AI Model Intelligence

Your AI bill has a blind spot.

Most companies route every API call to GPT-4 because it works. Argus finds the 70% of calls where a cheaper model returns identical quality. Then it fixes it, autonomously.

$8.4B
Enterprise LLM spend in 2025
70%
of API calls use the wrong model
30-70%
cost reduction with smart routing
How Argus Works

Not a gateway. Not a proxy.
An autonomous model analyst.

01

Connect your API keys

Argus hooks into your existing OpenAI, Anthropic, Google, and open-source model providers. No code changes. No proxy to configure.

02

Shadow-evaluate everything

Every API call pattern gets tested against alternative models in the background. Same prompts, real quality comparison, zero production impact.

03

See exactly where you bleed

A live dashboard breaks down cost vs. quality per task. "Your classification prompts work identically on Haiku at 94% less cost." Specific numbers, specific savings.

04

Auto-optimize with one click

Approve Argus's recommendations and it reroutes traffic automatically. Or set it to autonomous mode and let it continuously optimize as new models drop.

argus-report.diff
// Monthly LLM spend analysis - GPT-4 Turbo    847,000 calls    $12,400/mo + Haiku 3.5      593,000 calls    $890/mo    (identical quality) + GPT-4 Turbo    254,000 calls    $3,720/mo   (complex only) // Net savings: $7,790/mo (-63%)

Every model is a tool. Most companies use a sledgehammer for everything.

New models ship every week. Prices shift. Quality drifts. No engineering team has time to continuously benchmark their entire AI stack against every new option. That's the job Argus was built for. Watching everything, so you don't have to.