NinjaOne Lands $500 M in Outsized Series C
Austin-based endpoint management company NinjaOne has secured $500 million in Series C extension funding, catapulting its valuation to $5 billion, according to an announcement made earlier this week.
The funding round was led by ICONIQ Growth and CapitalG, Alphabet’s independent investment fund, along with participation from several other private investors. These new funds area an extension of the company’s $231 million Series C, raised a year ago, at a $1.9 billion valuation. That round was led by ICONIQ Growth
NinjaOne serves over 24,000 customers including tech giants Nvidia and Lyft as well as major brands like Porsche and HelloFresh. The company plans to channel the new capital toward autonomous endpoint management technologies and expanded IT capabilities.
Part of the funding will support NinjaOne‘s pending acquisition of Australian SaaS backup and data protection company Dropsuite. The $252 million deal was announced in a month ago, and is expected to close in the first half of 2025. The acquisition aims to address growing concerns around data protection as employees increasingly use multiple devices and SaaS applications. According to Gartner research cited in the acquisition announcement, 75% of enterprises are expected to prioritize backup of SaaS applications as a critical requirement by 2028, compared to just 15% in 2024. The combined technologies will extend data protection from physical devices to SaaS applications, offering automated setup and recovery features.
The overall market of managed and automated security is massive but has its incumbents. NinjaOne is showing impressive growth in a market dominated by the likes of CrowdStrike, SentinelOne, and Tanium.
Semgrep Secures $100 Million Series D
Semgrep, provider of an application security platform, has secured $100 million in Series D funding led by Menlo Ventures, with participation from existing investors Felicis Ventures, Harpoon Ventures, Lightspeed Venture Partners, Redpoint Ventures, and Sequoia Capital. This latest round brings the company’s total funding to $204 million.
The investment comes as organizations face mounting pressure to secure increasingly complex codebases while maintaining rapid development cycles. Current code scanners are often criticized for being noisy, ineffective, and detrimental to developer productivity.
Semgrep plans to use the funding to further develop what it calls autonomous AppSec technology – solutions that can automatically identify, fix, and communicate security issues in code without constant human intervention. This vision addresses the challenge of security teams being overwhelmed by the volume of code they need to secure.
The company’s approach emphasizes extensibility, allowing security teams to build custom guardrails rather than relying on vendor black boxes. Semgrep focuses on three key areas: delivering market-leading signal-to-noise ratio, maintaining high developer productivity, and enabling effective AppSec programs at affordable prices.
Recently, Semgrep launched Semgrep Assistant, which uses AI to learn an organization’s software development lifecycle and automatically finds, triages, prioritizes, and fixes critical security issues. Their platform combines traditional static analysis with large language model capabilities, maintaining rule-based determinism while adding contextual awareness. The company reports identifying true positives with a 96% security researcher agreement rate.
The company plans to use the new capital to hire AI and program analysis talent, increase awareness of their offerings beyond security practitioners, and expand their go-to-market team with veterans from organizations like Hashicorp, Elasticsearch, and Snyk.
Semgrep offers both a free Community Edition supporting approximately 40 languages and an enterprise AppSec Platform that provides Static Application Security Testing (SAST), Software Composition Analysis (SCA), and Secrets management capabilities.
Mimic Raises $50 Million Series A to Combat Ransomware Threats
Mimic, an enterprise ransomware defense company headquartered in Palo Alto, has secured $50 million in Series A funding led by GV (Google Ventures) and Menlo Ventures, with participation from existing investors Ballistic Ventures, Team8, Wing Ventures, and Shield Capital.
Founded in 2023, Mimic has developed a SaaS platform that detects ransomware attacks in fractions of a second, addressing the critical challenge that most ransomware attacks occur within just 90 seconds, leaving security teams with virtually no response time.
The funding announcement comes alongside several significant developments for the company. Kevin Mandia, founder of Mandiant and current Co-founder and General Partner at Ballistic Ventures, has joined Mimic’s Board of Directors. Mandia led Mandiant as CEO until 2024, building it into a cybersecurity powerhouse that was acquired by Google in 2022 and serves over 200 Fortune 500 companies and major government organizations worldwide.
The company has also unveiled the Mimic Signal Generator, a new capability that allows customers to safely simulate ransomware impacts within their networks. This tool enables organizations to test and validate their security posture without the risks associated with handling actual malware.
Mimic positions itself as the “last line of defense against ransomware,” offering security teams the ability to detect attacks early, deflect them before damage occurs, and recover within seconds rather than the days or weeks typically required following a ransomware incident.
Arize AI Secures $70 Million in Series C for AI Observability
Arize AI, a provider of tools to evaluate, understand and optimize LLM performance, has raised $70 million in Series C funding. The round was led by Adams Street Partners, with participation from M12, Microsoft’s Venture Fund, SineWave Ventures, OMERS Ventures, Datadog, PagerDuty, Industry Ventures, and Archerman Capital. Existing investors Foundation Capital, Battery Ventures, TCV, and Swift Ventures also joined the round.
Founded in 2020 and headquartered in Berkeley, California, Arize has quickly established itself as an essential backbone for AI systems at major enterprises including Booking.com, Condé Nast, Duolingo, Hyatt, PepsiCo, Priceline, TripAdvisor, Uber, and Wayfair.
The funding comes as businesses dramatically increase AI spending, with enterprises planning to invest between $50 million and $250 million in generative AI in 2025. Despite this surge in investment, AI models—particularly large language models (LLMs)—continue to face significant challenges when deployed in real-world applications.
Arize has identified a critical blind spot in the industry through its OpenEvals research initiative, demonstrating that LLMs struggle to reliably assess the correctness of synthetic datasets compared to non-synthetic data. This finding raises serious concerns as more AI models are trained and optimized using synthetic data generated by other AI models rather than real-world sources.
The company offers two main products: Arize AX, its enterprise platform, and Arize Phoenix, an open-source offering that has gained significant traction with over two million monthly downloads. These tools enable engineering teams to test, troubleshoot, and correct AI systems before failures can impact customers—particularly crucial as enterprises implement semi-autonomous multi-agent systems, voice assistants, and consumer-facing AI applications.
Arize has also strengthened its partnership with Microsoft, recently launching deeper integrations with Azure AI Studio and the Azure AI Foundry portal, SDK, and CLI. This collaboration is further reinforced by M12’s participation in the funding round.
The company plans to use the new capital to accelerate development of its platform and expand its capabilities, including its recently launched audio evaluation tools for voice assistants—the first of their kind in the market.
As enterprises rush to scale generative AI applications, Arize positions itself as the solution to a critical industry challenge: ensuring AI works reliably in production environments. The company’s growth reflects the increasing recognition that observability and evaluation are essential components of enterprise-ready AI systems in an era where AI failures can have significant real-world consequences.
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