Omium
Observability and recovery for production AI agents
The Technical Challenge
Autonomous agents operating in production frequently fail silently during multi-step tool calls, leaving engineers without clear trace visibility, token cost attribution, or the ability to restart failed workflows from the last valid checkpoint.
What We Designed & Shipped
MarketBaddies built the Omium telemetry platform: an observability dashboard that visualizes agent thought processes, step latencies, API payload transformations, and checkpoint recovery states.
Engineering Breakdown & Implementation
- High-throughput event ingestion API capturing distributed agent spans with minimal overhead
- Graph-based visual workflow debugger rendering multi-agent interactions in real time
- Deterministic state snapshots allowing engineers to replay failed agent steps with adjusted prompts
- Token usage and financial cost attribution down to the individual tool invocation
- Live at omium.ai providing visibility into enterprise agent pipelines
- Debug time for failed multi-step AI workflows reduced from hours to minutes
- Detailed cost-per-step visibility preventing unexpected LLM token overruns
Core Deliverables Handed Over
Observability Web Console
Interactive dashboard for browsing agent execution graphs, spans, and error traces.
Lightweight Python Telemetry SDK
Zero-friction decorator-based SDK for instrumenting custom agent workflows in two lines of code.
State Checkpoint & Replay System
Time-travel debugging engine to inspect and re-execute failed steps.
Services Used on This Project
AI Agent Development
Autonomous AI agents that execute complex business workflows, automate sales qualification, and operate 24/7.
Business Automation Systems
End-to-end workflow automation connecting your CRM, database, marketing channels, and internal tools.
SaaS Product Development
Scalable multi-tenant Software-as-a-Service platforms built from concept to recurring revenue.
More Production Systems Shipped
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