Skan AI has raised $63 million in funding to expand its enterprise artificial intelligence platform. The round was led by Cathay Innovation and Dell Technologies Capital, with participation from Citi Ventures, Bloomberg Beta, State Farm Ventures, and Wipro Ventures.
The San Jose-based company was founded by co-founder and CEO Avinash Mishra. It develops technologies designed to capture how work is performed within corporate systems. The platform then uses this context to help businesses identify opportunities and implement AI agents.
The new funding comes as businesses transition from experimental AI use to practical implementation. Many companies have faced difficulties in turning AI agents into reliable enterprise systems. Skan AI aims to solve this problem through a continuous contextual layer.
Skan AI asserts that traditional enterprise data does not provide a complete picture of how work is completed. While documentation and system logs can show outcomes, they often fail to record the decisions made, exceptions, and workflow sequences.
The company's platform is designed to bridge this gap through three interconnected products. Skan AI Blueprint helps identify potential AI opportunities across various enterprise systems. Skan AI Intelligence allows leaders to analyze workflows and manage operational efficiency.
Furthermore, Skan AI agents use this context to autonomously perform tasks. These agents are built based on observed business processes and tested in real operational environments, while human oversight and auditability remain part of the deployment process.
The company reports that its platform runs on NVIDIA AI Enterprise and NVIDIA NIM microservices. This infrastructure supports the company's focus on deploying enterprise-grade AI and allows organizations to operate AI in controlled environments.
Skan AI has demonstrated rapid growth alongside the increased adoption of enterprise AI. The company states that revenue has grown by over 300% year-over-year, and the average net customer retention yield reached 150%.
The company's growth is also driven by expanding its client base. Skan AI currently collaborates with seven out of the ten largest US banks and serves major organizations in banking, insurance, and other regulated industries.
The platform focuses on the operational context underlying business processes, including workflow sequences and decision-making paths. It is also capable of identifying technological gaps and potential automation opportunities.
Skan AI claims that its approach has already delivered cumulative value exceeding $500 million to clients. These figures are provided by the company itself, and further momentum will be important as deployments expand.
Cathay Innovation noted that the context of corporate work can become a foundational layer for enterprise AI. Dell Technologies Capital also emphasized the importance of understanding how work is actually performed. Both investors view Skan AI as infrastructure for migrating AI into measurable business operations.
The funds raised will be used to expand Skan AI's platform and operations. Additionally, the company plans to deepen its AI capabilities in complex enterprise environments, maintaining a focus on organizations whose workflows span multiple systems and applications.
Skan AI's strategy reflects a broader shift in enterprise AI. Businesses are increasingly seeking autonomous systems rather than just individual assistants. However, reliable automation requires not only powerful models but also precise information about processes and business rules, as well as an understanding of exceptions and operational decisions. Skan AI positions its context graph as the layer that provides this information.
Convex has raised $57 million in a Series B funding round. These funds are planned to be used to scale the development of its backend platform, which is specifically designed for artificial intelligence. The financing was led by Insight Partners, with participation from Etna Labs and all previous investors, including a16z and Spark Capital.
Thanks to this Series B round, Convex's total raised capital has reached $110.5 million. The company stated that it intends to use this money to improve its core platform, enhance tools for agentic development, and increase its staff in its San Francisco office.
Founded in 2021 by former Dropbox infrastructure engineers, Convex offers developers a fully integrated backend platform. This platform combines databases, functions, workflows, search, synchronization, authentication, and file storage into a single solution built for software development.
The fundraising comes amid the trend towards AI-powered coding and autonomous development tools. Convex believes that developers need infrastructure capable of handling the increasing complexity of applications while maintaining a high level of reliability.
The company posits that traditional backend infrastructure struggles to support the growing use of AI coding agents. According to the company, AI-generated applications based on standard databases can subtly introduce data errors that only manifest after deployment.
Internal testing revealed that 90% of AI-built applications running on traditional databases encountered data corruption in real-world operating conditions. In comparison, applications developed on the Convex platform passed the same tests without any failures.
Convex's backend includes built-in ACID transactions, end-to-end type checking, real-time subscriptions, and TypeScript support. These features reduce the need for manual integration of multiple services for developers and increase application reliability. Furthermore, Convex packages search capabilities, workflow automation, authentication, file storage, and retrieval-augmented generation functions, allowing AI applications to be enriched with organization-specific knowledge.
The platform has gained significant traction among developers building AI-based software. Convex currently supports nearly two million applications created by about 500,000 developers worldwide. The company also reported over 1.2 million weekly downloads from npm.
Convex's clients include OpenAI, Tripadvisor, Solana, Zapier, and Reducto. These organizations use Convex to simplify backend development while ensuring scalable, reliable performance for their applications.
Insight Partners noted that the growing adoption of AI coding assistants has exposed weaknesses in traditional software infrastructure. The investment firm believes that Convex provides developers with a more robust foundation where backend components function cohesively without the need for complex configuration.
Convex plans to use the new funding to accelerate product innovations amidst the transformation of software engineering influenced by AI. The company will direct funds toward creating new tools that simplify application development for both developers and AI agents that build software.
The company will continue to provide highly reliable backend products supporting increasingly complex AI-based applications globally. Convex is convinced that stable backend infrastructure is becoming critically important as artificial intelligence generates large volumes of application code.
Instead of combining disparate components, Convex offers a single unified platform, which effectively reduces complexity and prevents software bugs. The raised funds will strengthen Convex's engineering team and significantly expand its global developer ecosystem and platform capabilities. With fresh capital and a growing customer base, Convex aims to solidify its position in the evolving AI development infrastructure market, making the creation of reliable software faster and easier for both human developers and AI agents.
