Is the AI model you're using real?
API relays routinely water down their upstream — quietly swapping the Claude / GPT you paid for with a cheaper model (Qwen, DeepSeek, a quantized variant), often prompted to claim it is still Claude. Panshi Sentinel catches that by behavioral fingerprint, end to end.
Upstreams leak
A relay buys real Claude today, then silently routes to a cheaper model tomorrow to widen margin. You never see the switch.
Disguised identity
A swapped upstream is told to answer "I am Claude." Asking the model who it is proves nothing — fingerprinting sees through it.
Silent quality loss
Your product degrades, your users churn, and you blame your own prompts — when the real cause is the model under you changing.
Two ways in
From a free spot-check anyone can run, to 7×24 continuous monitoring for operators and teams — detection only, catching upstream model substitution.
Panshi Sentinel · Free Check
A free behavioral-fingerprint checker. Paste your relay's answers — or run a one-file local CLI — and find out in seconds whether your Claude / GPT is genuine or substituted.
- ✓ No signup, key never leaves your machine
- ✓ Sees through disguised upstreams
- ✓ Genuine / Suspected-substitution / Inconclusive + evidence
Panshi Sentinel · Monitor
Continuous-monitoring SaaS for relay operators and heavy users / teams. Watch all your upstream channels around the clock and get alerted the moment a model is swapped or degraded.
- ✓ Scheduled probes + crypto verification per upstream
- ✓ Drift & substitution alerts + per-channel audit trail
- ✓ From $99 / mo · priced by upstream channel count
Why you can trust the verdict
Panshi Sentinel is built on a behavioral-fingerprinting method informed by published research on LLM identification — not vibes.
False positives on official endpoints in our testing — genuine models are never flagged as substituted.
Still identifies the real model even when the upstream is prompted to disguise itself as Claude.
Informed by published research on LLM identification, not self-reported model identity.
⚠️ Results are probabilistic signals, not legal proof. Quantized / distilled variants and models outside our reference set cannot be determined.