This release introduces a game-changing feature that dramatically improves the accuracy and trustworthiness of your assistant’s responses:

✨ Grounded Responses with RAG

You can now enable Retrieval-Augmented Generation (RAG) to ground responses in your project’s Q&A knowledge—boosting accuracy, reducing hallucinations, and making answers more context-aware and verifiable.

Key Highlights:

• Enable Anytime:
  Turn on RAG at any point in the project version lifecycle—even after fine-tuning. Just toggle “Enable indexing for RAG grounded responses” before training.

• Fine-Tuned + RAG = Best of Both Worlds:
  RAG works in tandem with your fine-tuned model, combining semantic search with optimized generation for better performance.

• Accurate & Transparent:

  • 90% accuracy in most real-world scenarios

  • Significant improvement over fine-tuning alone (70–85%)

  • Reduces hallucinations by 20–30%

  • Search results are based on structured Q&A knowledge—not raw document chunks

• Deployment-Level Control:
  RAG can be turned on or off at the API key level, giving you full flexibility on when and where it is used.

• Pricing Note:
  No extra charge for enabling RAG during training, but runtime RAG responses may cost approx. 2× compared to fine-tuned only. See updated Pricing.

Why This Matters:

This makes Navigable the only platform where you can combine fine-tuning and RAG to create highly accurate, domain-specific AI agents. Other platforms don’t disclose or deliver accuracy metrics—we do.

This is our most impactful release yet, and we’re incredibly excited to put this level of control and reliability into your hands.