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Israeli AI startup Conntour raises $7m in seed funding

Conntour, a startup building AI software to analyze surveillance video, has raised US$7 million in seed funding led by General Catalyst, with Y Combinator, SV Angel, and Liquid 2 Ventures also joining.

Its platform lets security teams search livestreamed or recorded camera feeds with natural language prompts, rather than relying on preset detection categories.

Conntour was founded in 2024 by computer vision engineers Matan Goldner and Tomer Kola, and has joined Palantir’s Startup Fellowship program.

The company said the idea grew from the founders’ reserve service and its software is being used in homeland security operations in Singapore.

🔗 Source: Calcalist

🧠 Food for thought

Implications, context, and why it matters.

Funding came fast, though questions remain

  • The $7 million seed round wrapped in 72 hours, according to CEO and co-founder Matan Goldner. That speed suggests strong investor demand 1.
  • Conntour described a Singapore use case without naming customers. TechCrunch reports one customer is Singapore’s Central Narcotics Bureau, a government law-enforcement agency 1.
  • Conntour says the software can run fully on premises on the customer’s own servers, fully on the cloud on a provider’s infrastructure, or in a hybrid setup 1. Goldner also said it can watch up to 50 camera feeds on one consumer graphics processing unit (GPU) such as Nvidia’s RTX 4090 1.
  • The founders cite past work at intelligence agencies. The advisory board includes former CIA Chief Technology Officer (CTO) Bob Flores 2.

AI can turn video into searchable operational data

  • More vendors are trying to make video systems searchable for security and operational workflows 3.
  • The approach can shift surveillance toward prevention, safety, and day-to-day operations. One example is spotting blocked emergency exits or speeding up incident reviews 4.
  • The Tech Buzz compares Conntour with incumbents and newer camera providers. It names Verkada and Rhombus as firms that upgraded hardware and cloud layers while leaving search and query relatively basic, which leaves room for software-first products 3.
  • Natural language interfaces have become more common in enterprise software. That familiarity could help companies get comfortable asking questions of visual data 3.

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