CodeRabbit has successfully raised $143 million in a Series C funding round, valuing the company at $1.5 billion. Atomico and Smash Capital participated as co-leads in this round. New investors include BMW i Ventures, Datadog, Hirtle Callaghan, and SineWave Ventures. Existing investors, such as CRV, Scale Venture Partners, and Flex Capital, also supported the deal.
This funding was secured less than a year after CodeRabbit raised $60 million. The company reports that its revenue has increased more than fivefold compared to the previous year. Currently, CodeRabbit performs over two million code checks weekly for 17,000 clients, including companies like Adyen, BMW, Indeed, JFrog, NVIDIA, and Trivago.
The capital raised will be used to accelerate the company's international expansion and increase research and product development expenses. CodeRabbit plans to invest over $10 million to support open-source projects, which will allow it to maintain free access to AI review and agent features for accompanying projects.
AI coding tools enable engineering teams to create software at unprecedented speeds, as developers can generate code, create pull requests, and troubleshoot much faster. Nevertheless, every change introduced still requires testing, verification, and proper management before going into operation.
CodeRabbit asserts that this shift is transforming software development management practices in organizations. Traditional task trackers were designed to work with planned work and developer-driven execution. However, AI-based development allows code to appear before teams achieve full consensus.
This makes the pull request an increasingly critical control point. CodeRabbit CEO, Hardjot Gill, noted: 'Writing code has become dramatically easier. Verifying its quality remains complex.' He emphasized that changes created by AI still require independent verification before being released into the production environment.
CodeRabbit's goal is to provide this level of control for software created by both humans and agents. The platform analyzes changes using repository context, organizational standards, and testing evidence. The system also indicates the scope of impact and architectural dependencies that require further attention.
Along with the latest funding announcement, CodeRabbit introduced Agentic Change Management. This system expands AI review capabilities, including prioritization, explanation, and continuous code security monitoring.
Its purpose is to help engineering teams understand exactly which changes require attention. The CodeRabbit Triage tool ranks incoming pull requests based on value, urgency, and risk. It also considers reviewer dependencies, readiness, and suitability before routing the task. Lower-risk changes can pass through automated workflows, while complex changes are directed to human reviewers. CodeRabbit Change Stack provides deeper explanations of software changes and their potential impact by analyzing contracts, domain behavior, integrations, tests, and migrations between repositories.
CodeRabbit is also expanding its presence in security with an AI-powered product. This system continuously scans production code for vulnerabilities and emerging risks. It verifies detected issues against code evidence before recommending a fix via pull requests. This approach targets vulnerabilities that traditional rule-based tools might miss, including authorization bypasses, insecure object references, and business logic errors. The company believes that continuous monitoring will become increasingly significant as AI generates more software.
The latest funding will also support CodeRabbit's international expansion strategy. The company recently opened an office in London to serve corporate clients in Europe and plans further expansion in Europe, Japan, and other Asian markets. Luca Eisensteken, a partner at Atomico, will join the CodeRabbit board of directors. He stated that the infrastructure for independent governance will become increasingly important for AI-generated software. CodeRabbit believes that its model-agnostic approach will help organizations maintain software quality as AI adoption accelerates.
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.
Delightree, a company that develops an artificial intelligence-based operating system for industries with multiple points of sale (such as franchises), has raised $25 million in funding. These funds will be used to accelerate the growth of the company's team in engineering, product development, and general operations.
The investment round was led by Accel, with support from existing investors Emergent, Timber Grove Ventures, and Innovius. The Denver-based company plans to use the new capital influx to expand its AI platform and enter new vertical markets, including restaurants, fitness, wellness, retail, healthcare, and home services.
The Delightree platform integrates processes such as training, compliance, communication, audits, and new location launches. This ensures greater consistency between the central team's work across all on-site operations and uniform execution of tasks throughout the network of businesses.
Franchise businesses are actively implementing artificial intelligence to assist in various aspects of their operations, many of which rely on it to consolidate disparate processes such as training, communication, compliance, and reporting.
Since its launch just over two years ago, the Delightree platform has demonstrated rapid demand growth globally. The company reported that revenue has increased nearly twentyfold during this period, indicating a high level of product adoption by customers and overall growth.
Currently, the company's software is used in over 6,000 locations across the United States. Delightree's clients include solidcore, Dunn Brothers Coffee, JETSET, Five Star Franchising, MOOYAH Burgers, and Beem Light Sauna.
The platform replaces numerous individual systems with a single operational layer. Businesses use it to manage employee training, operational standards, communications, checks, regulatory compliance, and new site openings.
