Multi Agent Systems

Multi Agent Systems
AI Teams That Work Together

Some problems are too complex for a single AI agent. A multi agent system breaks complex workflows into specialized tasks handled by purpose built agents that communicate and coordinate autonomously. One agent researches, another writes, a third reviews, and an orchestrator manages the entire flow. The result is enterprise grade automation that handles end to end processes no single agent could manage alone.

21 day delivery
Full observability
Full source code

What This System Does

Multiple specialized AI agents coordinating on complex workflows. Each agent does what it does best, and the orchestrator keeps everything in sync.

Agent orchestration that coordinates multiple specialized agents working on a shared workflow
Task delegation with automatic routing to the best agent based on task type and complexity
Shared memory and context passing so agents build on each other's work without repetition
Hierarchical agent teams with supervisors that review, correct, and approve subordinate outputs
Inter agent communication protocols for handoffs, status updates, and escalation
Retry and fallback logic when an agent fails, with graceful degradation for partial completions
Execution visibility with a real time dashboard showing each agent's status, inputs, and outputs
Permission boundaries ensuring each agent only accesses the tools and data its role requires
Persistent workflow state that survives restarts and allows long running multi day processes
Performance analytics per agent: success rate, latency, cost, and output quality scores
Parallel execution where independent subtasks run simultaneously to minimize total completion time
Configurable workflow definitions with visual builder for non technical team members

Measured ROI

End to end

Process Automation

Complex multi step workflows handled without human intervention

10x more

Throughput

Parallel agent execution processes work orders simultaneously

Automatic

Error Recovery

Failed steps retried or rerouted without manual intervention

5x output

Team Capacity

Human team focuses on exceptions while agents handle the routine

Tech Stack

LangGraph
Agent orchestration
OpenAI / Claude
Agent reasoning
Redis
Message bus
PostgreSQL
Workflow state
BullMQ
Task queue
Pinecone
Shared memory
Hono
API server
Railway
Hosting

21 Day Build Timeline

Day 1 to 3

Workflow Design

Map end to end process, identify agent roles, define communication protocols, design state machine.

Day 4 to 7

Agent Development

Build specialized agents, implement shared memory, configure tools and permissions per agent.

Day 8 to 10

Orchestration

Orchestrator logic, task routing, parallel execution, retry and fallback, state persistence.

Day 11 to 13

Integration

External system connections, monitoring dashboard, alerting, workflow builder interface.

Day 14 to 17

Testing

End to end workflow testing, failure scenario simulation, load testing, cost optimization.

Day 18 to 21

Launch

Production deployment, gradual rollout, performance tuning, team training on monitoring.

Multi Agent System

$8,000

21 day delivery • Full orchestration • 30 day support

Simple 2 agent systems from $4,000 • Enterprise from $20,000

Build Your Agent System

See a Multi Agent Platform We Built

ContentForge: a multi agent content platform where research, writing, editing, and SEO agents collaborate to produce publication ready content at 5x the speed of a human team.

Read the Case Study

Frequently Asked Questions

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50+ products shipped$10M+ funding raised2-week delivery

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