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Introducing AI Query Expansion: How We Made AI Agents 10x Smarter

Our breakthrough AI query expansion technology automatically understands user intent, even when they phrase questions differently. Learn how we built this game-changing feature.

Alex Chen
CEO & Founder
December 15, 2024
3 min read
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Introducing AI Query Expansion: How We Made AI Agents 10x Smarter

Ever asked an AI chatbot a question and gotten a completely irrelevant answer? We've all been there. The problem isn't the AI's knowledge — it's understanding what you're actually asking.

The Intent Gap

Traditional chatbots match your question against their knowledge base using keyword matching or basic semantic search. But humans don't speak in keywords. We use:

  • Synonyms: "How do I cancel?" vs "How do I terminate my subscription?"
  • Implicit context: "It's not working" (What's "it"?)
  • Conversational language: "Can I get my money back?" vs "What is the refund policy?"

This creates an "intent gap" — the difference between what you mean and what the AI understands.

Our Solution: AI Query Expansion

Query expansion is a technique that automatically transforms your question into multiple related queries, dramatically improving the chances of finding relevant information.

How It Works

When you ask: "How do I cancel?"

Our system expands this to:

  • "How do I cancel my subscription?"
  • "How to terminate my account?"
  • "Cancel membership process"
  • "Steps to end my plan"
  • "Unsubscribe from service"

Then it searches for all of these, combines the results, and uses AI to synthesize the best answer.

The Technical Magic

We use a multi-stage approach:

1. Intent Classification

First, we classify the type of question:

  • Informational ("What is...")
  • Procedural ("How do I...")
  • Transactional ("I want to...")
  • Navigational ("Where is...")

2. Entity Extraction

We identify key entities and their relationships:

  • Actions: cancel, refund, upgrade
  • Objects: subscription, account, plan
  • Modifiers: immediately, partial, full

3. Expansion Generation

Using a fine-tuned LLM, we generate semantically similar queries that cover different phrasings of the same intent.

4. Hybrid Search

We run both semantic (vector) and keyword searches across all expanded queries, then combine results using Reciprocal Rank Fusion.

Real Results

In our testing across 10,000 customer support queries:

MetricBeforeAfterImprovement
Relevant Answer Rate67%94%+40%
First-Response Resolution45%78%+73%
Customer Satisfaction3.2/54.6/5+44%

Try It Yourself

Query expansion is now enabled by default for all Chatsy agents. No configuration needed — it just works.

Want to see it in action? Ask our support agent a question in different ways and watch how it consistently finds the right answer.

Deploy Your Smart Agent →

Tags:#ai#query-expansion#natural-language#product-update

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