Xona raises $250 million to expand commercial GPS satellite navigation network

The Israeli cybersecurity startup announced the successful raising of $34 million in funding. This round was a Series A of $28 million, led by the fund Red Dot Capital Partners. Representatives from Lumir Growth Partners also participated in the investment.

The company plans for its solutions to enable security teams to respond faster as cyber threats become more complex. Previously, Mave had raised $6 million in seed funding from Dell Technologies Capital and Emerge Ventures.

The funds will be directed towards developing products for the corporate sector and conducting artificial intelligence research, as well as implementing expansion plans. Mave's AI-based tools are designed to reduce the time analysts spend gathering evidence and analyzing alerts.

Mave was founded in 2025 by CEO Raziel Oren and CTO Guy Eshel, who co-founded the company. Both founders previously served in Israel's intelligence unit 'Unit 8200', providing the company with deep expertise in corporate security operations.

Large organizations often use dozens of different security tools. Incident information can be scattered across identity systems, endpoints, and cloud environments. Analysts have to consolidate these disparate data sources before making decisions on further actions.

Traditional Security Information and Event Management (SIEM) systems provide a unified view of collected data, but they may not contain all the necessary information to understand an active incident. This forces analysts to manually check threats across multiple platforms.

Mave's AI agents integrate directly with existing security systems. They query data from each tool, collect relevant information, and consolidate the results within a single investigation. The platform is also designed to filter false positives and detect activity related to potential attacks.

The system is capable of executing approved response actions according to rules set by security teams. These actions can include isolating affected systems, disabling compromised accounts, and blocking malicious activity. Human oversight remains critical when approval or judgment is required.

According to Mave, its platform is already used by 50 companies and global managed security service providers. These implementations help protect hundreds of clients, including organizations operating in regulated financial and medical sectors.

The company reports that its annual recurring revenue has grown by over 400% in the last year and is closing seven-figure deals. These metrics attract commercial attention, even though the absolute revenue volume is not disclosed.

The fundraising comes amid a growing number of AI-driven attacks against organizations. AI-based cyberattacks can develop significantly faster than security teams can conduct manual investigations. Mave believes that agentic systems will help organizations cope with this increasing volume of threats.

The new funding will be used to develop the research platform and strengthen the enterprise platform, as well as for international scaling, as interest in automated security operations continues to grow. The company currently has about 30 employees and plans to double its staff over the next three years, adding specialists in go-to-market and AI research.

The Israeli development center of the company will play a key role in this growth. Like other firms creating AI-based security devices, Mave operates in a competitive environment. The success of Mave's enterprise segment depends on the reliability of investigations, openness of choice, and restraint in response measures.

The corporate artificial intelligence (AI) company RapidCanvas announced on Friday that it has raised $29 million in a Series B funding round. The round was led by Vertex Ventures SEA & India. Hitachi Ventures also participated in the round, along with existing investors including Accel, Peak XV Partners, Valley Capital Partners, and Titanium Ventures.

This funding increases the total amount raised by the company to $52.5 million. RapidCanvas plans to use these funds to expand its go-to-market teams, as well as to grow its network of private equity and consulting service partners. Furthermore, the company intends to scale up its field AI engineering team in India, the United States, and Brazil.

According to RapidCanvas itself, this round followed an eightfold growth in annual recurring revenue over the last six quarters, as enterprises increasingly demand tangible results from custom AI in production processes. The company reported that over 40 percent of its clients are already using multiple AI use cases in their operations.

RapidCanvas combines its AI platform with field AI engineers to provide tailored AI solutions. In this process, engineers study each client's business processes, develop and create custom AI applications, and remain responsible for achieving the results of these applications after implementation.

The platform includes three products: Enterprise Context Engine allows an enterprise to record how a business process functions, starting from requirements and accumulated knowledge to data schemas and decision history, while the context remains the property of the enterprise. Visual Development Canvas enables AI engineers to quickly create custom AI solutions that comply with industry standards. And Operational Harness manages and monitors AI solutions after they are deployed in the working environment.

