SERVICE / 03 — SYSTEMS
MULTI-AGENT
SYSTEMS
DELIVERED
Multiple AI agents in concert with shared memory and orchestration. One holds context, another decides, a third executes. Works where one agent chokes.
// WHAT IT IS
A multi-agent system isn't «5 bots». It's an architecture with roles: an orchestrator breaks down the task, worker agents execute, a supervisor validates, a memory layer holds context across sessions. Complexity like microservices, value like a department with tenure.
- Orchestrator agent — breaks the input task into steps, delegates to others.
- Worker agents — each in its own role (research, write, validate, execute).
- Memory layer — Postgres + vector store, shared context across agents.
- Supervisor / eval — a critic that catches hallucinations before production.
- Integrations — Telegram, CRM, databases, n8n workflows, your internal APIs.
// WHO IT'S FOR
- Teams who've shipped a single agent and are hitting the complexity wall.
- Sales + ops + research — three roles that need to chain into one flow.
- Businesses with long processes (lead → discovery → proposal → onboarding).
- Analytical workloads — research → synthesis → reporting in Slack.
// WHAT YOU GET
- Multi-agent system in production — orchestrator + worker agents + memory.
- Architecture doc — diagram, roles, API contracts, deploy plan.
- Eval suite per agent — so the system doesn't drift over time.
- Observability — logs, metrics, alerting (Langfuse or custom panel).
- 60 days of post-deploy support — this is a systemic, not trivial, object.
// HOW IT WORKS
// PRICING
Starter multi-agent system (3 agents, 1 memory layer) — $5,000-15,000. Complex (5-7 agents, multiple memory layers, n8n + custom backend) — $15,000-50,000+.
// FAQ
When do I need a multi-agent system vs. just one agent?
One agent — for one process with 5-15 steps. Multi-agent — when the process has multiple roles (research, decision, execution) or a long timeline (days / weeks). If unsure — start with a consultation, I'll tell you.
What stack do you use?
OpenAI / Claude / Hermes as the LLM core. LangGraph or a custom orchestrator in TypeScript. Postgres + pgvector for memory. n8n for workflow glue. Vercel / AWS / Fly for deploy. Stack picks the job, not the other way around.
How do you prevent hallucinations in a multi-agent system?
Supervisor agent + eval suite + structured outputs (JSON Schema / Zod). Every step is validated before being passed to the next. Without this the system drifts within a week.
Can you ship this in under 6 weeks?
MVP — yes, but a production multi-agent system in 2 weeks is brittle. I don't take projects like that. If the timeline is tight — we ship one agent first.
LET'S TALK ABOUT YOUR SYSTEM
Message SYSTEM on Telegram — in 30 minutes we figure out whether it's a multi-agent case or one agent will do.
→ Usually reply within 2 hours during business hours