Corridor successfully raised $25 million in a seed funding round to scale its artificial intelligence-based brokerage service for medical benefits. The investment round was led by Bain Capital Ventures, with participation from BoxGroup. Investors include executives from technology companies such as OpenAI, Scale AI, and Ramp.
Corridor serves businesses with between one and 500 employees. The company asserts that small employers often receive less support from traditional brokers. The brokerage firm insists that small accounts require a similar volume of work despite lower commissions.
The Corridor platform utilizes AI-powered agents to perform administrative tasks under the supervision of human consultants. These agents are capable of vetting provider networks and organizing insurance information. Furthermore, they can schedule appointments and direct updated coverage details to physicians.
Corridor enables clients to receive quotes across the entire insurance market, allowing insurers to compete for business based on available plans and pricing. The company combines licensed consultants with AI-driven administrative support. The secured funding will be used to expand the company ahead of the next benefits enrollment cycle.
The process begins with employers providing information about their teams, budgets, and healthcare needs. Agents then structure the company and plan data, gather insurance quotes, and compare available options from various insurers. The system generates proposals and identifies potential risks in different plans.
Subsequently, human consultants present suitable options to employers. Employees can select their desired coverage during the enrollment process. Corridor agents continue to support clients after plan selection, including verifying if physicians remain within the insurance networks. Agents can also coordinate treatment and update insurance data for service providers.
The company reports that its clients save an average of 20% on medical benefits. Corridor's client base spans the technology, hospitality, capital management, and medical practice sectors. Corridor's model addresses challenges faced by small employers in the US. According to a 2025 KFF survey, workers at small firms experienced higher deductibles. Workers at firms with 10 to 199 employees had an average deductible of $2,631, compared to $1,670 in larger firms.
KFF also noted that in 2025, 59% of small businesses offered health insurance. Cost remained a significant barrier for companies that did not provide coverage. Corridor aims to solve these issues with its technology-enhanced brokerage model. The company believes that improved plan comparison can increase accessibility for small employers. Their approach keeps healthcare leadership human-centric while delegating administrative work to AI agents, allowing consultants to focus on employer needs and employee support.
The new funding comes just before the fourth quarter. Corridor notes that about 80% of small businesses choose health insurance plans in the fourth quarter, so the company is preparing its platform for increased demand. The main focus will be on supporting employers in plan selection and enrollment.
Corridor was founded after Jackson Wagner encountered difficulties following a sports injury. This experience highlighted the complexities of navigating medical services and insurance. Wagner later studied computer science and electrical engineering at the University of California, Berkeley. He worked with a former Scale AI colleague, Eric Tsien, on the Capernaum AI project, which focused on clinical AI for musculoskeletal and chronic pain treatment. The founders subsequently connected with Nikhil Aggarwal and Jason Dong from Cold Start. The group ultimately shifted to the broader field of medical benefits. Aggarwal became CEO of Corridor, and Wagner took on an executive role. The company now aims to become a trusted healthcare provider for American businesses.
Factory has successfully raised $200 million in a new funding round, achieving a valuation of $5 billion. Investors in this round include Blackstone, Khosla Ventures, and Sequoia Capital. Insight Partners, Evantic Capital, and Sound Ventures also participated.
Factory was founded in 2023 by Matan Greenberg and Eno Reyes. Other investors included NEA, Mantis VC, and Clearlake. The round also attracted angel investors, including Nico Rosberg, Brad Gerstner, and Mark Benioff.
The new funding increases the company's total capital raised to over $400 million. This represents significant growth compared to the $1.5 billion valuation set in April. Thus, in five months, Factory's valuation has more than tripled; previously, the company had raised $150 million at that same valuation.
The latest capital raise reflects growing enterprise demand for autonomous software development tools. The San Francisco-based company aims to increase the degree of autonomy in software development. Its platform enables large enterprises to create, test, and maintain software using artificial intelligence agents throughout the entire development lifecycle.
Factory differs from platforms focused on individual coding agents because it provides enterprises with a unified system for managing software development. The platform allows companies to control the training process of their 'software factory,' as well as manage models and system deployment. Factory can operate through its managed cloud infrastructure, or clients can deploy it on-premises or in fully isolated environments, giving enterprises greater control over AI-driven development.
The company reports that its platform is used by hundreds of thousands of developers. Factory's clients include Nvidia, Blackstone, Royal Bank of Canada, Palo Alto Networks, and Adobe. This growing client portfolio underscores the increased interest from the corporate sector in AI-powered software development.
Enterprises are increasingly using AI to boost engineering productivity. Factory believes that companies are moving from using individual coding assistants to building broader software factories around autonomous systems. Matan Greenberg noted: 'Major enterprises worldwide are transitioning from individual coding agents to software factories,' adding that clients confirm the potential for rearchitecting software development systems, although the company is still in the early stages of this transition.
