Oak has emerged from stealth mode, announcing the raising of $60 million in a seed round. These funds are earmarked to accelerate the development of its Artificial Intelligence-based Identity Operating System. The company's goal is to unify identity management and security by replacing disparate legacy tools with a single platform.
The seed round was co-led by Accel, Greylock Partners, and CRV, with participation from Hetz Ventures, AlphaDrive Ventures, and several strategic private investors. The startup plans to use the investment to expand its teams in engineering, artificial intelligence, and cybersecurity.
Oak was founded by cybersecurity veterans Shay Morag and Tal Marom. The company has already begun commercial deployment of its platform among enterprise clients, believing that identity has become the largest attack surface for organizations.
The Oak platform is designed to provide organizations with a continuously updated level of control that manages every identity throughout its lifecycle. The system supports both human users and machine identities and AI agents, reflecting the growing complexity of enterprise environments.
Instead of relying on static identity records, the platform analyzes raw data from enterprise systems to build a live identity graph. It then assesses actual access usage and automatically identifies unnecessary permissions and potential security threats. Thanks to its AI-driven architecture, the company claims that creating new application connectors takes hours, not months, as often required by traditional identity management platforms.
Tal Marom, Product Director at Oak, noted that discussions with over one hundred information security executives and identity leaders revealed widespread dissatisfaction with fragmented security tools and limited visibility in access management.
Morag brings over two decades of experience in cybersecurity to the business. Before launching Oak, he founded Integrity-Project, Secdo, and Ermetic, all of which were acquired by major cybersecurity companies, including NVIDIA's Mellanox, Palo Alto Networks, and Tenable. After Tenable acquired Ermetic, Morag served as the product director for that company before co-founding Oak with Marom. Marom previously held leadership roles in product at Tenable and Salesforce.
The startup has already formed a team of about 50 employees and plans to continue hiring, especially in the United States, where significant future expansion will be focused. Oak's long-term vision is to replace numerous disconnected identity management tools with a single operating system that provides continuous visibility, automated risk assessment, and real-time issue resolution in the enterprise environment.
Identity management is becoming increasingly critical as organizations adopt more cloud services, connected devices, and AI-powered applications. The company expects the new investments to accelerate product innovation globally. Industry analysts predict that intelligent identity management platforms will become a key element of corporate cybersecurity strategies in the coming years, as enterprises strive for better visibility into who and what has access to critical systems. Oak believes that its AI-centric approach allows it to meet this growing demand by consolidating identity management, risk analysis, and automation into one platform, rather than relying on many separate products.
Tangos has successfully raised $20 million in a seed funding round. These funds are designated to accelerate the development of an autonomous artificial intelligence platform designed for investigating financial crimes.
The round was led by Red Dot Capital Partners. The founder of Tangos is entrepreneur Eyal Azoulay, who established the company in 2025. Leaders Fund, Clarim, Venture Israel, SignalFire, Clutch Capital, Selah Ventures, and Bright Data also participated in the investment.
Tangos' technology assists financial institutions in investigating suspicious transactions, sanctions violations, and fraud cases. The company asserts that existing compliance teams cannot investigate every signal due to increasing workload and a shortage of experienced investigators.
Unlike most compliance software, which merely flags suspicious activity before handing cases over to humans, the Tangos platform gathers evidence, verifies, and confirms a range of hypotheses, providing comprehensive reports ready for audit. The system is capable of analyzing alleged transactions, investigating money laundering and sanctions risks, examining ultimate beneficial ownership structures, and identifying hidden connections between organizations or individuals.
Regulatory-compliant reports can be generated such that every finding is traceable back to the original source data. According to the company, this enhances transparency while ensuring regulatory adherence. Eyal Azoulay, founder and CEO, believes that financial crime has evolved into a complex network problem that exceeds the capabilities of traditional investigation processes, and he posits that autonomous AI can significantly improve the speed, consistency, and quality of investigations.
Tangos reports that its platform is already utilized by major financial institutions, intelligence agencies, and government bodies conducting high-risk investigations. Clients employ this technology to strengthen compliance and increase investigation throughput. The company emphasizes that this approach solves one of the biggest operational challenges facing compliance departments, as although financial institutions invest heavily in suspicious behavior detection systems, the actual investigation of these signals remains time-consuming and expensive.
Instead of relying on unlimited AI reasoning, the Tangos platform is built around specialized AI components developed for specific investigative tasks. These components follow predefined investigative methodologies created in collaboration with financial crime experts.
Financial crimes, exacerbated by the increasing sophistication of criminals, are driving growing demand for solutions in the financial crime technology space. Consequently, banks, governments, and fintech organizations are increasingly using AI tools to boost efficiency. Tangos plans to use the raised investments to accelerate research initiatives and deploy its platform into other regulated sectors. The company has not yet disclosed hiring targets but intends to scale its capabilities as corporate demand grows. As artificial intelligence becomes more widely integrated into compliance operations, Tangos positions itself to automate one of the most time-intensive stages of preventing financial crime, while retaining human responsibility for final decisions.
