Build your own swarm of security agents in one factory, on the model you choose, in your own cloud if you want. They work every risk until it’s closed, with people approving the calls that matter.
Cloud, code, identity, email and endpoint tools now find risk in seconds. Findings arrive faster than any team can close them.
Closing still runs on people. Who owns it? Is it risky here? When can the fix ship? Where’s the evidence? One handoff, one wait at a time.
Into breaches someone else finds first. Into analysts drowning in follow-ups. Into audit exceptions nobody tracked.
Each tool’s agent adds findings to the same drain. Scripts bolted onto tools became sprawl nobody maintained. Agents will too.
One agent factory for SOC, GRC, AppSec, IGA, IT, network and cloud, federated across the tools you already run, with no data lake to build.
They find the owner, contain the risk, draft the fix and re-test it, and follow up when an owner goes quiet.
Routine steps run inside guardrails. Risky ones wait for a named approver in Slack or Teams. Every decision is on the record.
Brief the AI builder like a colleague. Optimus drafts a workflow you can read step by step, or a harness, a team of agents working toward a goal.
Every step is visible before it runs, and each agent uses the model that suits its job, from the provider you trust.
Agents, schedules and shared memory around one goal, with approvals in Slack or Teams before anything risky.
Workflows for the runbooks you know, harnesses for open-ended work, on the same tools, memory, guardrails and registers.
Before it acts, an agent must know who owns the app, who has to approve the change, what else breaks and how much risk that team accepts. autobotAI keeps this live and governed, and every agent works from it.
Every agent action updates a live register, by team, with a named owner.
Optimus
checkout-apiPCI scopeFixes the wrong service, asks the wrong person, breaks payments at month end.
Owner found, PCI approval path followed, blast radius checked, approved skill used.
Autonomy is earned one action at a time. Each action gets a level by its risk: advise only, ask first, act within limits you set, or impossible by design. Your policy sets the level, never the AI.
Self-host the whole factory in your own AWS account. Your data stays inside it.
High-impact actions wait for a named approver in Slack or Teams.
Who asked, who approved, what changed, kept for every run.
Scoped, time-boxed, reversible permissions, set per action by its risk.
Siemens Energy, NTT DATA, Persistent and SimplifyEm run their security operations on autobotAI, alongside a community of teams building their own agents on it every day.
Energy
IT services
IT services
PropTech
AI software
PaymentsAgents find the owner of every misconfiguration across AWS, Azure and GCP, send the risk and the fix for approval, and close each one with evidence.
Read the storyautobotAI allowed us to streamline and automate our runbooks: faster detection, quicker remediation and stronger operational outcomes.
Ashwath Kumar, Head of SecurityMost security stacks ship every log to a central store before anyone can ask a question. autobotAI agents work with the SIEM you already run, and query every other tool directly, at the moment of action, keeping only the evidence a decision needs.
Cloud
describe_bucket(1 resource · owner tag
Identityowner_of(manager · groups
Security toolsalerts(4 alerts · 1 case
Code & CIblame(1 commit · 1 owner
ITSMopen_changes(1 change window
Chatask(1 reply · approved
Infrastructurepods(6 pods · 1 exposedany API · CLI · MCPbuilt in daysdescribe_bucket(1 resource · owner tagEach team builds the agents its own work needs, on the same foundation.
Alerts triaged, phishing purged, advisories swept. You see only what needs you.
See the use cases GRCControl evidence collected all year; every exception chased to a named owner.
See the use cases AppSecA critical flaw becomes a pull request, protected by a WAF rule until it merges.
See the use cases IGAAdmin for hours, not forever. Unused rights removed every week.
See the use cases IT OpsJoiners, leavers and routine requests handled end to end.
See the use cases NetworkExposed ports closed with their owner, on rules that expire.
See the use cases CloudMisconfigurations fixed by their owners and re-scanned.
See the use cases Red teamAutonomous pen-testing, worked to a merged and re-tested fix.
See the use casesThree numbers for a first read. The full assessment lets you change every assumption.
Assumes agents carry half of the hands-on work end to end, and people still review a share of it. Change both in the full assessment.
See your own risks worked end to end in a 30-minute demo, on your stack, in your cloud if you prefer.
