Sistava

AI Multi-Agent Orchestration | Coordinate Specialist Employees

Custom AI Team

Coordinate specialist Employees on a shared goal

Multi-Agent Orchestration lets you run a team of specialist AI Employees on a single objective, with one supervisor handling handoffs and quality checks. A research Employee gathers facts, a writer drafts copy, an editor reviews tone, and a publisher ships the result. Each one stays in its lane and passes work forward when ready. You define the goal and the roster. The supervisor breaks the goal into sub-tasks, routes each one to the Employee with the matching Skills and Duties, and waits for results before composing the final output. Every handoff carries the context the next Employee needs, so nothing gets lost between steps. This beats giving one generalist Employee a giant prompt and hoping it covers everything. Specialists go deeper, mistakes get caught at the handoff, and the supervisor enforces the order of operations. You get a complete deliverable instead of a half-finished draft that needs human stitching.

Benefits

How It Works

  1. Step 1:
  2. Step 2:
  3. Step 3:
  4. Step 4:
  5. Step 5:
  6. Step 6:

At a Glance

< 2 min
Average handoff latency
6x
Throughput vs single Employee
24/7
Coordinated team coverage
70%
Reduction in revision cycles

Supervisor and specialist split

The supervisor Employee plans, routes, and reviews. Specialist Employees execute the sub-task they were given and return a result. This split keeps planning logic in one place and lets each specialist stay focused on its craft. When you tune a specialist, the supervisor inherits the improvement on the next run. When you change the supervisor, every team it runs benefits without touching the specialists. The two layers evolve independently, which makes the team easier to debug and extend over time.

Shared memory across handoffs

Every team has a memory store scoped to the current goal. Specialists write what they learned, what they decided, and what is still open. The next Employee in line reads the relevant slice when it picks up the next sub-task. Memory persists across the full goal, so the editor sees what the writer chose and why, and the publisher knows which review notes were addressed. This removes the prompt-stuffing pattern where each step has to repeat everything that came before.

Parallel and sequential steps

The supervisor analyzes the dependency graph between sub-tasks. Independent steps run in parallel to compress wall time. Dependent steps wait for their upstream input to land in shared memory before they start. You see the full plan before execution begins, including which Employee owns which step and which steps can run at the same time. This visibility makes it easy to predict cost and time before a long-running goal starts.

FAQ

How do Employees share information between steps?

Every Employee writes to a shared memory store keyed to the goal. The supervisor reads from it when assigning the next step, so context, decisions, and intermediate results travel with the work.

What stops Employees from stepping on each other?

The supervisor owns task assignment and order. Specialists only act when handed a sub-task, and conflicting outputs are reconciled by the supervisor before the next step runs.

Can I add or remove Employees from a running team?

Yes. Update the roster from the team page and the supervisor picks up the change on the next sub-task. Existing handoffs continue with the original assignees until they finish.

What happens if a specialist Employee fails a step?

The supervisor retries with adjusted context, escalates to a backup specialist, or pauses for human review based on the Duty you set for that failure mode.

Do I need a custom supervisor for each goal?

No. The default supervisor handles common patterns. You can write a supervisor Duty for a specific workflow when the routing logic gets domain-specific.