Knowledge Scattered Across Tools
Startup teams use Notion for docs, Slack for decisions, GitHub for technical context, and Google Drive for everything else. New hires spend hours finding answers that exist somewhere.
Services
We deploy Amazon Q for Business for startup teams — replacing scattered knowledge across Notion, Confluence, and Slack with a single AI interface that answers questions from your own documentation.
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Replace expensive enterprise knowledge tools with Amazon Q for Business. AI-powered search across Notion, Confluence, GitHub, and Slack for startup teams that move fast.
Amazon Q for Business costs $20/user/month for the Q Business Lite tier (basic Q&A) and $25/user/month for the Pro tier (with data source connectors and admin controls). A 10-person startup team costs $200-$250/month — less than most individual enterprise SaaS subscriptions, and covering AI search across all your knowledge sources.
A basic Q deployment connecting 3-5 data sources takes 1-2 days: AWS account setup, IAM Identity Center configuration, connector configuration for each source, initial document sync (hours to days depending on document volume), and team access provisioning. We provide a startup Q deployment template that reduces setup to under a day.
Yes. Q for Business has a native GitHub connector that indexes repository contents — READMEs, markdown files, code comments, and wikis. Engineers can ask "how do we configure the staging environment?" and Q searches GitHub repos, Confluence, and Notion simultaneously. Note that Q searches documentation files, not raw code — for code-specific Q&A, Amazon Q Developer is the appropriate product.
Startup teams use Notion for docs, Slack for decisions, GitHub for technical context, and Google Drive for everything else. New hires spend hours finding answers that exist somewhere.
Enterprise knowledge management tools (Guru, Confluence Enterprise, Notion Enterprise) are expensive. Q for Business at $20/user/month provides AI-powered search at a fraction of enterprise tool costs.
Startup onboarding is often ad hoc — new hires interrupt senior team members with questions that are answered somewhere in documentation. Q reduces onboarding time by making existing knowledge findable.
Engineering teams want to ask natural language questions about infrastructure — "how do we rollback a deployment?" or "what are our RDS connection limits?" — and get answers from their own runbooks.
Q connected to your top 3-5 knowledge sources (Confluence, Notion, GitHub, Google Drive) in 1-2 days. IAM Identity Center SSO setup, Slack integration for in-channel Q queries, and starter access controls.
Q connected to GitHub READMEs, Confluence runbooks, and architecture decision records (ADRs) — giving engineers instant access to infrastructure documentation without Slack interruptions.
Q configured as a new hire assistant with access to onboarding documentation, company handbook, and role-specific knowledge — reducing onboarding Slack questions by 60-80%.
Talk to our AWS experts about amazon q for business for startups.