I’m working with Vertex AI’s Agent Builder and running into a frustrating problem with one of my datastores. My setup includes three different datastores and one of them contains FAQ content.
The weird thing is that my website datastore works perfectly fine. When I test queries against it, the agent finds the right information and returns proper snippets. But when it comes to the FAQ datastore, I’m getting empty responses even when I search for the exact questions that I know exist in the documents.
I’ve already tried several troubleshooting steps like disconnecting and reconnecting the datastore, clearing out all FAQ files and uploading them again, but nothing seems to fix it. The strange part is that some FAQ items do show up in searches while others don’t, which makes it even more confusing.
Has anyone else experienced similar behavior with FAQ datastores in Agent Builder? I’m looking for any debugging tips or solutions that might help resolve this inconsistent search performance.
check your datastore’s language settings - vertex ai sometimes gets the faq language wrong and kills the search indexing. i had the same weird issue where random faq items wouldn’t show up. turns out the system was flagging some entries as different languages just because of how the sentences were written. also check if you’ve got content filters turned on that might be quietly dropping results.
This drove me crazy for weeks until I cracked it. The issue isn’t your FAQ formatting - it’s how Agent Builder handles semantic matching between FAQ content and regular web pages. Your website datastore works because web pages have tons of context around keywords. FAQ entries? They’re just short Q&A pairs with zero surrounding context. Here’s what fixed it: I beefed up each FAQ entry with more descriptive content. Don’t just leave bare Q&A pairs - expand the answers with related keywords and context people actually search for. Also check your datastore’s search settings. FAQ content needs different relevance scoring than web content. Those partial results you’re getting? Some FAQ entries have enough meat for queries to match, others are too bare-bones. Add synonyms and related terms to your FAQ answers.
Hit this exact nightmare 8 months ago. Vertex AI processes different document types weirdly in the same agent setup.
Your website datastore works because web content has natural structure that Agent Builder expects. FAQ documents get chunked wrong during ingestion though. The system treats each Q&A pair like a tiny fragment instead of understanding questions connect to answers.
I fixed it by restructuring FAQ data before upload. Instead of traditional Q&A format, I converted each item into a mini article. “Q: How do I reset my password?” became “Password Reset Instructions: Users can reset their password by following these steps…”
This gives Agent Builder enough content density for semantic search. Your inconsistent results happen because some FAQ entries accidentally have enough content to match queries while others are too sparse.
Check your chunk size settings for the FAQ datastore specifically. I had to bump mine up from default because FAQ content was splitting at weird points.
Also verify your FAQ documents aren’t getting marked as low quality during processing. Agent Builder sometimes flags short FAQ entries and deprioritizes them in search results.
I’ve hit this same headache multiple times. Vertex AI’s FAQ indexing is brittle and inconsistent - that’s your real problem.
Here’s what actually works: ditch Agent Builder for FAQ data and build your own automation workflow. You’ll get a search system that understands your FAQ structure and returns reliable results every time.
I did this for our support team when we had the same random empty results issue. Instead of wrestling with Agent Builder’s weird datastore quirks, I automated the entire FAQ search. The system parses queries, matches them against FAQ content with better logic, and delivers consistent answers.
Best part? You can still plug this back into your existing setup, but now you control how FAQ searches work. No more mystery empty results.
Building this kind of automated FAQ system is pretty straightforward: https://latenode.com
Sounds like a document parsing issue with your FAQ format. I hit something similar last year - certain FAQ docs wouldn’t process right because of how they were structured. Check if your FAQ files have consistent formatting. Agent Builder chokes on documents with weird spacing, special characters, or nested questions. Also make sure those problem FAQ items don’t have funky punctuation or encoding that’s messing with the search indexing. Compare your FAQ file sizes and content density to your working website datastore too. I’ve seen overly dense FAQ files cause partial indexing failures. Try breaking your FAQ content into smaller, focused documents and see if that fixes the search consistency.