According to the company, by 2026 alone, over 75 enterprises in the manufacturing, financial services, retail, business services, and infrastructure sectors will have made 1.4 million AI-driven decisions using applications built on RapidCanvas. RapidCanvas serves enterprises with revenues between $100 million and $10 billion that have AI budgets and mandates from top management.

Rahul Pangam, co-founder and CEO of RapidCanvas, stated: 'AI can be a great equalizer, but so far the most significant successes have gone to companies on the Fortune 100 list. We want to provide equal opportunities to every company.' He added that 'Vibe coding simplified getting started with AI, but reliable and secure deployment of AI into production remains the biggest challenge. Our growth over the last six quarters proves that AI in the corporate sector is moving beyond pilot projects and into real operation.'

Piyush Harbanda, General Partner at Vertex Ventures SEA & India, noted: 'Most enterprises are still looking for a real return on their AI spending. RapidCanvas delivers this return by combining an AI platform that is enhanced with every deployment and engineers who work on the ground and are responsible for the final outcome. The proof is that clients continue to expand the use of new features and scenarios.'

North.cloud has successfully raised $60 million in a Series B funding round. These funds will be used to develop the company's financial operating system, which covers cloud services, artificial intelligence, and data handling.

Investors participating in this round include Peak Span Capital, Liquidity Ventures, Companyon Ventures, Alpaca, Uncommon Denominator, Gaingels, and Mana Ventures. The secured capital will allow for increased investment in product development, as well as ensuring a higher degree of automation and adding new integrations.

North enables enterprises to reduce infrastructure costs across all leading cloud service providers and modern data platforms, including Microsoft Azure, Google Cloud, and AWS. The company aims to replace fragmented processes related to various pricing models, usage requirements, and reporting tools inherent in each system (whether it is cloud infrastructure, a data model, or a service).

Thanks to the North platform, clients have saved over $400 million against total managed cloud spending, which approaches two billion dollars. Among the company's clients are AssemblyAI, Atlan, Tines, SnapLogic, Emplifi, and Imply. The platform addresses a growing problem for finance and engineering departments.

Traditionally, teams often use spreadsheets and separate dashboards to understand infrastructure costs, which consumes significant time without automatically eliminating costly inefficiencies. North combines cost analytics with automated optimization, helping businesses identify waste, manage cloud commitments, and increase computing value. This approach provides finance and engineering teams with a unified view of infrastructure economics.

The latest funding followed the release of North v3, which expanded support to Microsoft Azure, thus completing support for three major hyperscalers. Furthermore, native integrations with OpenAI, Anthropic, and Snowflake were implemented, and the Autobot automatic commitment scaling mechanism was enhanced.

Artificial intelligence is creating new challenges in business financial management. The increasing use of models adds an extra layer of complexity to existing cloud service and data expenditures. North is expanding its platform to help companies manage these interconnected costs.

TokenFlow's offering integrates model usage, attribution, budgeting, and financial control into a single system. Businesses can use these features alongside existing cloud infrastructure management, reflecting the growing overlap between AI and traditional infrastructure costs.

North believes that effective cost management requires more than just dashboards for companies. Automated systems can help teams detect changes, improve resource allocation, and leverage optimization capabilities, which can reduce manual workload as AI adoption accelerates.

AssemblyAI reported an effective savings rate of about 50% through its work with North. The company noted that its coverage expanded in parallel with infrastructure growth, allowing the team to focus on customer-centric development.

North plans to reinvest the Series B funds into increasing the number of integrations and strengthening autonomous optimization. Funds will also be invested in additional AI cost management tools and new personnel hiring. These investments will help North realize its vision of fully automating the infrastructure cost lifecycle.

The company demonstrates a customer retention rate of 98.8% and reports over $400 million saved by its clients. North's current clientele includes several large technology companies, and the company believes its results can be leveraged to target other cost categories. As AI plays an increasingly vital role in software development, infrastructure costs are becoming less separate from the product and the business it supports. North is building a platform designed to help such enterprises manage these expenses without stifling innovation.