Control AI spend before it controls you.

Yes — GetWrangler is built on a "never halt" principle: it never pauses or blocks live traffic regardless of spend level. Budget alerts are informational only, so a cost spike triggers a notification, not a forced passthrough, throttle, or upgrade block. This is a deliberate design choice, since blocking production traffic to control costs creates a worse outage risk than the cost overrun itself.

Yes. GetWrangler supports bypass mode, a per-token setting available anytime — including during your 14-day trial, with no subscription required — that routes traffic through full tracking and attribution infrastructure while preserving complete model capability with zero substitution. This is commonly used with GitHub Copilot CLI and Cursor's chat/plan traffic, where the value is spend visibility and attribution rather than automatic cost optimization. Claude Code and Codex CLI work differently: they connect through dedicated direct-passthrough routes that forward requests unchanged to your own provider credentials, with tracking-only behavior built in by design rather than a toggle you set.

Yes — GetWrangler supports shadow mode, a 14-day evaluation period where all requests pass through to your LLM provider completely unchanged. GetWrangler observes your traffic in the background, classifies it, and projects what optimization would have saved — without altering what your application actually receives. You see projected savings and routing behavior before you activate live optimization, at no risk to production traffic.

GetWrangler adds a brief classification step before your request reaches the model provider — this is what determines the most cost-effective model for the task. On average, this adds under one second of overhead, and it applies the same way whether you're using streaming or non-streaming requests. For deterministic and cached responses, you actually see lower total latency than calling your model directly, since the request never makes a round trip to the model at all. For latency-critical workloads, bypass mode skips classification entirely and routes your request directly to your specified model for the lowest possible latency — though you trade away the cost-optimization savings for that traffic.

If your total LLM API spend is under $200 per month and your goal is cost optimization, the platform fee likely exceeds what routing savings would deliver. But if you're using Claude Code, GitHub Copilot, or Codex CLI to build for clients and need to invoice them for that AI usage, spend level doesn't matter — GetWrangler gives your team per-project, per-client billing attribution for one flat price, regardless of how much or little you're spending.