Early Access · AI Cost Orchestration

Your AI bill doubled
last quarter.
We fix that.

tknwise is a single drop-in layer that quietly cuts the waste out of your AI spend — and finally gives finance a number they can trust. No new tools for your team, no code changes.

Onboarding a first cohort of 10 Pre-Release partners · No spam, ever

You're on the list.

We'll reach out about the Pre-Release partner program shortly.

Where the money goes

Your AI costs are a black box.

Teams adopt multiple AI providers to stay competitive — but every model call is invisible. Costs spike unpredictably, and by mid-month budgets are blown with no levers to pull.

60–80%

Wasted spend

of AI budget goes to simple tasks that don't need a frontier model.

~50%

Idle GPU

of local GPU capacity sits unused overnight while cloud bills keep running.

Zero

Visibility

context on which users, prompts, or apps are driving token consumption.

Mid-month

Budget exhaustion

forces emergency cutbacks or surprise overage invoices with no warning.

The approach

Intelligent routing, not just monitoring.

tknwise sits between your applications and every AI provider — cloud or local. It analyses every prompt in real time and routes it to the right model at the right cost.

Your Applications

Any API client · unchanged

→

Drop-in layer

tknwise

Orchestration layer

→

GPT-4o Cloud

Claude Cloud

Gemini Cloud

Local LLM On-prem

Point your API base URL at tknwise · no code changes · optimisation begins immediately

Integration

Live in an afternoon, not a quarter.

tknwise is OpenAI-compatible. Change one line — your base URL — and every existing call starts routing through the gateway.

Point your base URL

Swap one line in your SDK config. Keep your existing code, prompts and SDKs exactly as they are.

Set budgets & routing rules

Define monthly caps per team and quality floors per workload in the dashboard. No engineering required.

Watch the spend drop

Routing, semantic caching and overnight deferral kick in immediately. You see savings from day one.

app.py

from openai import OpenAI

client = OpenAI(
-   base_url="https://api.openai.com/v1",+   base_url="https://gateway.tknwise.io/v1",    api_key=os.environ["TKNWISE_KEY"],
)

# every existing call now routes through tknwise
resp = client.chat.completions.create(
    model="auto",        # tknwise picks the model
    messages=messages,
)

Inside the product

See exactly where every dollar goes.

One dashboard for spend, routing decisions and budget health — across every provider, in real time.

gateway.tknwise.io/dashboard

tknwise

Overview

Routing

Budgets

Providers

Cache

Settings

Cost Overview

Acme Corp · production workspace

Live

Last 30 days

Spend this month

$31,204

↓ 63% vs. baseline

Requests routed

2.41M

78% to local / small

Cache hit rate

38.6%

↑ 4.1 pts

Saved this month

$53,180

vs. all-cloud routing

Daily spend

Cloud

Local

Jun 1Jun 10Jun 20Jun 30

Live routing decisions

Budget by team

{{ b.team }} {{ b.used }} / {{ b.cap }}

Representative dashboard · figures illustrative

What it does

Every lever for controlling AI spend.

Intelligent Routing

Complexity scoring routes each prompt to the cheapest model that can handle it well. Simple queries never touch a frontier model.

Temporal Optimisation

Non-urgent workloads deferred to overnight on local infrastructure. Users get a "delivered by morning" option — you save peak cloud spend.

Semantic Caching

Near-identical prompts return cached results across users, apps, and sessions. No redundant API calls — ever.

Budget Governance

Real-time spend tracking per team, per app, per provider. Automatic throttling activates before limits are hit — not after.

The Day / Night Cycle

Your infrastructure never stops working.

The most differentiated capability in the product: an overnight self-improvement loop for local LLMs that runs while your cloud bill would otherwise keep ticking.

Business Hours

Real-time optimisation

Real-time routing to lowest-cost qualified model

Semantic cache hits served instantly

Non-urgent requests queued for overnight

Budget pacing active across all providers

User behaviour profiles continuously updated

Off-Peak Hours

Overnight self-improvement

Queued workloads processed on local LLM (H200, A100)

Local model fine-tuning and LoRA adaptation runs

RAG index and embedding updates

Cache pre-warming for next business day

Cost and usage reports generated for finance

What partners see

The returns, in plain numbers.

40–70%

Cost reduction

in monthly AI API spend

3–5×

Throughput gain

more AI capacity per dollar spent

Zero

Budget surprises

month-end overages or emergency cutbacks

100%

GPU utilisation

overnight vs. sitting idle

Ranges observed across early Pre-Release partner pilots. Your results depend on workload mix and infrastructure.

From a Pre-Release partner

“

We were burning close to $10k a month across four providers with zero visibility. Six weeks after pointing our base URL at tknwise we were under $6k — same output quality, and finance finally has a number they trust.

Nico Kruger

CTO · Digitata Limited

Security & control

Built to pass your security review.

Deploy in your VPC

Run tknwise fully on-prem or in your private cloud.

Your keys stay yours

Provider keys never leave your infrastructure boundary.

No training on your data

Prompts and completions are never used to train models.

SSO & audit logs

SAML SSO, role-based access and full request audit trails.

Who It's For

Built for the people who own the AI budget.

Buyer

CFO / Head of Engineering

Needs AI costs to be predictable and justifiable to the board. Wants a monthly number they can commit to — and levers when it drifts.

Champion

AI / Platform Lead

Wants to scale AI usage without getting shut down by finance. Needs control and visibility without slowing developers or changing their workflow.

End User

Developer Teams

Want the best model for the job. tknwise optimises silently behind them — no new SDK, no friction. Just faster, cheaper AI.

Questions

The things everyone asks first.

Won't routing to cheaper models hurt quality?+

No. You set a quality floor per workload, and routing only ever picks a cheaper model when its scored capability clears that floor. Anything that needs a frontier model still gets one — you just stop paying frontier prices for tasks that don't.

Does tknwise see our prompt data?+

You can deploy tknwise entirely inside your own VPC or on-prem, so prompts never leave your boundary. We never train on your data, and provider API keys stay in your infrastructure.

How long does integration actually take?+

Because tknwise is OpenAI-compatible, most teams are routing live traffic the same afternoon. You change one line — your base URL — and keep every existing SDK, prompt and call exactly as it is.

What happens if a local model or provider is down?+

tknwise fails over automatically to the next qualified provider, so a single outage never breaks your application. Health and latency are tracked per provider in real time.

How is tknwise priced?+

Pre-Release partners get early access at preferential terms while we shape the product together. Reach out via the form below and we'll walk you through options for your workload.

Join the Waitlist

Stop guessing.
Start controlling.

Be first to know when tknwise ships. We're onboarding a small cohort of Pre-Release partners — enterprises who want to shape the product before general availability.

Limited to 10 Pre-Release partners for the private beta · No spam, ever