The use case: how Inkeep deploys SigNoz
Inkeep built SigNoz into its open-source AI agent framework so that agents built with it emit OpenTelemetry traces and metrics by default. Inkeep engineers and framework users use SigNoz to debug multi-step agent runs, query traces programmatically through the Trace API, and track LLM latency, token usage and error rates, both locally with Docker and in SigNoz Cloud.
In the customer’s words
The parity between local development and production was the deciding factor for us. Our engineers can spin up SigNoz locally with Docker to debug agent loops on their laptops, and then get that exact same visibility in production. It aligns perfectly with our 'push/pull' workflow - you can fix a performance bottleneck locally and be confident it's solved in the cloud.Other AI tools used by Inkeep
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AWS BedrockDeclared
Azure OpenAIDeclared
ComposioDeclared
Elastic CloudDeclared
Google Sensitive Data ProtectionDeclared
Google WorkspaceDeclaredSigNoz users in Artificial Intelligence
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Based on SigNoz’s published case study. We check the public evidence; the results are reported by the vendor.
signoz.io- Last checked
- Nov 13, 2026
Open source capture What the story claims, and what we checked
What we compared with the page.
- The passage quoted aboveChecked
Copied word for word from the page, near the name of Inkeep.
- Inkeep uses SigNozChecked
Confirmed line.
- The result itselfNot checked
We quote it; we did not measure it.
Since SigNoz is OpenTelemetry-native, the integration is straightforward. No proprietary agents, no vendor-specific SDKs. The framework emits OpenTelemetry spans, SigNoz ingests them. Done.