A cybersecurity startup founded by one of the creators behind GitHub Copilot has secured a $35 million Series C extension backed by Samsung and NVIDIA, adding to a growing stream of investment flowing into artificial intelligence security infrastructure across Silicon Valley.

The company announced the funding on Thursday, saying the capital will be used to accelerate product development, expand enterprise partnerships, and support broader hiring efforts as demand grows for tools designed to secure AI-assisted software development.

The financing extension comes during a period of intense focus on software supply-chain protection and AI security, particularly as large corporations deploy generative AI systems across coding, cloud management, and enterprise automation workflows. Businesses adopting AI-generated code have increasingly faced concerns over hidden vulnerabilities, intellectual property exposure, insecure dependencies, and compliance risks tied to rapidly generated applications.

Industry analysts say investor appetite for cybersecurity companies has remained relatively resilient compared with other venture-backed technology segments, especially for firms positioned around AI governance, developer security, and infrastructure monitoring.

The startup’s connection to GitHub Copilot has attracted particular attention in the technology sector. GitHub Copilot, developed through a collaboration involving GitHub, OpenAI, and Microsoft, helped accelerate mainstream adoption of AI-assisted coding inside enterprises and software engineering teams. The widespread use of coding copilots has also introduced new questions about how organizations audit, validate, and secure machine-generated code.

Security researchers and enterprise technology leaders have warned that AI-generated software can unintentionally reproduce insecure coding practices or introduce vulnerabilities at scale if organizations lack adequate review systems. That concern has created an expanding market for startups focused on automated security testing, code verification, runtime protection, and policy enforcement tied to AI-driven development environments.

Samsung and NVIDIA’s participation in the financing round reflects how major hardware and infrastructure companies are increasingly positioning cybersecurity as a strategic component of the AI ecosystem rather than a standalone software category.

NVIDIA has become one of the central infrastructure providers behind the global AI expansion, supplying graphics processing units and software systems used to train and operate large language models. As AI adoption broadens across industries, securing the infrastructure that powers those systems has become a growing priority for enterprise customers and regulators.

Samsung, meanwhile, has expanded investments tied to enterprise technology, semiconductors, cloud systems, and AI-enabled computing platforms. Cybersecurity has become particularly important for multinational technology companies managing vast hardware ecosystems, connected devices, and cloud-integrated services.

The funding extension also highlights the increasingly close relationship between cybersecurity startups and semiconductor firms. As AI models require larger and more distributed computing systems, security protections are becoming deeply integrated into infrastructure architecture, cloud deployment strategies, and data center operations.

Across Silicon Valley, venture capital firms have continued prioritizing startups capable of addressing risks tied to generative AI deployment. Investors have recently directed funding toward companies focused on AI model security, infrastructure observability, data governance, identity protection, and automated threat detection.

The market momentum follows several years of heightened concern surrounding software supply-chain attacks and cloud-based intrusions. Cybersecurity incidents involving critical software dependencies and enterprise development tools pushed organizations to rethink how applications are built and monitored.

Federal agencies in the United States have also increased pressure on software providers and infrastructure operators to improve cyber resilience standards. Government cybersecurity guidance issued over the past several years has emphasized secure-by-design development practices, software transparency, and stronger protection of critical infrastructure systems.

The rise of generative AI has intensified those conversations. Security professionals warn that attackers are increasingly using AI tools to automate phishing campaigns, accelerate malware development, and identify exploitable weaknesses in enterprise systems. At the same time, defenders are deploying AI to improve threat detection, automate incident response, and strengthen vulnerability management.

The result has been an accelerating technological arms race between offensive and defensive cyber capabilities.

Large enterprises adopting AI coding tools now face mounting pressure from customers, regulators, and internal compliance teams to prove that machine-generated code can be reviewed and deployed safely. That shift has created demand for security platforms that can continuously analyze development workflows, flag vulnerabilities, and monitor AI-assisted coding behavior.

Cybersecurity executives say enterprise customers increasingly want integrated platforms capable of securing both human-written and AI-generated software. Organizations also seek tools that can operate across hybrid cloud environments and support large developer teams using automated coding assistants.

The startup said the new funding would help scale its platform for enterprise deployments and expand support for customers operating complex cloud-native environments. The company also indicated that it plans to invest further in research and engineering as enterprises adopt more autonomous AI systems.

Technology investors have generally remained cautious during the past year amid higher interest rates and slower public-market exits. However, cybersecurity and AI infrastructure have remained among the strongest-performing venture categories due to continued enterprise spending and long-term strategic demand.

Industry data from venture market trackers has shown that cybersecurity funding activity strengthened during recent quarters, particularly for startups linked to AI operations, cloud protection, and enterprise automation security.

The latest financing round could also reinforce acquisition speculation surrounding high-growth cybersecurity firms. Large technology companies have increasingly pursued security startups to strengthen their enterprise offerings and expand AI-related capabilities.

For Silicon Valley, the deal illustrates how AI development and cybersecurity are becoming increasingly inseparable. As companies push generative AI deeper into enterprise operations, the market for securing those systems is expected to expand alongside broader AI infrastructure spending.

Technology executives have repeatedly argued that future enterprise AI adoption will depend not only on computing power and model quality, but also on whether organizations can maintain trust, governance, and security at scale.

The funding extension signals that investors believe cybersecurity firms positioned at the intersection of AI and software development could become critical infrastructure providers in the next phase of enterprise computing.