Total amount raised
$44 Millions
Latest funding date
Location
Robust Intelligence has successfully raised significant funding over multiple rounds, culminating in 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 the intricacies of Robust Intelligence's fundraising journey and the investors backing this innovative platform.
What Is Robust Intelligence?
Founded in 2019, Robust Intelligence is based in San Francisco, California. The company focuses on AI security, providing automated solutions to protect enterprises from AI vulnerabilities.
Robust Intelligence was founded by Alexander Rilee, Eric Balkanski, Kojin Oshiba, and Yaron Singer. The team has grown to include 51-100 employees, all dedicated to ensuring the safety and reliability of AI applications.
The company's platform offers end-to-end solutions, including AI Validation and AI Protection, to detect and mitigate threats in AI models. This comprehensive approach helps businesses deploy AI securely and effectively.
How Much Funding Has Robust Intelligence Raised?
- Seed Round
- Amount Raised: $3M
- Date: March 2019
- Lead Investors: Engineering Capital, Sequoia Capital
- Valuation at Round: Not publicly disclosed
- Motivation Behind the Round: To develop the initial version of their AI security platform and validate the market need.
- Series A
- Amount Raised: $11M
- Date: February 2020
- Lead Investors: Sequoia Capital
- Valuation at Round: Not publicly disclosed
- Motivation Behind the Round: To expand the team and enhance the platform's capabilities.
- Series B
- Amount Raised: $30M
- Date: December 2021
- Lead Investors: Tiger Global Management
- Valuation at Round: Not publicly disclosed
- Motivation Behind the Round: To scale sales operations and invest in product and engineering efforts.
Total Amount Raised: $44M. Current Valuation: Not publicly disclosed.
Key Investors
- Tiger Global Management
- Details: Tiger Global Management is a leading global investment firm that focuses on private and public companies in the internet, software, consumer, and financial technology sectors. They have a strong track record of backing high-growth companies.
- Investment Focus Areas: Internet, software, consumer, financial technology
- Notable Investments: Facebook, LinkedIn, Spotify
- Sequoia Capital
- Details: Sequoia Capital is a venture capital firm that partners with founders to build enduring companies. They have a long history of investing in early-stage startups and helping them grow into market leaders.
- Investment Focus Areas: Technology, healthcare, consumer, financial services
- Notable Investments: Apple, Google, PayPal
- Engineering Capital
- Details: Engineering Capital invests in early-stage technology companies, particularly those with a strong technical foundation. They focus on companies that are solving complex technical problems.
- Investment Focus Areas: Early-stage technology companies, software, AI
- Notable Investments: SignalFx, Kentik, Confluent
- Harpoon Venture Capital
- Details: Harpoon Venture Capital is a venture capital firm that invests in early-stage technology companies. They are known for supporting innovative startups with high growth potential.
- Investment Focus Areas: Technology startups, innovative solutions
- Notable Investments: Not specified
What's Next for Robust Intelligence?
As AI continues to integrate into various industries, Robust Intelligence stands at the forefront with its unique solution to stress test AI models. The Robust Intelligence Model Engine (RIME) acts as an AI firewall, continuously testing models for potential failures and data drift. This capability is crucial as businesses increasingly rely on AI, presenting a significant growth opportunity for the company.
With the successful $30 million Series B round, Robust Intelligence is well-positioned to scale its operations and enhance its product offerings. Future fundraising rounds are likely as the company aims to expand its market reach and solidify its position in the AI reliability space. However, challenges such as rapid advancements in AI technology and competition from other AI reliability tools could pose hurdles along the way.
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