Multi-Agent
Workflows & Swarms.
Replace rigid manual pipelines with autonomous multi-agent networks that think, collaborate, verify results, and execute end-to-end operational workflows 24/7.
How autonomous swarms execute tasks.
Goal Decomposition
The Orchestrator agent ingests business inputs and breaks tasks into a Directed Acyclic Graph (DAG).
Specialist Execution
Parallel worker agents (Research, SQL, Synthesis, QA) execute isolated tool calls in secure sandboxes.
Critique & Validation
A Critic agent rigorously grades outputs against deterministic schemas and business logic rules.
Action Dispatch
Final validated payload is pushed directly to your production APIs, ERP, or notification channels.
Engineered for enterprise production.
Hierarchical Supervisor & Worker Swarms
Autonomous supervisor agents that break down complex high-level business goals into sub-tasks, assign them to specialist agents, and evaluate output quality.
Stateful Memory & Cross-Session Checkpointing
Persistent state machines and vector-indexed episodic memory so multi-agent workflows resume flawlessly across days without losing task context.
Human-in-the-Loop (HITL) Guardrails
Configurable approval breakpoints for high-stakes actions (e.g. ERP transfers, financial refunds, database writes) with Slack & email interactive approvals.
Self-Healing & Error Retry Loops
Autonomous reflection agents that inspect stack traces, rewrite invalid SQL/JSON queries, and self-correct runtime errors before escalating.
Ready to deploy your agent mesh?
Book a technical scoping session with our multi-agent systems engineers.