Cut your AI bill
automatically in production.
Same models. Same prompts. Smaller bills.
30-day money-back guarantee
Adding Tokani makes your inference path more resilient, not more fragile.
Fail-open by design
If our layer hiccups, traffic flows straight through to your provider — untouched. We can never be in the way of a successful request.
Multi-provider fallback
Designate any provider as your primary and any other as fallback. If the primary returns a 5xx, throttles, or times out, traffic transparently shifts to the next leg.
Your call. Your keys.
You pick which provider catches the fallback — Anthropic, Groq, Azure, Bedrock, your choice. You bring the keys, you keep the control.
Net result: 30–60% off your bill AND a more resilient inference path than you had before. Three pillars, zero asterisks: same model, same prompts, more uptime.
One layer. Every major provider.
- OpenAI
- Anthropic
- Azure OpenAI
- AWS Bedrock
- Google Vertex AI
- Groq
- Together
- Fireworks
- DeepSeek
- Mistral
- Cerebras
- xAI Grok
- Perplexity
- OpenRouter
- AI21
- vLLM
- Ollama
- TGI
- NVIDIA NIM
- HF Endpoints
- Databricks
Mix and match. Designate any provider as primary and any other as fail-open fallback — if the primary returns a 5xx or rate-limits, traffic transparently flows to the next leg. Tested across every pair.
Four ways to see your savings.
Instant calculator
Enter a few numbers, get an estimated savings range immediately. Top-of-funnel sanity check.
Estimate savings ›Design partner
14 days of full production access — free. In exchange: regular feedback, dashboard check-ins, and a co-authored case study at the end. Limited slots.
Apply as design partner ›7-day savings preview
Point a slice of real traffic at Tokani for a week — no commitment. At the end you get a workload-specific savings report with real numbers.
Start a savings preview ›Paid pilot
30-day pilot. Savings hit your provider bill from day one. Save more, pay less.
Start a pilot ›Three promises.
Zero asterisks.
Most AI-cost tools ask you to rebuild, hand over your prompts, or trust a black box. Tokani doesn't.
We never persist your prompts or responses.
Your content is processed in-memory and discarded. Nothing about it lands in our durable storage.
We never train on your data.
Not for our systems, not for our upstream providers, not for anyone else. Your traffic is yours.
Your data never crosses tenant boundaries.
Every record and retained signal is scoped to your tenant at the data layer — a structural property, not a setting you can flip.
Save more, pay less.
$1,000/mo platform and operations fee with a sliding share of verified savings — 25% on the first $50k saved, 20% to $200k, 15% to $1M, 10% above.
Cutting costs. Cutting emissions.
AI is a real resource draw — electricity, water, and the carbon that comes with them. Running leaner on AI means consuming less of all three. We don't lead with this on the sales call, but as global compute demand keeps climbing, it matters.
Lower energy draw
Lowering your AI bill directly lowers the electricity your workload pulls from the grid.
Less water for cooling
Hyperscale datacenters are major water consumers. Lighter demand means less cooling demand.
Smaller footprint
Same business outcomes, materially smaller resource draw. A quiet contribution to the global picture.
What is Tokani?
Tokani is an AI cost intelligence layer that reduces what you spend on AI infrastructure — without changing your stack, your models, or your prompts. It sits between your application and your AI providers and cuts costs automatically.
Most teams overspend on AI because they have no visibility into what's driving their bill. Tokani gives you that visibility and acts on it — reducing redundant spend, optimizing how requests are handled, and showing you exactly where the savings come from.
Frequently asked questions
What is Tokani?
Tokani is an AI cost intelligence layer that reduces what you spend on AI infrastructure — without changing your stack, your models, or your prompts. It gives you visibility into what's driving your AI bill and automatically reduces redundant spend.
What does Tokani actually do?
Tokani is software that sits between your application and your LLM providers and actively reduces your AI bill by 30–60% on most workloads. Your models, prompts, and output stay byte-identical — only the invoice changes.
How does Tokani's pricing work?
Performance-based: $1,000/month platform fee plus a sliding share of the savings Tokani delivers — 25% on the first $50k saved, 20% on $50k–$200k, 15% on $200k–$1M, and 10% above $1M. 30-day money-back guarantee: if we don't deliver any savings in your first 30 days, we refund the platform fee in full. If we don't reduce your bill, you're not net-paying.
Do I have to change my code or prompts to use Tokani?
No. Integration is a one-line endpoint swap. Prompts, model choices, and response handling stay byte-identical. A 7-day savings preview is available so you can see projected savings before going live.
Is Tokani secure for sensitive prompts?
Yes. Tokani is private by design — raw prompts and responses are processed in-memory and never written to durable storage, never used for training. Single-tenant and on-prem deployments are available for regulated workloads.
Does Tokani help with AI sustainability?
Yes. Reducing AI spend reduces compute consumption proportionally, so the cost reduction Tokani delivers also lowers each customer's AI emissions. Sustainability and savings move together — you don't have to trade one for the other.
Who makes Tokani?
Tokani is built by Forgestar Labs, an AI consulting and product studio at forgestar.ai.