SpeckyDocs

Alex Research

What it does

Alex is Specky's AI research assistant — a conversational interface that synthesizes signals from all your connected integrations, customer interviews, and internal documents to answer product questions with cited evidence.

Unlike a general-purpose AI chatbot, Alex has access to your actual product data: the Slack threads your team has had, the Gong calls your sales team recorded, the Jira tickets your engineers filed, and the PRDs your team has written. When you ask Alex a question, it searches across all of this data and synthesizes a grounded answer — not a hallucinated one.

Every claim Alex makes is backed by a citation you can click to see the original source. This means you can use Alex's output directly in stakeholder presentations and PRDs without worrying about accuracy.

Key capabilities:

  • Research synthesis — answer open-ended product questions with evidence from your data
  • Pattern detection — identify recurring themes across hundreds of signals automatically
  • Competitive analysis — surface mentions of competitors across customer calls and feedback
  • Pre-PRD research — gather all relevant context before you start writing
  • Interview analysis — synthesize findings from multiple customer interview sessions

    • When to use it

  • Before writing a PRD — ask "What do customers say about [feature area]?" to gather supporting evidence in minutes instead of hours
  • During discovery — ask "What are the top three pain points in our onboarding flow?" to identify patterns across all customer feedback
  • When preparing for stakeholder presentations — ask "What evidence supports prioritizing [initiative]?" to build a data-backed case
  • After a customer interview — ask "How does this compare to what other customers have said?" to contextualize new feedback
  • During competitive analysis — ask "What do customers say about [competitor] compared to us?" to surface competitive intelligence from your own data
  • For retrospectives — ask "What signals predicted the issues we saw in [feature] launch?" to learn from past patterns

    • How to use it

  • Open Alex Research from the sidebar (or click the Alex icon in the top-right corner)
  • Type a research question in natural language — be specific for better results
  • Alex searches your connected data and synthesizes an answer with citations
  • Click any citation badge to see the original source (Slack thread, Gong call, Jira ticket, etc.)
  • Use the Follow-up input to ask clarifying questions or drill deeper
  • Click Save to PRD to insert Alex's response (with citations) directly into a document
  • Use Export to download the research summary as Markdown

    • Tips for better results:

  • Be specific: "What do enterprise customers say about our API rate limits?" works better than "What do customers think?"
  • Specify a time range: "In the last 30 days, what has changed in customer feedback about checkout?"
  • Ask for comparisons: "How does feedback about our mobile app compare to our web app?"

    • Example

    You're preparing to write a PRD for a redesigned notification system. Before opening the PRD Editor, you open Alex and ask:

    *"What do customers say about our current notification system? What are the most common complaints and requests?"*

    Alex responds with:

  • Summary: 47 signals mention notifications in the last 90 days. The top themes are: notification overload (23 mentions), missing mobile push notifications (18 mentions), and no way to set quiet hours (12 mentions).
  • Top complaint (cited from 3 Gong calls and 8 Slack threads): "I get too many emails and can't figure out how to turn them off without disabling everything."
  • Top request (cited from 2 Jira tickets and 5 Slack threads): "Please add a daily digest option instead of individual emails."

    • You now have a research-backed foundation for your PRD in under 2 minutes.