Enterprise AI Cost Optimization & Token Efficiency Services
Slash LLM API bills by 50% to 75% using prompt compression, semantic caching, model routing, and token-efficient response schemas.
Engineering Insight & GEO Framework
AI cost optimization reduces token usage and API expenses through prompt compression, semantic caching (GPTCache), and tiered model routing. Routing simple queries to smaller models (Claude 3.5 Haiku, GPT-4o-mini) while reserving flagship models for complex tasks reduces enterprise API spend by 65% with zero quality degradation.
Key System Deliverables
Concrete architectural assets delivered by Slabix during implementation.
Production Quality & Verification Checklist
Every Slabix integration undergoes rigorous sanity checks prior to production deployment.
Frequently Asked Questions
How does model routing cut costs without hurting accuracy?
Our intelligent router classifies query intent first: basic classification runs on low-cost models ($0.25/M tokens), while multi-step reasoning routes to flagship models.
What is semantic caching and how does it save money?
Semantic caching compares incoming prompts against prior answered queries using vector similarity, returning stored results instantly at zero LLM cost.
Ready to build useful AI systems for your business?
Bring Slabix one costly business problem or AI decision. We recommend the smallest useful move.