For character.ai infrastructure and model engineering teams
Character.AI serving failure: ROCm loading, routing or cache pressure?
Preserve backend identity and request-to-worker mappings. Distinguish a resolved compatibility example from a new serving incident before escalating a device fault.
Free 30-day Team evaluation. No card or automatic subscription. Work email verification required.
Replay a resolved Character.AI workflow incident
Upload your log file. Review the selected evidence and masking, then run diagnosis. Keep the original log for any follow-up questions.
Before uploading, review cloud data handling and local options.
Upload your log file. Large files are processed in your browser. Only selected evidence is submitted when you run diagnosis.
Try Denpex for 30 days. FREE.
No credit card. No automatic subscription. See whether Denpex helps with an incident you already understand.
Start your free 30-day Team evaluation
Up to 50 diagnoses a day for 30 days. Verify your work email to activate an eligible company evaluation, then replay a resolved incident and compare the evidence and next steps with your team's confirmed cause.
What a useful evaluation should establish
Compare one incident your team has already resolved with the first failure, quoted evidence and remaining questions. Begin with this question: Is this an AMD ROCm deployment or another backend? Only assign a process, device or recovery state when the submitted evidence establishes it.
Is this an AMD ROCm deployment or another backend?
Evidence to compare: Actual accelerator vendor, serving-image revision and first model-load exception.
The newer published example uses AMD hardware. Preserve that vendor boundary and retain unsupported hardware conclusions as open questions rather than applying NVIDIA-specific containment.
Did the failure begin during loading or parallel execution?
Evidence to compare: Model-loading completion, TP and EP configuration and the first retained traceback.
The published compatibility issues crossed loading and parallelism boundaries. Identify the current failing stage instead of assuming an old configuration fix remains applicable.
Did routing delay a request or did its worker exit?
Evidence to compare: Redacted request-to-replica mapping, queue timing and corresponding worker exit status.
A slow first token can reflect routing, queueing or execution. A cache observation alone neither identifies the failed worker nor establishes exhausted device memory.
Use Denpex alongside your existing telemetry tools to investigate submitted incident evidence. With monitoring configured on a supported plan, detected failures can trigger alerts and an automatic diagnosis from the captured evidence.
Inside Denpex
See the evidence, not just the claim
Follow the causal chain, inspect the quoted evidence and prepare the next handoff. These actual product captures use founder-account examples and the VS Code extension, with the source identified under each image. Open a capture to inspect it at full size.
Follow the failure through the cascade

Prepare the hardware escalation

Ask for the evidence that is missing

Keep the investigation in the editor
