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How Much Did Robust Intelligence Raise? Headquarters, Funding & Key Investors

Robust Intelligence, founded in 2019 and based in San Francisco, has raised $44 million across three funding rounds before its $400 million acquisition by Cisco. The company’s AI security platform continuously tests and protects models from failures, data drift, and vulnerabilities. With a team of 51–100 employees, Robust Intelligence serves enterprises looking to deploy AI safely and reliably. Its innovative approach ensures operational and reputational risk mitigation while addressing the rapidly growing global demand for robust AI governance and security solutions.

    Robust Intelligence has raised $44 million across multiple funding rounds before its acquisition by Cisco for $400 million. The company offers an automated platform designed to protect enterprises from AI security vulnerabilities.

    Keep reading to explore Robust Intelligence’s fundraising journey, key investors, and what’s ahead for this AI-focused platform.

    What Is Robust Intelligence and What Does It Do?

    Founded in 2019 by Alexander Rilee, Eric Balkanski, Kojin Oshiba, and Yaron Singer, Robust Intelligence is headquartered in San Francisco, California. The company offers an AI security platform that validates and protects AI models from potential failures, data drift, and security vulnerabilities. Its core products include AI Validation, which ensures models operate reliably and accurately, and AI Protection, which monitors and mitigates threats to deployed AI systems.

    With a team of 51–100 employees, Robust Intelligence helps enterprises deploy AI securely while reducing operational and reputational risks.

    How Much Funding Has Robust Intelligence Raised?

    1. Seed Round
      • Amount Raised: $3M
      • Date: March 2019
      • Lead Investors: Engineering Capital, Sequoia Capital
      • Motivation: Develop the initial AI security platform and validate market demand.
    2. Series A
      • Amount Raised: $11M
      • Date: February 2020
      • Lead Investors: Sequoia Capital
      • Motivation: Expand the team and enhance platform capabilities.
    3. Series B
      • Amount Raised: $30M
      • Date: December 2021
      • Lead Investors: Tiger Global Management
      • Motivation: Scale sales operations and invest in product and engineering efforts.

    Total Funding Raised: $44M

    Latest Valuation: Not publicly disclosed

    Acquisition: Acquired by Cisco for $400M

    Key Investors

    1. Tiger Global Management
      • Details: Global investment firm backing private and public companies with high growth potential.
      • Investment Focus Areas: Internet, software, consumer, financial technology
      • Notable Investments: Facebook, LinkedIn, Spotify
    2. Sequoia Capital
      • Details: Venture capital firm partnering with founders to build enduring companies.
      • Investment Focus Areas: Technology, healthcare, consumer, financial services
      • Notable Investments: Apple, Google, PayPal
    3. Engineering Capital
      • Details: Early-stage investor focusing on technically strong startups solving complex problems.
      • Investment Focus Areas: Early-stage technology, software, AI
      • Notable Investments: SignalFx, Kentik, Confluent
    4. Harpoon Venture Capital
      • Details: VC firm investing in early-stage technology companies with high growth potential.
      • Investment Focus Areas: Technology startups, innovative solutions

    Where Is Robust Intelligence’s Headquarters?

    Robust Intelligence is headquartered in Palo Alto, California, offering proximity to Silicon Valley’s AI ecosystem, enterprise clients, and venture capital networks.

    What’s Next for Robust Intelligence?

    Robust Intelligence continues to lead in AI reliability with its Robust Intelligence Model Engine (RIME), which acts as a continuous “AI firewall” to test models for potential failures and data drift. The company’s future priorities include scaling operations and product offerings, expanding its market reach globally, and navigating competition amid rapid AI advancements.

    Key challenges involve keeping pace with evolving AI technologies and differentiating its solutions from other emerging AI reliability platforms.

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