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What to Expect from GetWrangler
Savings depend on your workload. Here is an honest breakdown.
Section 1
How Savings Are Generated
GetWrangler uses four mechanisms to reduce your AI costs. Three are live today. One is coming soon.
* GetWrangler provides access to major frontier models (Claude, GPT-4o, Gemini) via a client-owned Abacus.ai account, plus native direct endpoint support for Anthropic, OpenAI, and Google APIs via vault-stored keys and custom endpoints.
Section 2
Savings by Workload Type
Savings vary significantly by task. High-repetition and structured workloads save the most. Complex reasoning and architecture work saves the least — those tasks genuinely need a strong model.
The ranges below apply to code-related tasks running through your own API-integrated product — for example, a code review, documentation, or debugging feature you've built and call directly with your API key. If you're tracking spend from coding assistants like GitHub Copilot CLI, Cursor, Claude Code, or Codex CLI instead, see the Coding Tools Guide — routing and savings behavior differs there.
| Task type | Typical savings | Primary mechanism |
|---|---|---|
| Boilerplate generation | 60–75% | Cache + tier routing |
| Code review / lint | 40–60% | Tier routing |
| Documentation generation | 50–70% | Cache + tier routing |
| Debugging assistance | 20–35% | Tier routing (complex) |
| Architecture decisions | 10–20% | Strong model required |
| Task type | Typical savings | Primary mechanism |
|---|---|---|
| FAQ / repeated questions | 70–90% | Very high cache hit rate |
| Policy / procedure lookup | 65–85% | Cache + deterministic |
| Data lookup / calculations | 80–95% | Deterministic territory |
| Summarization | 40–60% | Tier routing |
| Analysis / reasoning | 15–30% | Strong model required |
Section 3
Blended Enterprise Averages
Most enterprise environments have mixed workloads. Here is what blended savings look like across workload profiles.
Expected savings range by workload mix
* Reflects code-related tasks running through your own API-integrated product, not third-party coding assistants like GitHub Copilot CLI, Cursor, Claude Code, or Codex CLI — see the Coding Tools Guide for how routing and savings differ there.
Section 4
The Evaluation Promise
During your 14-day shadow mode evaluation, GetWrangler analyzes your actual request patterns and shows you exactly what savings are achievable for your specific workload — before you pay anything or activate live routing.
The ranges above are industry averages. Your evaluation replaces them with your actual numbers. If the projections are not compelling for your use case, you have lost nothing.
Section 5
What "Verified Savings" Means
Verified savings = baseline cost (established during shadow mode) minus actual cost after GetWrangler optimization.
Every saving is logged in an auditable ledger you can export and verify independently. The ledger records the timestamp, handler type, baseline cost, actual cost, and verified saving for every request. Nothing is estimated or extrapolated after the fact.
GetWrangler is designed to support a jointly auditable savings ledger — you should never have to take our word for it.
Section 6
Cost Attribution and Chargeback
GetWrangler's token system does more than route API calls — it creates a complete attribution record for every request. Each token represents a developer, team, project, or client. Every API call made through that token is logged with full cost and usage detail, making AI spend visible, attributable, and recoverable for the first time.
How it works
- ✓ Assign one token per developer, team, or client project
- ✓ Enable bypass mode to preserve full model capability with zero substitution
- ✓ Every call is logged to that token automatically — no developer behavior change required
- ✓ Pull per-token usage reports from your dashboard to allocate or invoice AI costs
Common chargeback scenarios
- ✓ Allocate GitHub Copilot CLI, Cursor (chat/plan), and Claude Code / Codex CLI (tracking only) costs back to client projects or business units — see the Coding Tools Guide for what's supported today
- ✓ Invoice clients directly for AI usage on their work
- ✓ Enforce per-team or per-developer monthly spend caps
- ✓ Identify which projects are driving AI cost growth
- ✓ Produce monthly AI tool usage reports for finance
Getting your reports
Performance reports are delivered automatically on your chosen schedule (weekly by default). You can also export per-token usage at any time from the API Tokens section of your dashboard — click the export icon next to any token to download a CSV covering any date range. Report frequency and billing contact settings are managed under Report Preferences on your dashboard.
Savings will show $0 for tokens in bypass mode — this is correct and expected. The value is attribution and visibility, not cost optimization.