Enterprise AI agents can't talk to each other, can't be trusted with permissions, and can't be audited — 5 startups are already fixing that

Enterprise AI agents can do the work — but the infrastructure to let them talk to each other, prove they should be trusted, and be audited when something goes wrong is still being built.Here's a look at how five startups are tackling that gap — around orchestration, observability, connectivity, and security — as shown at VB Transform 2026.BAND is orchestrating all the agents you have running in the backgroundIn the very near future, agents will be deployed everywhere, and they will do work on our behalf, noted Vlad Luzin, CTO and co-founder of BAND. As he describes it: They will receive tasks, visit registries, recruit other agents to help them, delegate subtasks to AI peers in a “conversational space,” gather and share results, then return a summary to the human user. BAND is building a coordination infrastructure layer for multi-agent AI systems to make this a reality. Why don’t Telegram, Slack, or Discord solve the problem? These platforms were built for humans, Luzin noted. Agents have to be onboarded manually in numerous steps, and they can’t see each other; “they are still alone in a kind of digital solitary confinement.” Similarly, Claude is stateless, and devs often have multiple sessions open at a time that they toggle between for different tasks — something Luzin said creates real friction.The challenge is connecting remote processes, which Luzin called a distributed systems problem.“The transportation layer needs to be solved first, how the agents communicate in real time,” he said. Conversations can’t happen through IPs and URLs; they need to be bumped to the abstraction layer so agents can talk across channels, conversational spaces, and platforms.“Agents see each other. They understand. They can collaborate together. They discuss issues. They fix issues, and they ask for review from another,” Luzin said. BAND supports autonomous workflows that can run for eight to 20 hours and is compatible with A2A and MCP protocols, according to Luzin. Importantly, humans can join the conversation as agents converse and discover one another, he said. “We can record and show you all the tasks that your agent generates in real time,” Luzin said. Conifers is helping defenders move at machine speedThe biggest challenge defenders face today is that they’re still running at human speed, but adversaries are running at machine speed, said Tom Findling, CEO and co-founder of Conifers. Attackers are already adopting agents, Findling said, and they only have to be successful once to penetrate an enterprise. Malicious campaigns that used to take months and weeks now take hours, even minutes. Security operations, on the other hand, are fragmented, manual, inefficient, and slow. Findling said Conifers has taken various components of cyber defense — private intelligence, hunting, detection, engineering, investigation, response — and made them agentic. They then broke down the silos between them, he said. Various agentic systems can communicate with one another to ensure that operational defense and active defense are always on and adapting. Findling said that Conifers’ system is condensing containment time from 7 hours to 12 minutes, and that the company can turn around complex cyber investigations in four minutes or less. He emphasized the importance of connecting to an enterprise’s existing security tools, whether that be endpoint detection and response (EDR), security information and event management (SIEM), posture management, or others. Conifers helps customers understand their security posture, pain points, which controls are working and which are not, and the areas to invest for the best ROI. “The threat landscape is changing, detection stays the same, and threat intelligence is not being operationalized,” Findling said. “This is a job for agents.” Raindrop AI creates an agent audit logOne of the defining problems of the current era is finding critical issues in AI agents, says Ben Hylak, CTO of Raindrop AI. It’s what he called a