Orchestra: The Infrastructure for a New Generation of Specialized AI Agents

Orchestra: The Infrastructure for a New Generation of Specialized AI Agents

For the past few years, the AI conversation has revolved around one question: which model is best? We believe the next phase will be defined by a different question: how do you organize, govern, and operate a workforce of agents?

Today, we are introducing a product direction for Orchestra: infrastructure for specialized AI agents, accessible from the conversational interface each person prefers.

From isolated chatbots to teams of agents

A marketing agent should not have to work in isolation from a sales agent. An operations agent should be able to ask finance for context. A support agent should be able to escalate a case to the right specialist and leave a verifiable record of what happened.

The paradigm changes when we stop treating an agent as a conversation and start treating it as a specialized member of an organization. An agent can have:

• a defined role and a focused set of capabilities;
• access only to the tools it needs;
• persistent context and working memory;
• the ability to collaborate with other agents;
• clear workflows and operating limits; and
• results that can be reviewed and traced.

Orchestra is the infrastructure that coordinates this system.

The interface does not have to be a single application

The user experience does not need to be locked inside one proprietary interface. Through MCP, Claude, ChatGPT, and other tool-enabled clients can become ways to access Orchestra.

A person could say:

Ask the marketing agent to prepare the campaign, have the legal agent review the risks, and ask finance to estimate the impact. Show me the decisions that need my approval.

The conversational client interprets the intent. Orchestra identifies the relevant capabilities, coordinates the work, applies permissions, records the execution, and returns the result.

This separates two layers that are usually bundled together:

• the conversational interface, where people express goals; and
• the operational infrastructure, where agents work safely and together.

The interface can change. The organization of agents remains.

A new paradigm for business software

Traditional software is organized around applications: CRM, help desk, project manager, content platform. In the model we are building, the primary unit can become an operational capability: research, drafting, analysis, review, execution, and escalation.

The application is no longer the center of gravity. A controlled network of agents, connected to the company’s systems, becomes the operating layer.

That changes the way work gets delegated. Instead of asking people to move information between many tools, a company can delegate an objective to a digital team that knows how to coordinate the work. This is not about removing human judgment. It is about making the work between systems easier to direct, observe, and improve.

Why Orchestra is early to this category

We are building Orchestra to be among the first platforms to treat specialized agents as an infrastructure layer independent of any single AI interface. The distinction is not another chat window. It is everything that has to happen after someone writes the prompt:

• which agent should act;
• what context it can use;
• which tools it is authorized to access;
• which other agents should participate;
• what requires human approval;
• how the result is audited; and
• how the system recovers when something goes wrong.

This is the Orchestra thesis: models are reasoning engines, interfaces are terminals, and Orchestra is the operational layer that turns isolated capabilities into an organization of agents.

We are not claiming that no one has built an agent or exposed a tool before us. Our claim is more specific: Orchestra is being designed around the idea that specialized agents should be coordinated, governed, and operated as a durable layer beneath the interfaces people already use.

The opportunity — and the responsibility

A multi-agent infrastructure layer creates significant opportunities: configurable teams, reusable agents, shared memory, auditable workflows, deep integrations, and a catalogue of specialized capabilities.

It also raises the bar for security. A conversational instruction can trigger a real-world action. The product therefore needs identity and permissions at every layer, a clear separation between reading and writing, approvals for sensitive actions, limits on scope, protection against prompt injection, and a complete record of execution.

Autonomy is useful only when it can be understood, controlled, and stopped.

What we are building

The vision for Orchestra rests on three layers:

• Execution core: agents, tasks, memory, tools, workflows, and auditability.
• API and MCP: a standard way to discover capabilities, check status, and execute actions from external clients.
• Native UX: a visual space to manage teams, review results, recover executions, and stay in control.

MCP expands access; it does not replace governance. Claude, ChatGPT, and other clients can be excellent work terminals while Orchestra maintains identity, permissions, coordination, and traceability.

The beginning of a new category

We are entering a period in which a company will operate not only with software, but with a specialized and coordinated digital workforce. The value will not come from having more agents. It will come from being able to trust them.

Orchestra is being built for that layer: infrastructure that is open to the conversational interfaces people already use and designed for agents to work together in production.

This is the beginning of a new category: operational infrastructure for organizations of agents.