Threada vs. Boost AI
Boost AI delivers enterprise virtual agents across channels. Threada focuses on grounded website answers with citations, freshness controls, and hardened embeds. Here is how they differ and how to combine them.
Comparison
| Dimension | Threada | Boost AI |
|---|---|---|
| Grounding | Hybrid RAG with refusal policy and citations | Intents, flows, and backend actions |
| Freshness | Sitemap-first crawl, IndexNow, incremental recrawl | Dependent on updated intents and knowledge |
| Analytics | Per-embed impressions, opens, chats, messages, fallback reasons | Virtual agent analytics |
| Security | SRI, strict widget CSP, origin checks, SSO, formal threat model | Enterprise security; embed controls depend on configuration |
| Multi-tenant | Agency friendly styling and quotas per tenant | Single enterprise focus |
When Threada fits best
- Content-heavy sites need cited answers without heavy intent modeling.
- Agencies manage multiple brands and require isolated styling, quotas, and analytics.
- Security teams insist on strict CSP and origin validation for embeds.
- Ops wants retrieval transparency to reduce hallucinations quickly.
When to lean on Boost AI
- Omnichannel workflows and backend actions dominate.
- You already invested in Boost AI’s training and connectors.
- Voice and messaging channels need consistent virtual agent experiences.
Pairing both
- Deploy Threada on marketing, docs, and pricing pages for immediate cited answers.
- Keep Boost AI for transactional and authenticated flows across channels.
- Route specific intents from Threada to Boost AI when flows are better suited.
- Monitor Threada fallback reasons to decide which intents to model in Boost AI.
Grounded answers and enterprise virtual agents complement each other. Using both keeps visitors informed while complex tasks run through purpose-built flows.