Smart LLM Routing
Multi-tier routing system automatically selecting the optimal AI model for each task's complexity — with continuous evaluation of new models and resource auto-scaling.
Not every query requires the most powerful (and most expensive) AI model. A simple email requires a different level of intelligence than a strategic analysis for the board. Our multi-tier routing system automatically classifies each task and routes it to the optimal model — balancing response quality with cost. We continuously test new AI models appearing on the market and swap them in when they offer better quality-to-price ratios. The result: enterprise-grade AI at a fraction of the cost of the "always the most expensive model" approach.
Multiple Tiers — From Free to Premium
The routing system spans the full spectrum of AI models: from free open-source models running locally on GPU servers, through mid-tier cloud models, to the most powerful commercial engines available on the market. Each tier has defined parameters: cost, maximum context, response time, reasoning capabilities. The classifier analyzes each query and assigns it to the optimal tier — automatically, without user intervention.
Cost Optimization in Practice
In a typical enterprise scenario, the majority of queries are simple operations (correspondence classification, data extraction, templated responses) handled by economical or free local models. A smaller portion are medium-complexity tasks (document analysis, report generation) routed to mid-tier models. Only a small percentage are truly complex tasks (business strategy, legal analysis, system architecture) requiring premium models. This reduces the average cost per query by several times compared to the single most expensive model approach.
Continuous Evaluation and Model Swapping
The AI model market changes dynamically — new, better models appear every few weeks. The routing architecture acts as an abstraction layer: each tier defines requirements (e.g., multi-step reasoning capability), not a specific model. We continuously test new models and swap them in when they offer better quality-to-price ratios. No agent, no prompt, no workflow needs changes during such a swap. The system itself adapts to the best available technologies.
Auto-Scaling and Dynamic GPU Resources
Under increased load, the system automatically scales computational resources. We can dynamically connect — in a secure manner — multiple GPU providers, both local and cloud-based. When the organization needs more power (e.g., during peak hours, mass document processing), the system automatically launches additional instances. For organizations sensitive to costs or with data residency requirements, we offer a configuration fully based on local models at zero API cost — data never leaves the client's infrastructure.
Key Highlights
- Multi-tier LLM routing
- Multiple times AI cost reduction
- Swap models without code changes
- Continuous evaluation of new market models
- Auto-scaling GPU resources under load
- Dynamic connection of multiple GPU providers