Why AI agents need a universal orchestrator to scale beyond isolated tools

The generative AI boom has unlocked unprecedented automation, but many enterprises now face a hidden crisis: their AI agents can’t work together. Systems built on LangChain, CrewAI, or proprietary frameworks often operate in silos, forcing developers to manually bridge gaps with fragile code or manual handoffs. This fragmentation threatens to stall the next phase of AI-driven productivity—unless a universal layer emerges to connect these digital workers.

Enter BAND, a newly launched startup that just secured $17 million in Seed funding to act as the “interaction infrastructure” for AI agents. The company, officially named Thenvoi AI Ltd., aims to replace today’s ad-hoc integrations with a deterministic communication framework that treats AI-to-AI collaboration as a first-class problem—not an afterthought.

“Agents need to communicate like humans do, but the solutions we have today weren’t designed for their non-deterministic nature,” explained Arick Goomanovsky, co-founder and CEO of BAND, in an interview with VentureBeat. “API integrations alone won’t solve this. We need a new layer of abstraction.”

The agentic mesh: A new architecture for AI collaboration

BAND’s core innovation is the agentic mesh, a two-layer architecture designed to handle the chaotic reality of AI interactions. Unlike human-to-human tools like Slack—which force agents to re-enter context after failures—BAND’s system maintains continuity by design.

The mesh’s interaction layer enables three critical functions:

• Multi-peer collaboration: Agents can form shared “rooms” where a planning agent, coding agent, and QA agent synchronize context in real time. This full-duplex communication avoids the bottlenecks of peer-to-peer or client-server models.

• Deterministic routing: BAND rejects the idea of using LLMs to route messages, which could introduce the same unpredictability the platform aims to eliminate. Instead, it relies on a patent-pending architecture to guarantee reliable delivery.

• Scalability via proven infrastructure: To handle the anticipated explosion of agentic traffic, BAND’s backend leverages the same stack used by global messaging platforms like WhatsApp and Discord. This ensures the system can scale to billions of messages as digital identities surpass human ones.

The second layer, the Control Plane, acts as the gatekeeper for enterprise-grade deployments. It enforces governance rules, manages identity propagation, and prevents unauthorized data access.

• Authority boundaries: Organizations can define strict rules on which agents interact and under what conditions.

• Credential traversal: If a human requests information from Agent A, which delegates to Agent B, BAND ensures Agent B only accesses data the user is authorized to see. This solves a major security challenge in multi-agent systems.

Framework-agnostic and cloud-agnostic: Avoiding the vendor trap

BAND positions itself as the neutral middleware that prevents enterprises from being locked into a single AI provider’s ecosystem. In a market where hyperscalers like OpenAI and Anthropic push proprietary tools, BAND offers flexibility to mix models—open source, fine-tuned, or custom—based on task requirements.

“The beauty of our platform is that it doesn’t matter where agents run or how they were built,” Goomanovsky said. “We can band them together, let them discover each other, delegate tasks, and communicate bidirectionally.”

This independence is critical as competitors like OpenAI’s Workspace Agents and Anthropic’s Claude Managed Agents enter the space. BAND’s role as an independent platform allows enterprises to avoid dependency on any single vendor.

Real-world use cases: From code reviews to customer onboarding

BAND’s traction is strongest in tech-driven industries like telecom, finance, and cybersecurity. The most common applications today involve coding workflows, where different agents excel at distinct tasks:

• Planning and execution: Developers often pair a model like Claude for high-level planning with Codex for code generation and review. BAND enables these agents to collaborate in real time.

• Cross-boundary automation: Enterprises are using BAND to connect disparate systems. For example, a Workday agent might onboard a new hire, then trigger a ServiceNow ticket for equipment, which a purchasing agent finalizes—all without manual intervention.

To accommodate enterprise security needs, BAND offers three deployment models:

• SaaS: A cloud-based API for quick integration.

• Private cloud/on-premise: Full control over data residency and compliance.

• Edge deployment: Lightweight enough to run on drones or other resource-constrained devices.

The road ahead: Toward a unified agentic economy

The AI agent ecosystem is at a crossroads. Without a way to unify disparate systems, the promise of scalable automation risks stalling. BAND’s middleware could be the missing link, transforming isolated agents into a cohesive workforce.

As Goomanovsky noted, “The goal isn’t just to connect agents—it’s to create an economy where they can dynamically form teams, solve problems, and scale without human bottlenecks.” With $17 million in funding and early adopters in high-stakes industries, BAND is betting big on this vision. The next phase will determine whether enterprises embrace this universal orchestrator—or double down on fragmented, vendor-specific solutions.