We build the AI systems that turn vulnerability detection into bulk remediation — multimodal LLM agents, fast-track execution, and zero-impact guardrails for OT/IoT environments.
Your platform identifies millions of vulnerabilities, but remediation is manual and unscalable — incumbent tools rely on slow, device-specific "recipes."
A "Learn-and-Use" agentic architecture: a Researcher Agent uses multimodal LLMs and browser automation to create validated playbooks once, then a "Fast-Track" engine executes in bulk. (Armis)
Frontier models are too expensive to run on every action.
Dual-path execution: expensive LLM agents learn the flow once, then efficient non-LLM Playwright scripts execute the task at scale. Costs collapse without sacrificing accuracy. (Armis)
Your AI agent lives in the cloud but needs to control devices on private IP ranges (192.168.x.x).
Integration with TCP brokers as transparent forwarders to reach non-routable on-prem assets. (Armis Broker pattern)
One bad action takes a critical OT device offline. The system can’t crash the device, ever.
"Zero-Impact" guardrails: pre-flight connectivity checks, "Page Looks Good" UI validation, hard rollback paths. (Armis)
Agentic systems that turn the "scale problem" of vulnerability remediation into something a small team can actually own.
The pattern we proved with Armis: autonomous agents that research devices once, then execute remediation playbooks in bulk — safely, cheaply, and at scale.
Anchor reference: the Armis pattern — 1-month fixed-price Assessment, then MVP squad on T&M (1 EM + 1 SME + 2 AI Engineers).
A high-impact strike team that diagnoses, architects, and ships. We bring the ML engineers, infra, and domain expertise needed to deliver measurable lift within weeks.
A dedicated research partnership where we co-develop proprietary models alongside your team — from initial hypothesis through production deployment.
A controlled experimentation environment for validating strategies before they touch production. Test against realistic system dynamics and quantify impact upfront.
No pitch decks, no generic demos — just a technical conversation about your data and your goals.