Stream Security Launches StreamForce: AI Agents Built on a Live Model of Production Environments
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Stream Security today announced the general availability of StreamForce, its AI agent orchestration platform built natively on Stream’s live environment model. StreamForce is the first platform that lets security teams build, deploy, and run AI agents that already understand their production environment, without assembling infrastructure, normalizing data, or pre-defining use cases.
Background
Security teams have always operated with an incomplete picture of the environment they are protecting. Not because the tools were bad. Because no tool was built to maintain a live, accurate model of an environment that changes continuously. Cloud, on-prem, SaaS, identity, ephemeral assets, and even AI agents in production: the environment shifts every minute. The SOC was always defending without a real map.
AI didn’t create that problem. It exposed it. Speed is not the gap. If AI operates on an incomplete or outdated picture of the environment, faster answers to the wrong question do not help. The ceiling is architectural.
Addressing a Gap in the AI Agent Market
Security teams exploring AI agents today face a choice between two bad options.
The first is build-in-house. Connect an LLM to the environment, ingest raw logs, spend months building infrastructure, and then figure out how to feed context to the model in a form it can actually reason about.
The second is a packaged product. A vendor ships pre-built workflows for a fixed set of use cases. The threat model does not fit the template. Teams wait for the next release.
StreamForce is neither. Stream spent three years building a normalized data fabric for AI: a live model of the environment that updates the moment anything changes, so agents act on it directly without burning tokens or hallucinating reality from raw logs.
“It is like asking Waymo to figure out what the city looks like from the windshield alone, instead of simply handing it a real-time GPS. For three years, we built the map that updates as the city changes around it. StreamForce is what happens when you hand AI agents ground truth instead of asking them to reason their way to it from logs.”
Or Shoshani, CEO, Stream Security
How StreamForce Works
Security operations runs on two things: knowledge of the environment and the ability to act on it. Most AI platforms have invested heavily in the second and assumed someone else solved the first.
Stream’s environment model covers cloud, on-prem, SaaS, identity, ephemeral assets, and even AI agents in production. It updates in near-real time. StreamForce agents inherit that model entirely. They know what the environment looks like, what has changed, what is at risk, and what the attack paths are before a single workflow runs.
The result: security teams can build an AI workflow in natural language, deploy it against a live production environment, and get results that reflect current reality. Not a reconstruction from yesterday’s logs. Not a vendor’s approximation of a use case they anticipated.
Already in production
Michael Young, Cybersecurity Director at Hunt Consolidated, piloted StreamForce during early access.
“Our organization has embraced AI workflows broadly, but like many, we remain cautious about accuracy, unintended actions, and gaps in coverage. One of the reasons we moved forward with StreamForce is that Stream already has a strong, trusted model of our cloud environment. That foundation gives us confidence to extend into AI-driven workflows. Traditional SOAR approaches can be difficult to architect, maintain, and scale effectively, and they often slow progress rather than accelerate it. StreamForce gives lean security teams a way to quickly validate defenses against active attack techniques, without building and maintaining complex integrations. It is helping us move faster on security initiatives that have historically been delayed due to complexity.”
Michael Young, Cybersecurity Director, Hunt Consolidated
Availability
StreamForce is generally available today at stream.security/use-cases/force.
About Stream Security
Stream is the AI-native platform built to fight AI-enabled attacks. It autonomously prevents, detects, hunts, and remediates exposures and threats across production at machine speed - driving risk toward zero. It replaces the fragmented stack of scanners, runtime agents, exposure tools and playbooks with one live model of production.Defending Production needs a new approach: Stream is the only Autonomous Production Defense Platform that works across your entire production estate. It runs on a patented CloudTwin®, a high-fidelity security data harmonization layer that models Cloud, SaaS, identity, runtime, AI, network, perimeter, on-prem, security controls, and the behavior running on top of them into one live model of production: real-time, fully correlated, continuously updating. Not a snapshot. And it does not stop at boundaries - the boundaries that fragment every other tool are the same boundaries an attacker moves across. Inside CloudTwin they are one system.
