps.
Model-agnostic
No lock-in to a single provider.
Get started
Start with a pilot
Tell us about one workflow or repository you would like to hand to an agent. A typical pilot runs 4 to 6 weeks and ends with a measured result.
- One workflow, one measurable outcome
- Runs in your environment, on private models
- Humans approve every change