Factory raises $200 million at $5 billion valuation to scale AI software development

Positron AI has successfully raised $875 million in a Series C funding round, valuing the company at $5 billion. The company's core business involves developing hardware that makes the artificial intelligence inference process more energy-efficient and cost-effective.

The funding was secured in two stages: first, a Series C round of $375 million was closed, followed by a Series C-1 round of up to $500 million. The main round was led by NEA, Atreides Management, and Valor Equity Partners, with co-leads from Andra Capital and SemiAnalysis Capital participating. The second tranche was led by Jim Clark, founder of Silicon Graphics and Netscape, with participation from several institutional and strategic investors.

The capital raised will allow Positron to significantly expand its growing business in inference and add several experienced technology investors to its board of directors. Forest Basket from NEA and Gavin Baker from Atreides Management will join the board. Thomas Germoluk and Dylan Patel will also become directors.

As AI workloads increasingly shift towards inference, infrastructure is necessary for the continuous operation of models by every AI assistant, agent, and helper. Positron focuses on solving memory and power issues arising from this growth. The company's systems are designed with an emphasis on bandwidth and memory capacity, rather than raw computational power.

The company's next-generation systems utilize standard LPDDR5X memory, which reduces dependence on constrained high-performance memory supply chains. Positron claims its systems can achieve over 90% of available memory bandwidth.

Furthermore, the company focuses on high performance in tokens per dollar and tokens per watt metrics. Positron's architecture supports both air-cooled and liquid-cooled data centers, giving customers flexibility in deploying systems across various rack densities.

Positron already has clients using the first version of the Atlas system. Over 50 Atlas racks have been deployed in Oracle Cloud Infrastructure, where Parasail uses this power for its own inference services. Jump Trading and i3d.net are also production clients of Atlas.

The new funding will be directed towards developing the next generation of silicon chips. The Asimov chip is scheduled for fabrication using TSMC's N3P process by the end of 2026; TSMC describes N3P as an improved 3nm process. Production of Asimov is slated for the second half of 2027. Each Asimov chip will support between 288 GB and 2304 GB of memory, meeting the demands of increasingly complex AI inference workloads.

The Titan system will integrate four to eight Asimov chips into a single system and is designed to support models exceeding 16 trillion parameters. Titan will also target context windows exceeding 10 million tokens and can scale to thousands of nodes for larger deployments. Positron also plans to build a data center engineering facility with a capacity of over 2 MW and an emulation platform to support development, testing, and manufacturing readiness.

Positron intends to use the funds to secure LPDDR5X supply commitments, as well as to increase manufacturing capacity and system integration. Go-to-market operations will expand in parallel with production, helping the company meet the growing demand for inference infrastructure.

CEO Mitesh Agrawal noted that the Atlas deployments provided valuable customer insights that influenced the design of Asimov and Titan. The company is currently in a demanding execution phase, requiring it to complete silicon development while simultaneously scaling production and customer adoption.

Positron's strategy is focused on the economic efficiency of AI model operation. Its memory-centric architecture aims to reduce both energy consumption and infrastructure costs. The $5 billion valuation reflects investor confidence in the inference market.

Blee, a New York-based company, has successfully raised $20 million in Series A funding. The company provides corporate clients with tools to ensure that marketing materials comply using artificial intelligence.

The funding round was co-led by Fin Capital and SMBC Fin Atlas Beyond Fund, with participation from Hannah Grey VC and the National Bank of Canada. Existing investors, including Y Combinator, Penny Jar Capital, Cardumen Capital, and Treasury, continued to support the company. With this new injection, Blee's total funding has reached $27 million. The company was founded in 2022 with the goal of modernizing corporate content management.

Blee serves teams responsible for legal matters, regulatory compliance, and branding that manage client-facing content. The company's platform helps organizations vet materials before publication and monitors published content to ensure ongoing compliance. The company plans to continue investing in both its product and its team.

Artificial intelligence allows marketing departments to create content faster than ever before. However, this acceleration introduces new complexities for legal and compliance teams. Traditional review processes often rely on manual checks.

Gartner predicts a sharp increase in the automation of marketing work using AI. Marketing leaders expect the level of automation to rise from 16% in 2026 to 36% by 2028. The growing volume of content creates pressure in regulated industries, and Blee intends to support organizations managing increasingly automated marketing operations.

Teams need to review advertisements, video materials, partnership assets, and digital campaigns. Blee aims to bridge this gap through AI-powered compliance. Its platform integrates with existing content creation tools, thereby creating a continuous layer of governance for corporate marketing.

