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Intent Classification

Classify customer messages into intents and route to the right handler team. Replaces regex routing (70% accuracy) and Dialogflow (920ms) with semantic understanding at 15ms.

Replaces Dialogflow — 15ms vs 920ms. Orders of magnitude cheaper and 60x faster than Dialogflow

Replaces regex — 95%+ accuracy vs 70%. 25% fewer misrouted customers, no pattern maintenance

No ML team needed — New intents via LEAP in minutes. No BERT retraining cycle, no MLOps team

The Problem

Regex routing: 70% accuracy, 30% misrouted. Dialogflow CX: good NLU but 920ms and expensive at scale. Self-hosted BERT: 2-4ms but $500K+/yr MLOps team.

How LFM Compares

Regex routing is fast but misroutes 30% of queries. Cloud NLU is accurate but slow and expensive at scale. LFM matches NLU quality at 15ms and a fraction of the cost.

What LFM Unlocks

Dialogflow-quality detection at 15ms, fraction of the cost. Handles compound intents. New intents via LEAP in minutes.

Contact Center Router

Semantic intent classification at 15ms — replacing regex routing (70% accuracy, 30%+ misroutes) and Dialogflow ($210K/mo, 920ms) with a fine-tuned 350M model that sits directly in the API gateway path.

Messages

Routed

Avg Latency

Confidence

Session Cost

Customer Message

Try an example:

0 message(s)

Routing Result

Route a message to see classification results...

This demo is fine-tuned on sample data. Results improve with your data.

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