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Context-Aware Semantic Router

Slashing AI Inference Costs Through Intelligent Orchestration

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Try the demo

Send a message or use a sample below to invoke the router. Simple queries → fast model; complex → heavy model.

Try fast model (simple query)

Try heavy model (complex query)

Deploying generative AI across large-scale applications presents a massive unit economics challenge. Routing every standard user query to a frontier foundation model is like using a supercomputer to operate a calculator—it destroys profit margins and introduces unnecessary latency. The Context-Aware Semantic Router is a demonstration of how to build AI infrastructure that optimizes for both cost and speed without sacrificing quality.

The Value Proposition

Treating foundation models as interchangeable compute resources rather than monolithic solutions allows organizations to cut inference bills by up to 80% while dramatically improving response times for the end-user.

The Enterprise Use Case

In high-volume environments—such as experience management for enterprises, where millions of customer feedback data points are processed daily—a semantic router acts as the vital triage layer. It ensures that simple sentiment analysis is handled by blazing-fast, open-weight models, reserving expensive, heavy-reasoning models exclusively for complex, multi-step analytical tasks.

How to Use This Demo

Enter a Prompt: In the chat interface on the left, type a query. Try alternating between a simple request (e.g., “What is the capital of France?”) and a highly complex one (e.g., “Write a Python script to implement a self-balancing AVL tree.”).
Watch the Router: Hit send and observe the Telemetry Dashboard on the right.
Analyze the Telemetry: The dashboard will illuminate in real-time, showing you exactly which model the gateway selected, the milliseconds it took to make that classification, and the simulated cost savings of that specific routing decision.

Takeaway

True product leadership isn't just about shipping AI features; it's about protecting the P&L. This architecture proves that you can scale agentic systems sustainably by abstracting the model layer and building intelligent, cost-aware middleware.

Try the demo

Send a message or use a sample below to invoke the router. Simple queries → fast model; complex → heavy model.

Try fast model (simple query)

Try heavy model (complex query)

The Enterprise Use Case

How to Use This Demo

Enter a Prompt: In the chat interface on the left, type a query. Try alternating between a simple request (e.g., “What is the capital of France?”) and a highly complex one (e.g., “Write a Python script to implement a self-balancing AVL tree.”).

Watch the Router: Hit send and observe the Telemetry Dashboard on the right.

Analyze the Telemetry: The dashboard will illuminate in real-time, showing you exactly which model the gateway selected, the milliseconds it took to make that classification, and the simulated cost savings of that specific routing decision.