DeepCost
GenAI Optimization

Generative AI Cost Optimization

Control your GPT, LLM, and generative AI costs with intelligent optimization. Reduce OpenAI, Anthropic, and AI API spending by 70% while maintaining output quality.

OpenAIOptimized
AnthropicOptimized
GoogleOptimized
Azure OpenAIOptimized
70%
Average Cost Reduction
$50K+
Monthly Savings (avg)
10B+
Tokens Optimized
5min
Setup Time

Optimize All Your AI Providers

Unified cost management for every major generative AI provider.

OpenAI

GPT-4GPT-4 TurboGPT-3.5

Anthropic

Claude 3 OpusClaude 3 SonnetClaude 3 Haiku

Google

Gemini ProGemini UltraPaLM 2

Azure OpenAI

GPT-4GPT-3.5Embeddings

AWS Bedrock

ClaudeTitanLlama 2

Cohere

CommandEmbedGenerate

GPT Strategic Cost Management Features

Comprehensive tools for generative AI strategic cost management, from token analytics to intelligent model routing.

Intelligent Model Routing

Automatically route requests to the most cost-effective model based on task complexity. Use GPT-4 for complex reasoning and GPT-3.5 for simple tasks.

50% cost reduction

Token Usage Analytics

Detailed visibility into token consumption by feature, user, and endpoint. Identify wasteful patterns and optimize prompts.

Per-token tracking

Prompt Optimization

AI-powered analysis identifies verbose prompts and suggests concise alternatives that maintain quality while reducing tokens.

30% token savings

Semantic Caching

Cache similar queries to serve repeated requests without hitting the API. Reduce costs and improve response times.

40% fewer API calls

Budget Controls & Alerts

Set spending limits per feature, team, or user. Get real-time alerts before costs exceed thresholds.

Zero surprise bills

Cost Forecasting

ML-powered predictions for future AI spending based on usage trends and growth patterns.

Accurate budgeting

Proven Optimization Strategies

Strategies used by leading companies to reduce generative AI costs by 70%.

Model Tiering Strategy

Not every request needs your most expensive model. Our intelligent routing analyzes request complexity and routes to the optimal model.

Example: A customer support chatbot routes simple FAQ responses to GPT-3.5 Turbo ($0.002/1K tokens) while escalating complex issues to GPT-4 ($0.06/1K tokens).

60% reduction in average cost per request
Typical Results

Prompt Engineering Optimization

Shorter, more focused prompts use fewer tokens. We analyze your prompts and identify opportunities to reduce token usage.

Example: Removing redundant instructions and examples from a summarization prompt reduced tokens from 500 to 150 per request.

70% token reduction per prompt
Typical Results

Response Caching

Many AI requests are semantically similar. Our caching layer identifies similar queries and serves cached responses.

Example: An e-commerce product recommendation engine caches responses for similar product queries, serving 40% of requests from cache.

40% fewer API calls
Typical Results

Model Pricing Comparison

Understanding pricing differences enables intelligent model routing.

ModelInput CostOutput CostBest For
GPT-4 Turbo$0.01/1K$0.03/1KComplex reasoning
GPT-3.5 Turbo$0.0005/1K$0.0015/1KSimple tasks
Claude 3 Opus$0.015/1K$0.075/1KComplex analysis
Claude 3 Haiku$0.00025/1K$0.00125/1KFast, simple tasks

* Prices as of latest public pricing. DeepCost automatically tracks pricing changes.

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