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| title: AgentMesh — AI Agent Cost Savings Calculator | |
| emoji: 🕸️ | |
| colorFrom: indigo | |
| colorTo: blue | |
| sdk: gradio | |
| python_version: "3.11" | |
| app_file: app.py | |
| pinned: true | |
| license: apache-2.0 | |
| tags: | |
| - ai-agents | |
| - llm | |
| - cost-optimization | |
| - governance | |
| - enterprise | |
| - langgraph | |
| - crewai | |
| - openai-agents | |
| - anthropic | |
| - token-budget | |
| # AgentMesh — AI Agent Governance & Cost Savings Calculator | |
| **The governance plane for AI agents — policy, budget, and audit across every framework.** | |
| This Space demonstrates how AgentMesh reduces AI agent costs by 60–90% in enterprise deployments. | |
| ## What is AgentMesh? | |
| AgentMesh is an open-source framework-agnostic sidecar that enforces: | |
| - **Token Budget Enforcement** — Hard limits, no surprise bills | |
| - **Dynamic Model Routing** — Auto-route to cheaper models as budget is consumed | |
| - **Semantic Caching** — Cache near-duplicate queries (10–40% savings) | |
| - **Circuit Breaker** — Kill runaway loops before they drain budgets | |
| - **Tamper-Evident Audit Trail** — Ed25519-signed compliance for EU AI Act, HIPAA, SOC 2 | |
| - **Policy-as-Code** — YAML governance enforced at runtime, not post-hoc | |
| ## Usage | |
| ```bash | |
| pip install agentmesh-proxy | |
| ``` | |
| ```python | |
| from agentmesh import AgentMesh | |
| from agentmesh.policy.engine import Policy | |
| mesh = AgentMesh(policy=Policy.from_yaml("policy.yaml")) | |
| governed_graph = mesh.wrap_langgraph(your_graph) | |
| ``` | |
| ## GitHub | |
| [github.com/anilatambharii/agentmesh](https://github.com/anilatambharii/agentmesh) | |