Signal
Overview
Observability for production agent workflows with traces, cost breakdowns, quality scores, alerts, replays, evals, and structured logs.
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Signal is an observability tool for teams running AI agents in production. According to its official product page, teams add the SDK to capture agent runs, tool calls, LLM requests, traces, structured logs, costs, latency, quality scores, replays, and alerts. It is positioned as monitoring for agent workflows across frameworks such as LangChain, CrewAI, AutoGen, custom scripts, and raw API calls. Signal supports use cases such as finding silent agent failures, detecting runaway token costs, auditing what an agent did during a customer request, replaying past runs, monitoring latency and quality drift, and sending alerts through Slack, PagerDuty, or webhooks. The product is currently offered for early access teams, with public launch stated for Q3 2026 on the official page.
Autonomy level
50%
Comparisons
Custom Comparisons
Some of the use cases of Signal:
- Monitoring production agent runs in real time
- Tracing multi-agent workflows and tool calls
- Tracking token costs and identifying expensive runs
- Replaying failed or unusual agent executions for debugging
- Setting alerts for latency spikes, quality drops, and cost jumps
- Running built-in evaluations such as hallucination checks, format validation, and safety scoring
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Describe the job. Get an AI worker you can actually message.
We create the setup, keep it running after your laptop closes, and save its memory. Test in the browser, then add Telegram, WhatsApp, or Slack.
Plans start at $29/month. Cancel anytime.
Hosted agent
OpenClaw or Hermes