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TokenLensEnterprise LLM Cost & Shadow Evaluation Proxy Platform

TokenLensEnterprise LLM Cost & Shadow Evaluation Proxy Platform: "An API proxy that cuts enterprise LLM inference bills by 42% via real-time shadow model benchmarking."

02 / THE PROBLEM

Runaway LLM API Spend & Risk of Quality Regression

Engineering teams deploying Generative AI features face a difficult choice: spend millions on top-tier models (GPT-4o, Claude 3.5 Sonnet) or downgrade to cheaper models and risk subtle quality regressions. Standard analytics tools only show past bills without routing traffic dynamically.

KEY PAIN POINTS BEFORE THIS EXISTED
Uncontrolled monthly LLM API spending spikes with zero per-feature attribution
Inability to test cheaper open-source models safely against production traffic
Provider rate limits causing sudden customer outages
03 / THE APPROACH

Zero-Latency Edge Routing & Asynchronous Shadow Scoring

We built an ultra-fast proxy layer that routes production requests to the primary provider while running identical prompts in the background against cheaper candidate models to score quality parity.

DECISION 01

Edge Proxy Architecture

Deployed on Cloudflare Workers ensuring less than 14ms overhead so primary user responses are never delayed.

DECISION 02

Asynchronous Shadow Benchmarking

Calculates semantic similarity between frontier and candidate model outputs in background queues.

DECISION 03

Automatic Provider Fallback

Instant failover across OpenAI, Anthropic, and Groq whenever provider latency spikes or errors occur.

04 / WHAT IT DOES

Dynamic Traffic Routing & Automated Model Cost Arbitration

Gives engineering teams granular telemetry and automated cost controls.

01

Sub-14ms Edge Traffic Interceptor

Passes API requests securely with tenant rate-limiting and zero data retention.

Interface Detail: Live traffic inspector showing request latency distribution and streaming token throughput
02

Background Shadow Model Benchmark

Scores whether cheaper models match frontier model response quality on real production prompts.

Interface Detail: Quality parity scorecard comparing GPT-4o vs Llama-3 output similarity scores
03

Automated Circuit Breaker

Switches model providers instantly if rate limits or errors trigger, preventing downtime.

Interface Detail: Circuit breaker status widget displaying instant failover routing topology
05 / OUTCOME & IMPACT

42% Reduction in Inference Expenditure & 99.99% Uptime

42%
Cost Savings
Average reduction in monthly LLM inference bills
<14ms
Proxy Latency
Edge routing overhead on critical path
99.99%
System Availability
Zero-downtime provider failover protection

TokenLens empowered engineering teams to scale AI features aggressively while keeping API budgets under tight control.

Live Active Beta — Intercepting enterprise LLM traffic.
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BESPOKE DEVELOPMENT

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06 / TECH STACK & INFRASTRUCTURE FOOTER
Technical Details
Next.js 16Cloudflare WorkersUpstash RedisPostgreSQLOpenAI APIAnthropic SDKGroq CloudNext.js 16Cloudflare WorkersUpstash RedisPostgreSQLOpenAI APIAnthropic SDKGroq CloudNext.js 16Cloudflare WorkersUpstash RedisPostgreSQLOpenAI APIAnthropic SDKGroq Cloud