Price every AI call before it sends. Track spend across Claude, ChatGPT, Gemini and Grok. Prove every dollar saved. We take 10% of verified savings. You keep 90%.
Works with:
How this is calculated - a worked model from published prices
A team spending $50,000/mo moves 40% of its Claude Opus 4.8 traffic to Claude Sonnet 4.6. At today’s published token prices that traffic costs 60% of what it did (blended 3:1 input/output), so $20,000 becomes $12,000 - $8,000 saved. Tokeven takes 10% of that ($800); you keep the rest. Your own numbers will differ. Measuring them is the whole point.
How it works
Two lines of Python wrap your existing Claude, OpenAI, Google or xAI client. Tokeven captures token counts, model, latency and cost while your calls run exactly as before. Your keys stay local and prompt content never reaches Tokeven.
Captures usage: token counts, model, latency and cost. Prompt content and your provider key never reach Tokeven.
The same 9,000-token system prompt is billed as fresh input on 755 Claude calls a week. Marking it cacheable bills the repeats at the 90%-off cache-read rate instead.
155 of your 370 claude-opus-4-8 calls this week were single-turn lookups. On the identical prompt, claude-sonnet-4-6 prices 40% lower.
3 gemini-3.1-pro workflows re-send full conversation history every turn. Summarising prior turns would cut fresh input tokens by ~35%.
Before a prompt is sent, the advisor shows the cost on the current model, the cost on alternatives across Claude, GPT, Gemini and Grok, and a confidence score for each. Your developer makes the call in the moment. A weekly digest gives your admins the week's spend by model category and provider, with coaching tips.
The Proof dashboard traces every verified dollar back to the call where your team accepted a cheaper model, priced on both models at the token prices in force when it ran. Fully auditable. Because both sides use live token prices, the numbers stay honest as provider pricing moves.
Gainshare pricing
Savings measured against live token prices per model. Published math, open to audit.
Your biggest lever
System prompts repeat across 89% of sessions, all providers
Enable prompt caching where supported
Save $515/wk
gpt-5.5 used for tasks where gemini-3.5-flash matches quality
Route summarisation to Flash
Save $1,030/wk
68% of Opus calls are single-turn Q&A
Switch to Sonnet or Gemini Flash for simple lookups
Save $796/wk
Interactive calculator
Low end of a modelled 15-30% range from routing, caching, and shorter prompts. Modelled, not a customer average - your own numbers are the only ones we bill against.
A price before you send. Accepted recommendations lower the bill. We take 10% of what you actually save.