Several agents, one operation:
coordinated instead of colliding
A business running several AI agents, one for support, one for reporting, one for data entry, ends up with agents that do not know about each other. They duplicate work. Or leave a task half-done at the boundary. We build an orchestrator agent that routes work to the right specialist and carries state across the handoff. It keeps a clear audit trail of which agent did what.
When agents do not know about each other
A business that adds AI agents one at a time, a support bot here, a reporting script there, usually ends up with agents operating in isolation. A support agent might answer a customer without knowing a fulfilment agent already flagged the same order as delayed. The customer gets two different, slightly contradictory answers from the same business within an hour.
Work also gets duplicated or dropped at the boundary between agents. A task that should flow from a qualification agent to a scheduling agent can stall if nobody built the handoff. It can get picked up by both if nobody built the conflict check. Either failure stays invisible until a customer or a manager notices something went wrong.
And nobody has one place to see what every agent across the business actually did today. Each agent might log its own actions, but without a shared view, working out why an outcome happened means checking several systems and reconstructing the sequence by hand.
What we build
We build a router agent that sits in front of your specialist agents. It decides which one should handle an incoming piece of work, based on rules your team defines, and hands it off with the full context attached. The receiving agent never has to re-ask the customer or re-derive what already happened. State carries through the whole chain: if a task passes through three agents, all three see the same history.
Where two agents could plausibly act on the same task, a conflict resolution rule decides which one takes it. Anything the rule cannot resolve routes to a human, instead of letting both agents act independently. Every handoff and decision gets written to a shared audit log. A manager can see the exact sequence of agents and actions behind any outcome.
Typical integrations: whatever messaging, CRM or internal tools your existing or planned specialist agents already use, with the orchestrator layered on top as the coordination point.
What stays with humans
Defining what each specialist agent is responsible for, and what counts as a conflict between them, is a decision your team makes and can revise any time. Anything outside the scope the orchestrator and specialists were built for escalates to a person, rather than getting forced through the nearest matching agent. Reviewing the orchestrator’s routing decisions periodically, and adjusting the rules as your operation changes, stays an ongoing task for your team. The audit log supplies the data to do it from.
Guards
Every routing decision, handoff and specialist action is logged centrally, so nothing happens across the agent system without a traceable record. Rate limits and budget caps apply per agent and across the whole system, so a malfunctioning agent cannot run away with cost or volume. The orchestrator runs in a shadow mode against real incoming work before it is allowed to make live routing decisions. A kill switch can pause any single agent, or the entire system, in one message.
Price and timeline
| Option | Price | What it covers | Timeline |
|---|---|---|---|
| Single automation | from $1,500 | Router agent, 2 to 3 specialist agents, shared audit log | 2 to 4 weeks |
| Department package | from $4,500 | Full orchestration across 5+ agents, conflict rules, dashboard, escalation design | 6 to 10 weeks |
Running cost is usually $50 to $200 a month in model usage depending on task volume and agent count, with a budget cap set before launch.
Related
This pairs well with agent approval queue and audit log for the governance layer on top of the orchestration. It also pairs with agent cost and quality monitoring for keeping the whole system healthy over time. See the AI agents service page and the automation-everything overview for full package details. For real multi-agent builds, see the ProBay own marketplace AI agent team case study and the seven-channel AI sales agent case study.
Running several agents that do not talk to each other? Get in touch and we will map how your current agents and processes actually connect.
Tired of doing this by hand? We can take the whole routine off your team, not only this step: Routine takeover, from $400 →
FAQ
How much does it cost to set up multi-agent orchestration?
From $1,500 for a router agent and two to three specialist agents working together, live in 2 to 4 weeks. Larger operations with five or more agents and complex handoff rules usually run $3,000 to $6,000.
How long before it is live?
2 to 4 weeks, depending on how many existing agents or processes need wiring into the orchestrator and how much state needs to pass between them.
Do I need to already have AI agents in place?
No. We can build the specialist agents and the orchestrator together, or wire an orchestrator around agents and scripts you already have running.
What happens when two agents could both act on the same task?
A conflict resolution rule your team defines decides which agent takes it, or routes it to a human if the rule does not clearly resolve it. Neither agent acts alone and creates a duplicate or contradictory outcome.
Is the whole system auditable?
Yes. Every handoff, decision and action across every agent is logged in one place. You can trace any outcome back through the exact sequence of agents that touched it.