diff --git a/server/utilities/opentelemetry.mdx b/server/utilities/opentelemetry.mdx
index 2779851..9943da6 100644
--- a/server/utilities/opentelemetry.mdx
+++ b/server/utilities/opentelemetry.mdx
@@ -151,6 +151,41 @@ exporter = OTLPSpanExporter(
 
 See our [Langfuse example](https://github.com/pipecat-ai/pipecat-examples/tree/main/open-telemetry/langfuse) for details on configuring this exporter.
 
+### Opik (LLM observability)
+
+[Opik](https://www.comet.com/opik/) is an observability, evaluation, and optimization platform for LLM and agent workloads. Pipecat's span hierarchy maps directly onto Opik's trace explorer, allowing you to replay conversations, inspect service-level metrics, and monitor latency and cost for every turn. See our [Opik example](https://github.com/pipecat-ai/pipecat-examples/tree/main/open-telemetry/opik) for a reference implementation.
+
+1. Make sure the HTTP OTLP exporter is available (installed automatically with `pipecat-ai[tracing]`).
+2. Configure your environment variables for the Opik deployment you use:
+
+```bash wordWrap
+# Opik Cloud
+export OTEL_EXPORTER_OTLP_ENDPOINT=https://www.comet.com/opik/api/v1/private/otel
+export OTEL_EXPORTER_OTLP_HEADERS='Authorization=<your-api-key>,Comet-Workspace=<workspace>,projectName=<project>'
+
+# Opik Enterprise
+export OTEL_EXPORTER_OTLP_ENDPOINT=https://<your-comet-domain>/opik/api/v1/private/otel
+export OTEL_EXPORTER_OTLP_HEADERS='Authorization=<your-api-key>,Comet-Workspace=<workspace>,projectName=<project>'
+
+# Self-hosted Opik
+export OTEL_EXPORTER_OTLP_ENDPOINT=http://localhost:5173/api/v1/private/otel
+export OTEL_EXPORTER_OTLP_HEADERS='projectName=<project>'
+```
+
+3. Use the HTTP exporter without additional parameters—the headers and endpoint are picked up from the environment:
+
+```python
+from opentelemetry.exporter.otlp.proto.http.trace_exporter import OTLPSpanExporter
+from pipecat.utils.tracing.setup import setup_tracing
+
+setup_tracing(
+    service_name="pipecat-opik-demo",
+    exporter=OTLPSpanExporter(),
+)
+```
+
+Opik automatically groups spans by `conversation_id`, enriches them with per-service metrics (LLM token usage, TTS character counts, STT transcripts, TTFB), and records any errors raised by your pipeline. Visit the [Pipecat + Opik guide](https://www.comet.com/docs/opik/tracing/integrations/pipecat) for screenshots and a full walkthrough.
+
 ### Console Exporter (for debugging)
 
 The console exporter can be enabled alongside any other exporter by setting `console_export=True`: