AgentMux works wherever multiple agents need to research, deliberate, verify each other, and stay under human control. From code to contracts to compliance.
Assign agents to separate research tracks - one reviews case law, one analyzes contracts, one checks regulatory compliance. Each agent works independently, then they verify each other's findings through interpane communication.
Spin up agents to explore different approaches in parallel. Have them deliberate, challenge each other's conclusions, and converge on verified results.
See every tool call, file write, and network request an agent makes. Set constraints that trigger alerts. Know exactly what your agents are doing to your production codebase.
Your product runs on agents. AgentMux gives you the observability layer to debug agent behavior, tune guardrails, and understand why Agent #4 keeps reverting Agent #2's work.
Point agents at your issue backlog. Watch them triage, reproduce, and propose fixes. Review their PRs from AgentMux instead of your inbox.
Run compliance checks across multiple domains in parallel. Each agent specializes in a regulation area, and they cross-verify findings before reporting.
80% of companies with active AI agents have experienced applications acting outside intended boundaries. AgentMux gives you platform-level observability that goes beyond application logging - immutable, centralized, and tied to identity.
Agents writing Terraform, CDK, and Kubernetes manifests need a supervisor. AgentMux lets you watch infrastructure changes in real time, catch dangerous modifications before apply, and coordinate agents across deploy pipelines.
Data pipelines are perfect for multi-agent workflows. One agent builds the ETL, another validates the output, a third writes the tests. AgentMux lets you see all three working and catch data quality issues before they propagate.
Point agents at your codebase and your docs. One agent identifies gaps between code and documentation, another drafts updates, a third verifies accuracy. The docs stay in sync because the agents never stop watching.
When production is down, you need answers from multiple angles simultaneously. Assign agents to logs, metrics, recent deploys, and configuration changes. See their findings converge on a root cause in real time.
Use AgentMux as a teaching tool. Students watch agent reasoning, tool usage, and decision-making unfold step by step. Side-by-side panes let you compare how different prompts or models approach the same problem.
Free and open source. ~152MB portable — no install needed.
Early alpha. Features may be incomplete or unstable. AI agents generate content that may be inaccurate — always review outputs. Report issues