The system provides feedback regarding regulatory, legal, compliance requirements, and brand standards. Teams can identify potential issues even before materials undergo official review. Blee reported that its clients have achieved a reduction in average review time by 65%.

Blee manages the workflow from initial submission to approval, as well as tracking comments and maintaining a full audit trail. The platform continues to function after content reaches customers, monitoring published materials for adherence to regulatory and brand norms. This includes social media and influencer websites. This approach gives compliance teams greater transparency across all content channels. Furthermore, Blee is responding to the rise of AI agents capable of generating large volumes of customer content with minimal human involvement.

Founder and CEO Guy Shahar stated that businesses require stronger control over their content. He believes that organizations implementing such systems early can gain a competitive advantage. Expedia Group is one of Blee's clients, utilizing the platform to support its legal activities.

Blee plans to use the Series A funds to deepen its capabilities in content governance. The company intends to expand into new industries and geographic markets, while also targeting more executives in the fields of law, compliance, marketing, and branding.

Currently, Blee serves large enterprises across several core sectors, including financial services, travel, life sciences, and consumer brands. SoFi Technologies also uses the platform. Blee reported that its annual recurring revenue increased tenfold between June 2025 and June 2026. The company is also preparing for announcements of additional enterprise clients. Its expansion is expected to strengthen its presence in North America and Europe. The funding comes amid the growing use of AI-generated content by enterprises. Companies are now forced to balance faster production with enhanced control. Blee aims to become the central compliance layer for this transition, and its platform is designed to help enterprises scale content without compromising oversight.

HiddenLayer, a company specializing in artificial intelligence security, has successfully closed a Series B funding round, raising $100 million. The leadership of this round included Delta-v Capital, with participation from Ten Eleven Ventures, Morgan Stanley, M12, and Booz Allen Ventures. The fundraising occurred amid a significant surge in demand for AI security solutions.

Over the past year, HiddenLayer's annual recurring revenue has increased more than tenfold, and the company has also acquired over 50 new clients. These clients operate in sectors such as financial services, healthcare, government, technology, and defense industry.

The HiddenLayer platform is designed to support organizations implementing generative, predictive, and agentic AI systems. The system provides protection for AI applications throughout their entire lifecycle. The capital raised will be used to expand the enterprise platform and strengthen sales and distribution channels.

HiddenLayer is scaling its platform as enterprises begin to utilize autonomous AI agents. These systems are capable of making decisions independently and interacting with external tools. The company's Agentic Runtime Security feature allows for monitoring AI behavior during operation, enabling the detection of unauthorized actions, tool misuse, and manipulation.

Furthermore, the Agent Harness Security feature was introduced, which extends runtime protection to autonomous coding agents. These agents can write, test, and release software with minimal human involvement, creating additional risks for development teams in the corporate sector.

HiddenLayer believes that traditional security tools cannot handle these risks alone. AI systems can be threatened through poisoned models, malicious inputs, and prompt injections. Therefore, the company has focused its efforts on creating security specifically designed for AI environments. The platform integrates threat detection, attack simulation, supply chain security, and runtime security.

HiddenLayer's security capabilities are backed by an extensive AI research program. The company's researchers hold 39 granted patents and 65 pending patents related to AI threat analysis, model protection, and adversarial attack detection. The team has also developed a comprehensive Adversarial Prompt Engineering Taxonomy, continuing to identify vulnerabilities in the AI ecosystem. Research covers foundational models, AI tools, and auxiliary infrastructure.

HiddenLayer is also involved in industry initiatives concerning AI governance and security. Its researchers collaborate with organizations such as CISA, MITRE, NIST, OWASP, and OpenSSF. These joint efforts contribute to improving red teaming practices and overall AI security.

The new funding will serve as a foundation for the company's next phase of commercial growth. HiddenLayer recently appointed Mike Gesnaldo as Chief Revenue Officer. The company also plans to strengthen partnerships with sales channels and expand its international operations. Key expansion targets are Europe and the broader EMEA region.

HiddenLayer anticipates continued growth in enterprise demand for AI security. The company already serves clients in several highly regulated industries, including banking, insurance, pharmaceuticals, and government. One leading provider of frontier models also uses HiddenLayer technology, reportedly serving over 700 million users weekly.

The growth in HiddenLayer's client base reflects growing enterprise concern over AI security issues. The company's platform aims to help organizations adopt AI with greater confidence. The company forecasts that autonomous systems will become increasingly significant in business processes, which in turn will create additional demand for specialized AI security tools. HiddenLayer will now focus on scaling its platform in parallel with the rapid advancement of artificial intelligence, asserting that its research helps enterprises respond to emerging threats, with a particular focus on protecting AI systems during real deployment.