Helsing unveils Clarity, an AI platform that prepares targets for weapons systems
German defense tech company Helsing presented Clarity in Berlin on Wednesday, calling it an "agentic intelligence platform." According to the company's press release, the software processes all data a military unit can access: sensor feeds, open-source intelligence, written reports and systems already in use. Hundreds of specialized AI agents link these sources, identify military forces, facilities and positions, and prepare information on adversary assets for human review. Clarity then packages the data for the appropriate weapons system.
Helsing says the agents are trained on real operational data, synthetic AI-generated data and simulated environments. A shared military ontology and evidence base lets them work in parallel and deploy analytical tools. The company also calls the platform "AI-native," not built on legacy architectures.
Sovereignty is a central pitch. Helsing says Clarity runs on the customer's own infrastructure, its models and interfaces were developed in Europe, and data and operations stay under the armed forces' sole control. The platform follows the Modular Open Systems Approach, implements NATO standards and can connect to effectors from any manufacturer.
On oversight, the decision to strike is supposed to stay with a human who selects targets and must authorize every handoff to a weapons system. Helsing says a target is only recommended when independent sources agree and the assessment can be made with high confidence, and every decision is documented with the name of the person responsible.
With Clarity, Helsing steps into a market led by Palantir, whose Maven system is embedded in Pentagon and NATO workflows and has been refined through years of operational use. Helsing is one of the few European vendors that can point to experience from the war in Ukraine, where it supplies drones. It did not say whether Clarity is already running with any customer. Germany's Bundeswehr plans to introduce AI-powered systems starting next year.
The Decoder then lays out how comparable systems have played out. In the Iran war, the US military is reportedly using Palantir's Maven with Anthropic's Claude to suggest hundreds of targets, prioritize them and recommend ordnance. According to the Wall Street Journal, the US struck about 1,000 targets in the first 24 hours, and within days the number topped 3,000. The Journal also reports that military officials warn of an attitude described internally as "The computer said to do this."
In Gaza, according to investigations by +972 Magazine and Local Call, Israel's Lavender system for a time flagged up to 37,000 Palestinians as potential targets. Human review often lasted only about "20 seconds" per target, mainly to verify whether the person was male. A separate system called "Where's Daddy?" tracked flagged individuals to their family homes, which were then often struck at night.
Combining sources does not prevent hallucinations either. According to CNN, in an incident from spring 2026 the US military nearly boarded a Chinese ship because a chatbot falsely claimed in an intelligence report that it was carrying nuclear weapons program components. The chatbot had combined open and classified data and misidentified the cargo. Armed troops were preparing to board and aircraft were already in the air when the error was caught, only shortly before the operation. There were no uniform standards for verifying AI-generated information, and younger analysts in particular trusted the tools uncritically. "AI allows you to get to a bad idea faster," one source said.
Key facts
- Helsing presented Clarity in Berlin on Wednesday: an agent-based platform in which hundreds of specialized AI agents turn sensor feeds, open-source intelligence and reports into target information, then package it for the appropriate weapons system.
- Helsing says a human must authorize every handoff to a weapons system, a target is recommended only when independent sources agree with high confidence, and each decision is documented with the responsible person's name.
- Clarity is pitched on European sovereignty: it runs on the customer's own infrastructure, with models and interfaces developed in Europe, and it enters a market led by Palantir's Maven. Helsing did not say whether any customer already runs it.
- The Decoder cites other systems as warnings: in Gaza, Lavender flagged up to 37,000 people and human review often took about 20 seconds per target; in Iran, the US reportedly struck about 1,000 targets in 24 hours using Maven with Claude.
- In spring 2026 a chatbot's false intelligence report nearly led the US military to board a Chinese ship, according to CNN; the error was caught shortly before the operation.
Why it matters
Clarity is a European entrant in AI-assisted targeting, a market the source says is led by Palantir, whose Maven is embedded in Pentagon and NATO workflows. Helsing stresses European control and mandatory human authorization as its differentiators. The Decoder's point is that experience with similar systems shows where such promises can break down: review times shrink to seconds and AI errors can lead to dangerous wrong calls. Germany's Bundeswehr plans to introduce AI-powered systems starting next year.
Who it affects
Armed forces that would buy or run such a platform, with the Bundeswehr named only as planning AI-powered systems from next year, not as a Clarity customer. It also affects the human operators who would be named on each decision, and the people on the receiving end of targeting, as the Gaza and Iran examples in the article illustrate. Rival vendors, Palantir above all, face a new European competitor.
How to use it
This is a military product, not something readers can adopt. No customer for Clarity is named, and there is no price, contract value or delivery date. Helsing did not say whether the platform is already running with any customer. According to the company, it connects to effectors from any manufacturer, follows the Modular Open Systems Approach and implements NATO standards.
How solid is it
The description of Clarity rests on Helsing's own press release and statements, so the oversight and accuracy claims are the company's, not independently verified. The Iran figures come from the Wall Street Journal, the Gaza figures from +972 Magazine and Local Call, and the Chinese ship incident from CNN; The Decoder relays them, and the Iran use of Maven with Claude is described as reported. The unnamed source behind the closing quote is not identified.
Risks and caveats
The Decoder does not say Clarity itself has caused errors; the Iran, Gaza and China examples concern other systems (Maven, Lavender and an unnamed chatbot), and Helsing is not said to be involved in those operations. The human-in-the-loop promise is worded as the decision being "supposed to" stay with a person. The cited cases show the risks the article raises: human review that shrinks to about 20 seconds, an internal attitude of "The computer said to do this," no uniform standards for verifying AI-generated information, and analysts, especially younger ones, trusting tools uncritically.
“AI allows you to get to a bad idea faster”
— One unnamed source, cited in The Decoder's account of the CNN report