The implementation of enterprise software has encountered a significant hurdle. Companies are acquiring advanced artificial intelligence tools, but integrating these tools into legacy systems remains a slow, costly, and complex task. To solve this problem, the company June AI has raised $20 million in seed funding.
Deploying enterprise software is a labor-intensive and complicated process. Globally, organizations invest hundreds of billions of dollars annually in configuring, integrating, and supporting their core systems. Businesses aim to integrate models like GPT, but the presence of years of technical debt complicates the operation of such systems. There are very few seamless connections between older platforms, such as SAP, Oracle, Workday, and Salesforce, and modern cloud data infrastructure.
June AI directly addresses this implementation gap. Instead of forcing companies to hire expensive external consulting teams, the startup uses AI agents to optimize the integration process. The platform functions as an automated digital bridge, analyzing enterprise workflows and automating repetitive configuration tasks, which significantly reduces the time required for enterprise software setup.
The process at June AI begins with deep system analysis and process mining. The platform studies existing database logs to determine how business workflows are actually executed within an organization. After mapping these hidden patterns, the system identifies operational bottlenecks and automates structural changes in the software. This technology works natively in core data environments such as Databricks and Snowflake.
By mapping inter-system relationships, June AI ensures that updates in one department do not disrupt subsequent processes. The platform allows engineers working directly in the system and system integration teams to deploy enterprise AI agents with less friction and lower overall costs. The global systems integration market is expected to reach over a trillion dollars in the coming decade. As companies increase their investments in AI, automated integration will become an integral part of corporate infrastructure. Advanced foundational AI models are of little value if enterprises cannot connect them to their real-time operational data.
The founding team brought deep experience in enterprise software to solve this problem. June AI is the brainchild of CEO Ephrat Rapoport, CTO Idan Zittat, President Barak Goldstein, and Chief Architect Ohad Hen. The founders previously developed the conversational intelligence platform Bonobo AI, which Salesforce acquired in 2019. Over the past five years, they led key product and engineering teams within Salesforce, gaining firsthand experience with challenges in the enterprise sector.
They noticed that purchasing AI software is relatively simple, but implementing it into disparate user workflows is extremely difficult. June AI was created to replace manual professional services with automated software workflows, providing faster value realization for modern enterprise solution buyers. With the $20 million in new capital raised and support from leading industry figures, June AI is well-positioned to innovate in automated deployment. By eliminating technical debt and accelerating integrations, the company helps businesses move from simple AI demonstrations to fully functional automated operations.
Horizon3, a San Francisco-based company specializing in artificial intelligence-driven cybersecurity, has secured $250 million in Series E funding. The funds will be used to further expand its platform internationally across the globe. Following this round, the company's valuation exceeded $2 billion.
This valuation is more than triple the approximately $600 million achieved during the previous funding round a year ago. The investment is intended to support Horizon3's native cybersecurity expansion into international corporate markets and client operational activities.
The funding was led by NightDragon and NEA, with participation from existing and new global strategic investors. The company plans to accelerate innovation and strengthen proactive cybersecurity capabilities for enterprises facing increasingly complex, AI-driven threats.
The raised capital will be utilized for global sales development, marketing expansion, market growth, and initiatives to develop autonomous cybersecurity technologies worldwide. Horizon3 intends to increase its presence in Europe and enter the Singaporean and Australian markets through strategic international expansion.
The company will increase R&D investments to enhance its NodeZero platform and AI-based security agents. These autonomous agents are capable of effectively and automatically detecting and remediating vulnerabilities within enterprise IT systems.
The investment will also go towards strengthening the proactive AI security platform and accelerating the innovation process. This financing follows growing enterprise demand for protection against AI-driven cyber threats and evolving regulatory compliance requirements.
Snehal Antani and Anthony Pillitiere, former colleagues from JSOC, founded Horizon3 with the goal of automating penetration testing via NodeZero. NodeZero continuously attacks client networks using self-guided penetration testing technology to proactively detect cybersecurity vulnerabilities.
Unlike annual audits, the platform safely tests live production environments using fully automated continuous security testing capabilities. This helps enterprises identify attack vectors, prioritize security weaknesses, and quickly and efficiently implement remediation measures.
The company reported conducting over 310,000 security tests in client production environments globally. Unlike traditional testers, Horizon3 assesses the entire enterprise infrastructure while production systems continue to operate uninterrupted.
The platform also incorporates intelligent honeypots that help organizations detect active attackers targeting enterprise systems in real time. Currently, the platform is used by over 7,000 enterprises across sectors such as banking, healthcare, public administration, and Fortune 10 companies worldwide.
The rapid adoption of AI has changed the approach to how security issues arise. For instance, an attacker with the right automated approach can quickly identify weaknesses and initiate complex attacks faster than manual methods, which reinforces the automation of security assessment.
Horizon3 reported a year-over-year recurring revenue growth of approximately 120%, noting that its annual recurring revenue approached $100 million last year. The company serves between 7,200 and 7,300 clients globally, including managed service providers and some of the world's largest corporations.
The new funding will also support the development of AI training loops, allowing AI defense systems to continuously improve by analyzing new attack methodologies. This should support enterprises' efforts to move from simple vulnerability awareness to the ability to automatically mitigate the most severe security threats.
Given that new cyber threats emerge at 'machine speed' and with high sophistication, the company asserts that AI-based security testing is indispensable for enterprises seeking to protect critical assets and confidential data.
