The Linux Foundation announced the formation of the Agentic AI Foundation (AAIF) with founding contributions from OpenAI, Anthropic, and Block, marking a strategic industry response to prevent AI agent ecosystem fragmentation through neutral, open standards.

The initiative addresses a critical infrastructure bottleneck: as AI systems evolve beyond chatbots toward autonomous agents capable of coordinating complex tasks, the technology landscape faces the risk of splintering into incompatible, proprietary stacks that would lock organizations into single-vendor dependencies.

General Intelligence has secured an $8.7M seed round led by Union Square Ventures to build an operating system for the “one-person, billion-dollar company.” The startup is already validating this vision by running its own business with 95% of its operations automated by AI agents.

This move signals a critical market evolution from point-solution AI tools toward full-stack orchestration infrastructure. While most enterprises struggle with the complexity of deploying and coordinating agents, General Intelligence is demonstrating how to achieve production-grade automation across product development, support, and core business functions.

Enterprise teams can build compelling AI demos, but 95% fail when moving to production—a bottleneck that Orq.ai targets with its €5 million seed round led by seed + speed Ventures and Galion.exe.

The Amsterdam-based platform addresses what co-founder Sohrab Hosseini calls the “industrialization gap”: the infrastructure needed to move AI agents from successful prototypes to reliable, compliant enterprise systems. While most teams can demonstrate AI capabilities, they consistently hit the same blockers when scaling—unclear agent behavior, fragmented tooling, missing observability, and manual compliance work.

7AI raised $130 million in the largest cybersecurity Series A funding round in history, validating autonomous AI agents as the infrastructure solution to enterprise security operations that can’t scale with traditional approaches.

The Boston-based company, led by Cybereason co-founder Lior Div, has processed over 2.5 million security alerts and completed more than 650,000 autonomous investigations in just 10 months since emerging from stealth. The Index Ventures-led round, with participation from Blackstone Innovations Investments, signals enterprise confidence in agentic security infrastructure that replaces human-driven alert triage with AI agents that investigate threats autonomously.

AI agents in financial services handle thousands of customer interactions daily, but manual compliance reviews cannot scale with rising regulatory scrutiny across jurisdictions like the EU AI Act and MiFID2. Alinia has raised $7.5M in seed funding to build compliance infrastructure that embeds real-time auditing, guardrails, and risk controls directly into AI workflows, ensuring regulatory adherence without deployment delays.

The Barcelona and New York-based startup closed the round led by Mouro Capital (Santander’s corporate VC), with participation from Raise Ventures, Speedinvest, and Precursor Ventures. This strategic backing from financial services infrastructure validates the compliance bottleneck across regulated industries deploying autonomous AI systems.

Simular raised $21.5 million in Series A funding from Felicis to scale desktop AI agents that control entire Mac and Windows computers directly—solving the hallucination problem that has kept enterprise AI automation confined to simple browser tasks.

The fundamental constraint limiting AI agent enterprise adoption isn’t capability but reliability. Current large language models hallucinate unpredictably, and when agents execute thousands of desktop steps, even small errors cascade into complete workflow failures. Simular’s breakthrough addresses this through “neuro symbolic computer use agents” that let AI explore freely, then lock successful workflows into deterministic code.

Raindrop’s $15 million seed round led by Lightspeed Venture Partners tackles a fundamental problem plaguing AI agent deployments: enterprises have no reliable way to detect when their production AI agents fail silently, creating business-critical blind spots in systems increasingly trusted with high-stakes decisions.

The monitoring infrastructure gap has become acute as AI agents evolve from simple chatbots to autonomous systems that “reason longer, use more tools, and connect to MCP servers,” running autonomously for hours across critical sectors like healthcare and financial services. Traditional monitoring tools offer only basic metrics like latency and token usage, leaving engineering teams unable to discover or track the complex behavioral failures that matter most.

Automat secured $15.5M in Series A funding led by Felicis with participation from Initialized, Khosla Ventures, and Y Combinator to replace legacy Robotic Process Automation (RPA) systems with agentic workflow infrastructure. The funding addresses a critical enterprise bottleneck where 70% of RPA implementations fail to scale beyond pilot deployments, creating a $30 billion market ripe for next-generation automation architecture.

The Legacy RPA Bottleneck

Enterprise automation faces fundamental scalability constraints with traditional RPA platforms like UiPath, Automation Anywhere, and Blue Prism. These systems require specialized developer teams, fragile low-code configurations, and expensive per-bot licensing that makes scaling economically prohibitive. The core technical limitation stems from brittle rule-based automation that breaks when user interfaces change, requiring constant maintenance and reconfiguration.

SF Compute’s $40 million Series A addresses a $11.76 billion infrastructure bottleneck: AI startups locked into 12-36 month GPU contracts while serving customers with sporadic usage patterns. The San Francisco-based startup has created a marketplace allowing companies to resell unused compute capacity, managing over $100 million in hardware across several thousand GPUs.

The funding round, led by DCVC and Wing Venture Capital with participation from Electric Capital and Alt Capital, values the company at $300 million. This represents a growing recognition that AI infrastructure financing models have created hidden systemic risks across the ecosystem.

Factory downtime costs the global manufacturing industry €1.21 trillion annually—a 319% increase since 2019 as supply chains grow more complex and energy prices rise. Zurich-based Cerrion raised €15.6 million ($18M) Series A led by Creandum to scale AI video agents that transform existing factory cameras into intelligent production monitors.

The funding comes amid escalating pressure on manufacturers to reduce unplanned downtime while managing rising operational costs. Traditional monitoring relies on human operators watching dozens of screens or reactive maintenance after problems occur—creating blind spots that lead to cascading failures.