Aiveris Cost Clinic
Upload Claude/API logs. Get exact engineering steps to cut LLM spend.
A paid diagnostic for teams with real LLM usage evidence. We turn safe exports, traces, prompts, and architecture notes into ranked findings, estimated savings, risk, confidence, and a proof path your engineers can run.
Supported artifacts
Bring evidence, not vibes.
Cost waste hides in routing, retries, prompt bulk, tool loops, cache misses, retrieval bloat, and weak attribution. The diagnostic starts from the safest useful artifact set you can share.
Anthropic/Claude usage and OpenAI/Gemini/Bedrock exports
Billing + usageInvoices, console exports, provider CSVs, token totals, cache read/write fields, model names, latency, status, retries, and route metadata.
Langfuse/Helicone/LiteLLM/LangSmith traces
ObservabilityTrace exports showing workflows, tools, model calls, retry behavior, cache behavior, request status, and cost attribution.
JSONL/CSV logs, prompts, tool schemas, RAG config
Engineering contextSampled request logs, prompt templates, agent instructions, tool definitions, retrieval settings, chunking rules, vector-store notes, and workflow diagrams.
metadata-only exports and synthetic/sample exports
Least sensitiveNo prompt text required when metadata is enough. A synthetic/sample export can validate the report shape when production content cannot leave your company.
Safe intake
Share the least sensitive evidence that can still support a real finding.
This is not an upload portal. Start with a call or email, choose an intake mode, and send only the artifacts your team is allowed to share.
Local/client-side redaction
Redact names, emails, account IDs, customer text, secrets, URLs, and document excerpts before Aiveris sees files. Keep cost, token, workflow, retry, latency, and model metadata.
metadata-only mode
No prompts, no outputs, no customer text. Useful fields include model, tokens, cache reads/writes, cost, latency, retry count, tool count, route, workflow ID, environment, and status.
delete-after-analysis
Choose report-only, delete-after-analysis, or 30-day follow-up retention before sharing. Raw artifacts are used only for the diagnostic and review call.
no training on uploads
Aiveris does not use buyer uploads to train foundation models and will not publish, resell, or use artifacts as marketing evidence without separate written approval.
synthetic/sample export
If production data cannot leave the company, send fake rows shaped like production usage. Conclusions may be lower-confidence, but the diagnostic format can still be tested.
No secrets or PII
Do not upload or email API keys, tokens, credentials, private keys, passwords, session cookies, customer PII, regulated data, or privileged internal URLs unless separately scoped in writing.
Diagnostic output
A report your engineering team can execute.
The deliverable is not a generic cost dashboard. It is a ranked engineering report that names what to change, why it matters, how risky it is, and how to prove the savings.
Pricing test
Pay for a diagnostic before funding a platform.
If the artifact set is too thin, Aiveris will decline the diagnostic rather than sell a vague report. Fog sold by the pound is still fog.
Free qualification review
We review spend range, artifact types, security posture, and the decision owner. If there is not enough evidence for a useful report, we say so.
Diagnostic Lite
Up to 3 artifact types, 5 ranked findings, and a 30-minute review call. Built for teams testing whether the diagnostic has bite.
Diagnostic Standard
Up to 6 artifact types, 8 to 12 ranked findings, a 45-minute review call, and one follow-up clarification pass.
Implementation sprint
Optional after the report, not before it.
If the report finds credible savings, Aiveris can help implement the top fixes: routing, prompt compaction, cache breakpoints, retry policy, attribution metadata, batch movement, or eval gates. The report earns that work. The dashboard does not.
Reject this if you want a dashboard first.
- You want generic "use a cheaper model" advice.
- You cannot share raw, redacted, metadata-only, or synthetic evidence.
- You want upload handling, auth, billing, queues, or a monitoring dashboard before the diagnostic proves value.
- You need unsupported compliance assurances before scoping the data posture.
Start here
Send the spend problem. Not the raw logs.
Book a 30-minute qualification call or email a short note with your monthly LLM spend range, providers, artifact types, security constraints, and the cost issue that forced the conversation.