TwelveLabs has successfully raised $100 million in a Series B round to accelerate the development of its artificial intelligence platforms. The investment was co-led by NEA and NAVER Ventures. Amazon, Radical Ventures, Korea Investment Partners, Index Ventures, Quadrille Capital, and Red Bull Ventures also participated in the round.
This round increases TwelveLabs' total raised capital to nearly $150 million. The funds will be allocated to research, product development, and international expansion. The company plans to open new offices in New York and London, as well as strengthen existing centers in San Francisco and Seoul.
Founded in 2021, TwelveLabs creates AI models that analyze existing video content rather than generating new video. According to the company, this allows organizations to find significant information within vast video archives that are difficult to review using traditional methods.
Unlike AI companies focused on video creation, TwelveLabs specializes in helping organizations understand existing recordings. Their technology is designed for industries with large video archives, including government bodies, advertising, media, sports, and security sectors.
The company's Marengo model transforms speech, sounds, movements, and visual events into searchable information. The second model, Pegasus, structures this data, enabling the identification of relationships, timeframes, and events in long recordings. Jae Lee noted that the company's long-term advantage lies in creating an intelligence layer that extracts valuable knowledge from video, instead of relying solely on increasingly common AI models.
One of the key outcomes of this round was the formal establishment of Amazon Web Services as TwelveLabs' preferred cloud provider following its participation in the funding. This partnership means that future AI models will be optimized for AWS Trainium chips before widespread deployment. The Marengo and Pegasus models are already available through Amazon Bedrock, as well as via TwelveLabs' proprietary API.
Industry observers are increasingly viewing such investments as strategic collaborations with cloud providers, rather than just venture capital deals. Cloud providers thus secure long-term infrastructure clients, supporting complex AI computational tasks.
NAVER Ventures also reached a significant milestone with this investment. The firm launched its Silicon Valley division in 2025, and TwelveLabs became its first portfolio company, subsequently co-leading this latest funding round.
Over the past year, TwelveLabs has significantly expanded its operations: its staff grew from fewer than 60 employees to approximately 178 people. The company now serves clients in public administration, corporate business, media, entertainment, and security sectors. The demand for AI-powered video search continues to grow as organizations seek practical applications beyond content generation.
The new funding will support further research in San Francisco and Seoul, and expand the company's client base in Europe and North America. Furthermore, the company intends to strengthen its platform for enterprise clients who require complex video analysis at scale. TwelveLabs follows a different strategy than video generation tool companies, helping organizations transform video into actionable information to support decision-making and improve operational efficiency.
LinqAlpha has successfully raised $22 million in a Series A funding round. These funds are earmarked to accelerate the growth of its artificial intelligence platform designed for institutional investors.
The round was supported by investors such as AVP, Atinum Investment, and GFT Ventures. Additionally, several strategic financial institutions and venture platforms from Europe, Asia, and the United States participated. The New York-based company develops what it calls the Alpha Intelligence Layer for global public markets.
The platform assists investment specialists in processing complex market information using specialized AI agents. With this new funding, LinqAlpha's total raised capital has increased to approximately $28.6 million.
LinqAlpha was founded in 2022 by Jacob Choi, Subin Pang, Jin Kim, and Hodjun Choi. The founding team combines financial expertise with research in artificial intelligence. Among the founders are former Goldman Sachs analysts and MIT computer science graduates.
As public markets become increasingly interconnected, investors are forced to simultaneously track earnings reports, policy changes, supply chain events, credit markets, and social media signals. LinqAlpha believes that traditional analysis methods cannot keep up with such a growing volume of data. The platform allows investment teams to use AI agents trained on their own research history instead of relying on general language models. These agents then link new market events to previous investment ideas to generate relevant insights. One of the founders noted that the competitive advantage lies in identifying market-influencing signals even before they become widely known.
Currently, the platform is used by over 70 financial institutions. Clients include research, trading, and sales teams at major investment banks. On the buying side, clients include Causeway Capital Management LLC and Schonfeld Strategic Advisors LLC. The company initially started in Cambridge, Massachusetts, and later operated between South Korea and the United States before establishing its headquarters in New York. During this period, the business also underwent two rebrandings before adopting the name LinqAlpha.
The new funding will allow the company to expand its international staff. Management also plans to strengthen integration with market and alternative datasets. Additional investments will be directed towards implementing equity, macroeconomics, credit, and multi-asset investment strategies.
LinqAlpha is entering the competitive market of AI research platforms. Demand continues to grow as investment firms seek faster analysis without compromising their proprietary insights. According to Manish Agarwal, General Partner at AVP, many AI products focus on automating routine tasks or accelerating information retrieval. He believes that LinqAlpha helps investors find differentiated investment ideas through context-aware intelligence.
Competition remains significant, as large AI service providers have attracted significantly more funding in recent years. Nevertheless, LinqAlpha asserts that its specialized approach better meets the needs of institutional investors who seek bespoke analysis rather than standard AI outputs. Industry forecasts also point to continued expansion in financial AI, with growing adoption among banks, insurance companies, and asset managers expected to attract further investment in companies developing specialized corporate AI platforms. LinqAlpha's long-term success will likely depend on demonstrating measurable value to institutional clients operating in increasingly complex global markets.
