token intelligence layer

Your agents are
bleeding tokens.

85% of teams went over their AI budget this year. Token Ninja stops the waste before the bill: routing every call to the right model and metering spend by reasoning phase.

Maximized performance. less spend. One line of code.

$8.4B

enterprise LLM spend, doubled in 6 months

85%

of companies exceeded their AI budget this year

~30%

of tokens wasted per workflow run

products

Two tools. One proxy. No wasted tokens.

Token Ninja sits between your agent framework and any LLM provider. Every call is classified, routed, and metered before the token is spent.

product 01 · routing~20% avg savings

Right model.
Right step. Every time.

Not every reasoning step needs GPT-4o. Token Ninja classifies each LLM call by complexity and reroutes it to the cheapest model that passes quality. Automatically, on every call.

  • Classify each call by reasoning complexity in real time
  • Reroute to the optimal model before the token is spent
  • Terminate runaway loops before costs compound
live routing · run #4,892active
stepclassmodelcostsaved
task planningHIGHopus-4$0.041
web search queryLOWhaiku-3$0.003↓87%
code generationMEDsonnet-4$0.018↓55%
format responseLOWhaiku-3$0.001↓97%
review & validateHIGHopus-4$0.039
total cost
$0.253$0.102−60%
works with: LangGraph · AutoGen · CrewAI · raw API
product 02 · smart metering~10% additional savings

Know where the money
goes. Before it's gone.

Dashboards after the fact don't save you money. Token Ninja attributes spend to each reasoning phase and fires anomaly alerts before costs spike, informed by every prior run.

  • Per-phase attribution: see exactly which step burns tokens
  • Anomaly alerts fire before the overage happens
  • Historical runs inform future budget allocation automatically
phase attribution · run #4,892metering
planning
23%$0.041
research
41%$0.089
coding
18%$0.032
review
9%$0.016
output
9%$0.016
research phase +40% vs baseline · alert fired · budget reallocation suggested
works with: LangGraph · AutoGen · CrewAI · raw API

~30%

combined savings · routing + metering

100%

output quality maintained

1 line

to integrate. no rewrites.

get early access →

integration

One line. No rewrites. Works with everything.

Token Ninja is a drop-in proxy. Wrap your existing client and every call is automatically classified, routed, and metered.

integration.py
# before
import openai
client = openai.OpenAI()
# after: routing + metering on every call
import openai, tokenninja
client = tokenninja.wrap(openai.OpenAI())
# ↑ every call is now classified, routed to the right model,
# and metered by reasoning phase. no other changes needed.
LangGraphAutoGenCrewAIOpenAI SDKAnthropic SDKGoogle AI

proof

Already working. Measurably.

Our MVP optimizes each agent step at runtime, choosing models and adjusting token caps dynamically per reasoning stage. We only count savings when output quality is maintained.

benchmark / swe-20-taskMVP · April 2026

20

tasks

SWE benchmark evaluated

~30%

savings

token cost reduction

100%

quality

output parity maintained

landscape

Nobody else acts before the token is spent.

Observability tools give you dashboards. Orchestrators give you graphs. Providers give you rate limits. Token Ninja is the only layer that intervenes in real time.

PlayerWhat they seeActs before spend?
Providers (OpenAI · Anthropic)One API request at a time. No agent context, no phase awareness.NO
Orchestration (LangGraph · AutoGen)The graph and checkpoints, not per-call cost or waste.NO
Observability (Langfuse · Helicone)Dashboards after spending. Traces per node, not per problem.NO
Token NinjaEvery call, its context, classified, routed, trimmed, reallocated.YES

get started

Stop the waste.
Start saving today.

We're working with early design partners now. If you're spending on AI agents and want to spend less. Let's talk.

No contracts. No minimums. We only win when you save.

get early access →

info@usetokenninja.com · usetokenninja.com