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Cut Your AI Costs 78%

One URL swap. Your API keys. A self-learning router that sends simple queries to cheap models and hard queries to quality models — automatically.

app.py
# Before
client = OpenAI(base_url="https://api.openai.com/v1")

# After — that's it
client = OpenAI(base_url="https://api.feeg.ai/v1")

21 providers. 99+ models. One URL.

OpenAI
Anthropic
Google
Mistral
DeepSeek
xAI
Groq
+14 more

You're Overpaying for AI

$

Most queries are easy

67% of your API calls don't need GPT-4 or Claude Sonnet. You're paying premium prices for "Hello world."

×

Static rules break

Hardcoded model tiers can't adapt when your workload shifts. What's "simple" today isn't tomorrow.

Manual routing doesn't scale

You can't review every query and decide which model handles it. You need a system that learns.

Three Steps. Five Minutes. Done.

Swap your base URL

Change one line of code. Everything else stays the same — your SDK, your prompts, your logic.

base_url="https://api.feeg.ai/v1"

Bring your own API keys

FEEG never sees or stores your prompts or responses. Your provider keys are encrypted at rest and never leave your tenant.

FEEG learns your workload

Every query teaches the router. Simple questions go cheap. Complex reasoning goes to your best model. No labels. No configuration. It just adapts.

Real Savings. Verified Quality.

78.4%
Cost Savings
Multi-provider, production queries
0.89
Quality Score
LLM-judge verified (out of 1.00)
5 min
Integration Time
Change one URL. That's it.
99+
Models, 21 Providers
OpenAI, Anthropic, Google, Mistral, DeepSeek, xAI & more

Cheaper Doesn't Mean Worse

FEEG runs an independent LLM judge on a sample of every routed query, scoring accuracy, relevance, depth, and clarity. If a cheap model isn't cutting it, the router learns and sends the next similar query to a better one.

In testing, FEEG's judge caught quality gaps that traditional metrics completely missed — downgrading a model's share from 96% to 60% when quality didn't hold up.

Quality is monitored. Always. Automatically.

You Only Pay When You Save

FEEG takes 20% of your verified savings. If we save you nothing, you pay nothing.

Your Monthly LLM Spend FEEG Saves (~78%) Your 20% Cost You Keep
$500 / mo $392 $78 $314
$1,000 / mo $784 $157 $627
$5,000 / mo $3,920 $784 $3,136
$10,000 / mo $7,840 $1,568 $6,272
Savings vary by provider mix and workload. Single-provider (e.g., Anthropic only) typically saves 40–50%.
Every query logged with model, tokens, and cost
Full savings API — audit every query, token, and penny
Monthly billing — no contracts, cancel anytime
Quality verified by independent LLM judge

Why Not Build It Yourself?

FEEG DIY Routing Static Rules
Setup time 5 minutes Weeks Days
Adapts to workload Automatically You maintain it Never
Quality monitoring Built-in judge Build your own None
Cost to you 20% of savings Engineering time Overpaying
Risk Zero — pay only if you save High — may not work Medium — breaks silently

Frequently Asked Questions

No. FEEG routes your request to the selected model and streams the response back. We log the model used, token counts, and cost for your savings dashboard — never the content of your prompts or responses. Your API keys stay in your environment, not ours.

If FEEG is unreachable, your client receives a standard connection error, just like any API outage. We recommend configuring a fallback base URL in your client for high-availability workloads. FEEG runs on infrastructure with automatic restarts and health monitoring.

Every query logs two numbers: the actual cost (what the routed model charged) and the counterfactual cost (what your default model would have charged for the same query). The difference is your savings. You can audit every query, every token, every penny in your real-time dashboard.

99+ models across 21 providers. Major providers: OpenAI (GPT-4o, GPT-4.1, o1, o3-mini), Anthropic (Claude Opus, Sonnet, Haiku), Google (Gemini 2.5 Pro, 2.5 Flash, 2.0 Flash), Mistral (Large, Small, Codestral, Pixtral), DeepSeek (Chat, Reasoner), xAI (Grok). Inference platforms: Groq, Together, Fireworks, Cerebras, SambaNova, Lepton. Enterprise: Azure OpenAI, AWS Bedrock, OpenRouter, Perplexity. Specialized: Cohere, AI21, Replicate, Hugging Face, Ollama (local). You choose which models are in your routing pool.

Yes. FEEG's built-in LLM judge monitors response quality across accuracy, relevance, depth, and clarity. If a cheaper model consistently underperforms on certain query types, the router automatically shifts those queries to a higher-quality model.

Immediately. FEEG starts with intelligent priors — cheap models for simple queries, quality models for complex ones. The router improves over the first few hundred queries as it learns your specific workload patterns, but savings begin from query one.

FEEG still saves you money by routing between models within a single provider. For example, routing simple queries to Haiku instead of Sonnet. In our Anthropic-only tests, savings were 48.5%. With multi-provider routing, savings reach 78.4%.

No. FEEG's routing engine adapts to your query patterns using lightweight mathematical signals (embedding similarity and cost data) — not your actual content. Your data is never stored, shared, or used for training.

OpenRouter and Portkey give you unified access to multiple providers — you still choose which model to use. FEEG chooses for you, automatically, and gets better over time. It's the difference between a switchboard and an autopilot.

No. Monthly invoicing via Stripe, cancel anytime. You only pay 20% of verified savings — if FEEG doesn't save you money, you pay nothing.

Stop Overpaying for AI

Swap one URL. Watch your costs drop.