New
Stop tokenmaxxing. Start outcomemaxxing.
Your AI costs are climbing — and 60% of the time, the wrong model is on the job. Token Tuner maps token spend to real work, then tells you exactly where to cut.
5-minute demo
TOKEN TUNER Report in 14 days
Board-ready recommendations
Built for CIOs, CFOs & COOs
200 AI requests a day. The wrong model on 60% of them.
Most teams have no idea which model handled which task — or what it cost. Premium models silently handle work that a fraction-of-the-cost model would nail.
50
per knowledge worker
60%
of all requests
The everyday tokenmaxxing happening right now.
Token Tuner surfaces the workflows where premium models are doing low value work — and what it's costing you.
Claude Opus writes a TikTok caption
"Make a fun caption for a coffee photo"
A $4 sentence about a $4 latte
GPT-4o generates a whole dashboard again
"Run this financial analysis again"
Dashboard that is run repeatedly and costs $54 every time
Same task. Same result. 10x the price.
Analyzing customer feedback sentiment
Claude Opus 4
$4.73
per analysis
Analyzing customer feedback sentiment
Claude Haiku 3.5
$0.47
per analysis
10× the price. Same result.
You wouldn't use a flamethrower to light a candle.
So stop running Opus on tasks Haiku finishes for a tenth of the cost.
Right model. Right task.
"Draft a thank-you email"
Haiku 3.5
"Build a SQL query for retention"
Sonnet 4
"Find recent pricing for BTC"
o3
Across all teams.
Introducing Token Tuner
Same outcomes. A fraction of the spend.
Token Tuner recommends models that can deliver the same results — Haiku for the easy stuff, Sonnet for the work that needs more, Opus only when it actually earns its price.
TOKEN TUNER
OPTIMIZED
this month spend
$1,218.40
"Now this is fine."
— your finance team, finally
Token Tuner Report in 14 days.
No instrumentation project. No quarter-long rollout. Just answers your leadership team can act on.
Token spend, decoded
A clear view of spend by team, app, model, and workflow.
Overspend, identified
The workflows where premium models are unnecessary.
Specific actions
Concrete downgrade and routing opportunities, ranked by impact.
A board-ready report
A prioritized Token Tuner Report for finance, IT, and the board.
Three steps to an operating answer
01
Connect your data
Token Tuner ingests token usage across apps, models, teams, and workflows.
02
Map spend to work
Lanai translates spend into AI Work Hours, Leverage, and Depth.
03
Get the answer
A Token Tuner Report with concrete recommendations on where to downgrade, standardize, and optimize first.
Questions execs ask
We tap into your existing Enterprise AI providers' (OpenAI, Anthropic, etc.) data. Connecting takes no engineering work.
You can be up and connected in just a few hours!
No, we analyze all teams who are using AI. Lanai creates a standardized data set across all users in order to compare how much AI work is being delegated, how much impact there might be, and opportunites to optimize.
Your Token Tuner report will have actionable insights from the data we collect and analyze over two weeks, as well as create a baseline for future change measurement.
Absolutely. We'll help you be ready to finally answer, "what are we getting for all this AI spend?" with actionable recommendations to preserve all the value generated by AI, but spend less.
Lanai is SOC 2 Type II compliant. We've architected our platform with privacy-preserving data flows and customizable retention. We've deployed at F500 companies and in regulated industries and have done this before: enterprise leaders building for enterprise leaders.
See where your tokens are actually working.
Book a 30-minute Token Tuner demo and get a State of AI Report in 14 days.
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The operating system for AI value creation. See it. Steer it. Scale it.