Is uploading PDFs enough?

Uploads help, but crawls keep the assistant aligned with the live site and prevent drift when pages change.

How do I control hallucinations?

Use adaptive relevance thresholds, strict refusal prompts, and track fallback reasons so you can tune retrieval instead of tweaking a prompt forever.

What if I already use an FAQ trainer?

Start by pointing Threada at your docs and pricing. You can keep the trainer for niche flows while Threada answers the rest.

Threada vs. Chatbase and FAQ Trainers

FAQ trainers and upload-only chatbots seem easy: drop PDFs in, write a prompt, and publish. The downside shows up later as stale answers, missing new pages, and no transparency into why the model replied the way it did. Threada starts with your sitemap, enforces retrieval rules, and gives you the metrics to tune accuracy over time.

Core differences

Source of truth: Threada indexes the live site, sitemap first, with polite crawling. FAQ trainers depend on manual uploads and prompt tweaks.
Freshness: IndexNow and scheduled sitemap monitoring keep Threada aligned with releases and pricing changes. FAQ trainers often drift until someone remembers to re-upload files.
Observability: Threada logs retrieval scores, fallback reasons, and per-embed metrics. Trainers usually expose only conversation counts.
Security and compliance: Widget CSP, postMessage origin checks, and a formal threat model keep embeddings and responses in scope. Trainers vary in isolation and often lack deep tenant controls.
White label and multi-tenant: Agencies can spin up multiple branded embeds with separate quotas and analytics. Trainers are often single-tenant.

Migration path

Point Threada at your sitemap and key support pages; let it crawl up to the quota.
Compare top unanswered questions and containment against your FAQ trainer for a week.
Redirect high-volume intents to Threada and leave niche flows in the trainer until you build coverage.
Use feedback flags to tune thresholds and prompts rather than piling on more example Q&A pairs.

What to measure

Containment rate (no handoff needed) across both tools.
Time to publish updates after docs change.
Fallback reasons in Threada vs generic errors from the trainer.
User feedback on outdated answers; watch the rate drop as freshness and retrieval improve.

Quick uploads are handy. A crawler with disciplined retrieval, freshness controls, and analytics keeps your assistant trustworthy as your site evolves.