RouterAI

Overview

RouterAI is an intelligent model classification and routing agent designed for platform builders and power users managing high-volume AI workflows. It automatically classifies incoming tasks by complexity, output type, and latency requirements, then routes them to the optimal model—whether Claude, Gemini, or GPT—to dramatically reduce AI infrastructure costs by 60%+ without compromising quality. This multi-model execution layer ensures every task gets the right model for the job, maximizing efficiency at scale.

How It Works

1. Classify the Incoming Task — Uses Claude (mcp-claude) to analyze the task on three dimensions: complexity level (Simple/Medium/Complex), output type (Classification/Summarisation/Generation/Analysis/Code), and latency requirement (Real-time/Batch). Returns a jobId for async processing.

2. Select the Optimal Model — Based on classification results, the agent intelligently selects the best model: Claude Haiku 4.5 for simple real-time tasks, Claude Sonnet 4.6 or Gemini 2.5 Flash for medium-complexity batch work, Claude Opus 4.6 for complex reasoning, GPT-5.1 Codex for code generation, or Gemini 2.5 Pro for research-heavy tasks requiring current data.

3. Execute the Task on Selected Model — Runs the task on the chosen model using multi-model APIs (mcp-openai, mcp-gemini, mcp-claude), leveraging features like adaptive thinking, structured outputs, web search, and code execution as needed.

4. Log the Routing Decision — Creates a comprehensive database record in Notion (mcp-notion) capturing task type, model selected, tokens consumed, cost, latency metrics, and quality scores for continuous optimization and cost tracking.

Key Features

• Automatic Task Classification — Intelligently categorizes tasks by complexity, output type, and latency to ensure optimal routing without manual intervention.
• Multi-Model Support — Seamlessly routes across Claude, Gemini, and GPT models, automatically selecting the fastest and most cost-effective option for each task.
• Cost Reduction at Scale — Cuts AI infrastructure costs by 60%+ by routing simple tasks to efficient models and reserving expensive models for genuinely complex work.
• Real-Time Performance Tracking — Logs all routing decisions, token usage, latency, and quality metrics in Notion for continuous workflow optimization and ROI analysis.
• Flexible Latency Handling — Distinguishes between real-time and batch requirements, choosing models optimized for speed when urgency matters and cost-optimized models for batch processing.

Use Cases

• High-Volume Content Processing — Organizations running thousands of classification, summarization, or moderation tasks daily can route simple tasks to Haiku while saving Opus for nuanced analysis, dramatically reducing costs.
• Enterprise Multi-Team Workflows — Large organizations with diverse AI needs (customer support chatbots, code generation, data analysis) can use a single router to intelligently allocate tasks, ensuring each team's work is processed optimally.
• Cost-Sensitive SaaS Platforms — SaaS providers embedding AI features can integrate RouterAI to provide AI-powered functionality while maintaining healthy margins through intelligent model selection.
• Research and Data Analysis Pipelines — Teams conducting research, competitive analysis, or data-heavy tasks can route information-gathering to Gemini's real-time web capabilities while routing reasoning work to Claude Opus, balancing speed and insight.