CrawlBot AI vs. Dashworks Internal AI
Dashworks helps employees search across internal tools. CrawlBot is built for grounded website answers with citations, freshness controls, and hardened embeds. Here is how they differ and how to use both.
Comparison
| Dimension | CrawlBot AI | Dashworks |
|---|---|---|
| Primary surface | Public website visitors | Internal teams and knowledge |
| Grounding | Hybrid RAG with refusal policy and citations | Connectors to docs, Slack, tickets |
| Freshness | Sitemap-first crawl, IndexNow, incremental recrawl | Sync frequency depends on connectors |
| Analytics | Per-embed impressions, opens, chats, messages, fallback reasons | Internal search analytics |
| Security | SRI, strict widget CSP, origin checks, SSO, formal threat model | OAuth scopes, enterprise connectors |
| Multi-tenant | Agency friendly styling and quotas per tenant | Single company focus |
When CrawlBot fits best
- Public visitors need cited answers without exposing internal data.
- Marketing and support teams require structured analytics on impressions, opens, chats, and fallback reasons.
- Agencies manage multiple brands and need isolated styling and quotas.
- Security reviews demand strict CSP and origin validation for embeds.
When Dashworks remains essential
- Employees need a copilot across tools like Google Drive, Jira, or Slack.
- You want smart search over internal tickets, specs, or runbooks.
- Knowledge sources include sensitive docs that never belong in a public assistant.
Pairing strategy
- Deploy CrawlBot on marketing, docs, and pricing pages for grounded Q&A.
- Keep Dashworks powering internal copilots and search.
- Share CrawlBot unanswered questions with internal teams so Dashworks connectors prioritize the same topics.
- Feed Dashworks insight (e.g., frequently searched terms) into CrawlBot’s crawl scope to improve public coverage.
Grounded external answers and internal copilots solve different problems. Running both keeps customers and employees informed without mixing datasets.