Enterprises are deploying specialised AI agents across engineering, support, security and operations. The difficult problem begins when those agents need to collaborate. They run on different clouds, use different frameworks and report to different owners, leaving employees to connect context and resolve failures manually.
Band, a startup in Tel Aviv and San Francisco, has emerged from stealth with a $17 million seed round to build an interaction layer for autonomous systems. Its premise is that agents need the equivalent of the API gateway or service mesh that earlier distributed software required.
Protocols such as Model Context Protocol and agent-to-agent standards define how systems connect. They do not by themselves govern routing, authority, recovery, cost or human oversight in production.
Protocols provide a handshake, not an operating environment
Enterprise heterogeneity is unlikely to disappear. Teams will continue choosing different models, tools and clouds. Point-to-point connections may work for a pilot, but each new agent multiplies integration and maintenance work.
An interaction layer can provide routing, error handling and shared policies without forcing every participant onto one framework. It should know which agent may delegate a task, what context can cross a boundary and when a person must approve the exchange.
This is especially important when older corporate systems are involved. A billing agent and compliance agent might act on the same account simultaneously, creating locks or conflicting records. Central coordination can sequence actions and prevent an agent from exceeding its capability.
Band positions its platform as cloud- and framework-agnostic, concentrating on operation rather than another development toolkit.
Cost and context need circuit breakers
Multi-agent workflows can generate continuous calls to expensive models. A routing failure or negotiation loop may consume a cloud budget rapidly without producing useful work.
Interaction infrastructure can enforce token and compute thresholds, ending conversations that exceed the value of the task. Cost limits should be defined alongside authority, not discovered after a runaway bill.
Context transfer creates another risk. Agents often summarise information for one another, which can degrade details and obscure the original source. Moving data between isolated vector stores may also expose material one participant is not authorised to see.
A shared mesh should preserve lineage to cryptographically verifiable records while enforcing specific access controls. If a support agent hands a case to diagnostics, the recipient needs relevant history—not an uncontrolled copy of everything the first agent could access.
Comprehensive logs let auditors trace automated decisions to their origin. They also help engineers distinguish a model error from corrupted or incomplete context.
The interaction mesh becomes a security boundary
Governance cannot remain an optional dashboard after agents begin delegating and acting across organisational lines. The execution layer must inspect chains of authority, constrain tools and keep human intervention available.
This does not require one central model managing the enterprise. Specialised agents can retain different architectures and strengths while a common layer governs their interactions.
The analogy to a service mesh is useful but incomplete. Agent communication carries interpretation and uncertain intent, not only predictable service requests. Policies need to account for what a task means, which evidence supports it and whether the recipient may perform the requested action.
Band’s funding reflects a market moving from individual assistants toward networks of autonomous participants. The commercial opportunity lies in making those networks dependable before integration cost, data contamination and uncontrolled inference overwhelm their value.
Companies should not measure progress by the number of agents deployed. They should ask whether agents can exchange context accurately, respect financial and authority limits, recover from failure and produce an audit trail a person can understand.
Interaction infrastructure is the layer that turns those questions into enforceable runtime behaviour. Without it, multi-agent automation remains a collection of impressive components held together by human operators. With it, enterprises gain a credible route to collaboration that is governed as carefully as the systems being connected.