Factory's strategy is focused on creating autonomous software factories that operate continuously under human supervision. Enterprises can regulate measurable outcomes while AI performs development tasks. The company competes in the rapidly growing AI coding market. Factory plans to use the new capital to support further growth, focusing particularly on platform expansion and adoption within the corporate sector.
The tech startup Graph AI, which specializes in the pharmaceutical industry, has successfully raised $13.3 million in a Series A funding round. The round was led by Insight Partners, with participation from existing investors, including Bessemer Venture Partners.
The funds raised will be used to expand the company's operations in the US and Europe, as well as to accelerate product development.
Graph AI was founded in 2024 by experienced employees from corporate technology companies who previously worked at organizations such as Google, Wipro, Infosys, LTI, and ServiceNow. The startup has developed an artificial intelligence platform that automates processes related to pharmacovigilance and patient safety.
Raghav Parvatiraju, CEO of Graph AI, noted that traditionally, pharmacovigilance scaled up by increasing staff and processes around outdated systems. He stated: 'We believe that intelligence can change this. Graph Safety provides safety experts with an intelligent system that takes on operational complexity while keeping traceability, accountability, and human oversight central.'
The startup's platform combines artificial intelligence with deterministic controls, validation levels, and end-to-end audit trails specifically designed for regulated pharmacovigilance environments. The platform's development took into account applicable regulatory requirements and evolving expectations regarding the use of AI in drug development and patient safety.
Graph AI claims that during real-world implementation, its platform reduced case processing time from over three hours to less than ten minutes, allowing for a reduction in operating costs by up to 66%.
The company has already attracted clients from the pharmaceutical and biotechnology sectors in North America and other markets, and has also signed partnership agreements for module development.
Richard Mattus, Senior Partner at Insight Partners, commented on the situation, noting that pharmaceutical companies must ensure absolute patient safety, but most are unwilling to integrate disparate tools to achieve this goal. He added that software and service providers are not keeping pace with what modern AI is capable of doing to increase accuracy and value for pharma companies.
Euno has successfully raised $23 million in a Series A funding round, which will be used to expand its artificial intelligence context platform. The round was led by N47, with participation from existing investors, including 10D. Founders and executives from technology companies such as Wiz, Cyera, Eon, Tavily, and Tableau also participated in the financing.
With this new round, Euno's total funding has reached $29 million. The company is currently actively increasing its presence among large corporate clients. Euno was founded in 2023 by Sarah Levy and Eyad Firstenberg. The company's operations are focused in San Francisco and Tel Aviv.
The founders possess extensive experience in cybersecurity, AI, and data infrastructure. Their previous work includes roles at Sight Diagnostics, Unit 8200, and LightCyber. Euno is currently hiring around 30 employees in the United States and Israel.
Enterprise AI systems critically depend on accurate and reliable information. However, AI agents often struggle to understand how organizations actually use their data. Euno solves this problem with an AI-native context platform.
The company's technology continuously studies processes for building, using, and managing information within organizations. The company positions its platform as the 'AI brain' for enterprise data, providing agents with the necessary context to navigate complex organizational systems. Euno analyzes metadata patterns to reconstruct institutional knowledge, allowing it to identify data meaning, origin, owner, and governance rules. The platform then supplies each AI agent with the required context to perform a task, limiting unnecessary access and increasing the reliability of automated decisions.
Furthermore, the platform learns from agents' interactions with the organizational context, creating feedback loops that continuously improve the platform's understanding. The company believes this can shorten lengthy processes for preparing for AI adoption. Traditionally, corporate teams manually maintained context, relying on data catalogs, semantic layers, and governance policies. Euno argues that such systems were originally designed for humans, whereas AI agents function differently because they can move autonomously between multiple systems.
Therefore, the platform integrates governance directly into its context infrastructure. It determines what information an agent can access based on its role and task. This approach helps enterprises maintain organizational boundaries during automated workflows and gives data teams greater control over increasingly autonomous AI systems. Euno has already attracted clients from the Fortune 500 list across various industries, including AlphaSense and the telecommunications company Zayo Group.
The new capital will primarily be directed towards supporting sales, marketing, and AI research. Euno also plans to significantly expand its technical team. N47 expresses confidence that the demand for enterprise AI infrastructure is rapidly growing, considering context indispensable for agents working with business data. Additionally, Euno received recognition from Gartner, being included in the 'Coolest Vendor Innovations in Data Management' list for 2026, where its constantly updated graph of enterprise context was noted for semantic data understanding.
This recognition boosts trust, as enterprises seek more robust AI infrastructure. Euno competes in the rapidly evolving enterprise AI market, where organizations increasingly want agents capable of independently performing complex tasks. Euno potentially could make organizational context the core layer of enterprise AI infrastructure. Nevertheless, greater autonomy introduces new data and governance challenges that Euno intends to solve through a continuously learning context layer. The company now has the funding to expand its technologies and commercial reach.
