Optimize AI spend. Don't sacrifice quality.
AI cost optimization usually means a tradeoff — cheaper models, shorter prompts, worse output. Tokani breaks the tradeoff. You keep every model, every prompt, every output. Your bill drops 30–60%.
The optimization tradeoff teams keep falling into
The standard advice for AI cost optimization is to compress prompts, switch to smaller models, or batch requests. Each one costs you something — engineering time, output quality, latency, or all three. Six months in, the optimization gets undone every time the product ships a new prompt.
The real win is leaving the prompts and models alone and reducing the bill at a different layer. That's what Tokani does.
Where Tokani fits in your AI FinOps stack
- Visibility tools tell you where AI spend goes. Useful, but the bill doesn't change.
- Governance tools set budgets and attribution. Useful, but the bill doesn't change.
- Tokani is the active layer that changes the bill itself. 30–60% lower spend, with no changes to models, prompts, or your team's workflow.
The three are complementary, not substitutes. Most serious AI organizations end up running all three.
Performance-priced — never net-negative
Tokani's pricing is structurally aligned with the customer's outcome. The Companies tier charges a $1,000/month platform fee plus a sliding share of savings actually delivered (25% on first $50k saved, 20% to $200k, 15% to $1M, 10% above). The Builders tier is $149/year plus 20% of monthly savings.
In every scenario, the customer keeps more than Tokani earns. If Tokani doesn't deliver savings, the bill stays close to flat — it's never the wrong financial decision.
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