Delightree will continue to strengthen its capabilities in artificial intelligence for business automation platforms and operational management on a global scale. Future AI assistants will be able to automatically identify issues, assign tasks, track progress, and suggest improvements in operations everywhere.
The new funding will support further investments in product innovation and artificial intelligence. Delightree intends to develop new features that reduce operational complexity for growing franchise businesses. The company believes that AI can help operators open new locations faster while reducing administrative burden.
According to Delightree, clients using the platform can open locations two to three months earlier than when using traditional methods, meaning a reduction in launch times of more than 25%. Furthermore, businesses report that on-site employees free up up to 30% of their working time thanks to workflow automation and centralized operations.
Co-founder Madhulika Mukherji stated that the company's long-term goal is to provide small franchise operators access to complex operational technologies that were previously only available to large corporate chains.
The company sees significant growth opportunities in industries where millions of people work on-site. Its platform is designed to simplify the management of multi-branch businesses while increasing operational transparency.
Delightree is convinced that artificial intelligence can transform growth without the need to add additional layers of management in distributed companies. Artificial intelligence automates back-office operations while maintaining uniformity of operational standards across all business locations.
Delightree aims to strengthen partnerships with franchise brands striving for standardized operations in fast-growing global networks. The platform combines AI-based automation with workflows, significantly reducing management complexity and improving location consistency.
The company plans to use the funds to add AI-powered operational analytics for franchise owners, managers, and on-site employees. Delightree's goal is to become the operating system for multi-location enterprises implementing faster, smarter, and more efficient automation methods globally.
Xsight Labs, an Israeli specialist in AI infrastructure technologies for data centers, has raised over $300 million. This allowed it to increase its post-money valuation to $2.8 billion. This move will help the company scale its products and strengthen its penetration into the rapidly growing artificial intelligence market.
The funding was led by several funds, including Fidelity Management & Research Company. The remaining investments were provided by partners such as Aliya Capital Partners, Atreides Management, Artisan Partners, Battery Ventures, Diagonal Capital, and Intel Capital.
The funds raised will allow Xsight Labs to continue developing a multi-generational roadmap for Ethernet switches and Data Processing Units (DPUs), as well as advancing the UEC (Ultra Ethernet Consortium) roadmap. The company plans to hire engineers, expand manufacturing capacity, supply chains, and customer service.
Xsight Labs CEO, Yossi Meyuchas, stated: 'Our company strives to provide high-performance networking solutions and distributed, intelligent, high-performance network infrastructure to support next-generation AI workloads and cloud giant infrastructure.'
Founded in January 2020 with the goal of creating advanced networking technologies, the company provides intelligent connectivity technologies for open ecosystems—from enterprise edge to data centers and AI serving cloud giants.
Its product portfolio includes solutions such as E1 DPU, intelligent processors, and X2 switches for data centers. The X2 switch provides low-latency processing on the 800G line with industry-leading energy efficiency.
The platform operates on open standards, including DPDK and SONiC, in Linux-based network technology environments for enterprises. It utilizes a programmable data plane based on Xsight's instruction set architecture compiler technology.
Currently, Xsight Labs conducts research and development activities and maintains regional offices in Israel, the United States, and Armenia, supporting clients who are building increasingly complex AI computing environments.
These capabilities allow customers to customize their network infrastructure. The funding announcement followed a successful joint technology trial with SpaceX, during which Xsight processors were integrated into the company's new V3 satellite platform.
According to reports, the programmable X2 switch allows customers to modify network software after deployment, which is particularly valuable for space applications where remote updates are necessary.
The timing of the fundraising reflects the growing demand for network equipment capable of supporting large-scale AI systems, cloud infrastructure, and specialized computing environments.
The need for faster and more efficient network equipment has become critical for modern data center architecture. AI training clusters require massive bandwidth, ultra-low latency, and reconfigurable network solutions for efficient data movement.
These capabilities enable the processing of colossal amounts of data required for modern advanced artificial intelligence workloads. Large institutional investors and technology-focused venture firms are increasingly backing silicon companies that develop critical AI infrastructure.
Their investments demonstrate growing confidence in silicon companies enabling the next generation of AI computing. Investment capital is shifting from AI software to silicon companies creating platforms for computation and connectivity.
With strengthened financial standing, growing customer base, and investment in connectivity, Xsight Labs is poised for further expansion. The company is well-positioned to become a major provider of AI-managed cloud and data center infrastructure.
