Stop paying for
unused tokens
Ensure your organization gets the most from LLM with just-in-time optimization and token attribution.
Works with models and clouds
The bill is compounding.
Every LLM interaction sends waste tokens to the model. Every token gets charged.
You pay for them in spend and performance, on every call, compounding across sessions and teammates.
Just-in-time optimization
Anyray sits between users and models, optimizing every interaction in real time.
-
01
One platform
Any provider, any model.
-
02
Self-hosted
Runs inside your cloud. Nothing leaves your network.
-
03
Lightweight install
Installs in minutes with zero dependency.
-
04
For humans
No change to workflow, no IDE plugins, no IT overhead.
The numbers, per workload.
Anyray compresses and optimizes payloads without degrading the output — across every workload, from coding agents to research, analysis, and operations.
| workload | reduction | before | after | saved |
|---|
| Access logcompacting repetitive entries down to the relevant few | 11,252 | 230 | ||
| Incident debuggingkeeping only the signals that point to the cause | 17,765 | 1,408 | ||
| GitHub issuesreading GitHub issues/comments to categorize/prioritize | 65,694 | 5,118 | ||
| JSON arraykeeping only the fields and items the task uses | 12,560 | 2,893 | ||
| Code searchgrep/semantic search returning many file+line hits | 54,174 | 14,761 | ||
| Git diff outputreviewing what changed in a commit or PR | 3,500 | 1,565 | ||
| Codebase explorationreading source files to understand architecture | 78,502 | 41,254 | ||
| Pasted screenshotterminal error image OCR'd to text, not vision tokens | 9,420 | 1,507 | ||
| Spreadsheet exportkeeping only the rows that match, plus the header | 28,640 | 2,864 | ||
| Database schemaretaining only the tables a text-to-SQL query needs | 19,880 | 2,386 | ||
| Recurring reportremoving repeated instructions across a nightly batch | 41,300 | 8,260 | ||
| RAG retrievalkeeping only the chunks that answer the question | 33,150 | 10,940 | ||
| Email filteringcompacting 200-email JSON while preserving fidelity | 60,512 | 3,026 |
View and reproduce Anyray benchmarks on GitHub
See what every token buys.
You finally get the breakdown — spend tied to real work, so you can have an ROI conversation per project, not per invoice.
- By project
- By team
- By model
Your data never leaves your network.
Anyray deploys inside your environment. Requests are optimized in-network, then forwarded to the model providers you already use.
-
Self-hosted
Runs as a container in your own cloud account. Nothing routed off the network.
-
Your endpoints
Talks only to the model APIs you already trust. No new vendor in the data path.
-
No new dependency
If Anyray is ever unavailable, traffic routes straight through, untouched.
Savings
Structural waste is removed automatically before it reaches the model. Every saved token is tracked in the admin console.
Productivity
Engineers ship more with fewer cycles. Wasted interactions are identified and reduced automatically.
Performance
Faster, more accurate responses as context stays clean, with fewer back-and-forth loops.
Visibility
Token spend by user, team, model, and project, with intent breakdown across debugging, feature development, code review, and more.
Security
No new vendor in the data path. Traffic stays on infrastructure you already trust, with full audit visibility.