We spent two years teaching agents to work—now we're learning they can't talk to each other without a translator.
The Summary
- BAND (Thenvoi AI Ltd.) raised $17 million in Seed funding to build what CEO Arick Goomanovsky calls "Slack for agents"—a universal orchestrator that lets AI agents built on different frameworks actually coordinate with each other.
- The problem: agents built on LangChain can't hand off tasks to CrewAI agents; Salesforce agents can't coordinate with custom Python scripts. Enterprises deployed hundreds of isolated tools that can't form a workforce.
- BAND's bet: API integrations won't cut it for non-deterministic agents. You need a new communication layer built for how agents actually behave.
The Signal
For eighteen months, companies raced to deploy autonomous agents. Customer support bots. Code refactoring assistants. Data pipeline managers. Everyone built, few thought about what happens when these things need to collaborate. The result is fragmentation at scale—a company might have twenty agents that can't talk to each other without brittle, custom integrations.
BAND's solution is what they call an "agentic mesh." Not just another orchestration layer. Not middleware that pipes data between APIs. A deterministic communication protocol specifically designed for non-deterministic agents. The distinction matters.
"The communication solutions we have today for systems don't work for agents, because agents are non-deterministic creatures."
Traditional system integration assumes predictable inputs and outputs. Agent A sends a formatted request, Agent B returns a formatted response, repeat forever. But agents don't work that way. They interpret. They make probabilistic decisions. They need context that changes based on prior interactions. You can't just slap an API wrapper on that and call it coordinated.
BAND's approach treats agent-to-agent communication more like human collaboration than system integration:
- Agents maintain conversational context across handoffs
- The orchestrator handles translation between different agent frameworks (LangChain, CrewAI, custom builds)
- Communication is deterministic even when the agents themselves aren't
The $17 million seed round suggests investors see the same pattern emerging. The first wave of AI infrastructure went to model training and deployment. The second wave went to agent builders and frameworks. This third wave—the plumbing that makes agents productive together—is just starting.
The Implication
If you're deploying agents at your company, ask what happens when you have ten of them. Or fifty. Can your customer support agent hand off a complex case to your engineering diagnostic agent? Can they share context without you building custom middleware every time?
The real test of BAND's thesis isn't whether agents need to communicate. It's whether companies will pay for a universal protocol instead of building point-to-point integrations themselves. History suggests they will—once the pain of fragmentation gets expensive enough. We're probably there.