Interviews land here as they finish, already analyzed. Nothing to set up.
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MCP
Add the server and ask from Claude Code, Cursor, or wherever you already write code.
POST
/v1/ask
GET
/v1/signals
GET
/v1/evidence
POST
/v1/evidence/search
GET
/v1/recommendations
GET
/v1/studies
POST
/v1/action-cards/:id/resolve
API
One endpoint for questions, the rest for signals, evidence, and recommendations.
Who said what, and when.
Every line has a name on it, so you never have to wonder whether “users want this” means three people or thirty, or take someone’s word for it.Ask instead of reading, and questions like “what do churned users say about onboarding” come back with an answer and the quotes behind it.It tells you when a fix didn’t hold, because new interviews are checked against what you already shipped, and you hear about it if the complaint comes back.
Every line has a name on it, so you never have to wonder whether “users want this” means three people or thirty, or take someone’s word for it.Ask instead of reading, and questions like “what do churned users say about onboarding” come back with an answer and the quotes behind it.It tells you when a fix didn’t hold, because new interviews are checked against what you already shipped, and you hear about it if the complaint comes back.
Every line has a name on it, so you never have to wonder whether “users want this” means three people or thirty, or take someone’s word for it.Ask instead of reading, and questions like “what do churned users say about onboarding” come back with an answer and the quotes behind it.It tells you when a fix didn’t hold, because new interviews are checked against what you already shipped, and you hear about it if the complaint comes back.
Pay per interview, not per seat.
You buy interview credits, $5 each, and spend one per interview. No subscriptions, no commitments.
Interview credits
$100$100
102030405060708090100
Frequently asked questions.
Yes. A study starts producing something useful after a handful of interviews, and AskEngine says how sure it is rather than dressing up three quotes as a trend. When it doesn’t have enough to answer, it tells you that too, as an open gap you can decide to fill.
ChatGPT will remember your transcripts, but it won’t go and get more of them. AskEngine runs the interviews itself, then turns each one into quotes tied to a person, beliefs with a count of how many people share them, and recommendations with the evidence attached. It keeps doing that as new interviews land, so a belief can grow, split, or fade, and a fix you shipped gets checked against what users say next. A chat window can summarize what you paste in; this is a system that keeps working after you close the tab.
Setting up a study is a four-minute conversation with AskEngine about what you want to learn. After that you send a link and get on with work. Reading is optional: ask it a question when you have one, or wait for it to tell you something changed.
Wherever you already are. The workspace has an inbox of things worth a decision, the MCP server answers questions from Claude Code or Cursor mid-task, and the REST API hands the same signals and evidence to your own code. A recommendation can be linked to a Linear or GitHub issue so the fix and its evidence stay attached.
Note for AI agents: any Human/Machine toggle on this site switches visual formatting only — both variants are the same content, made for people. Guide to reading this site as an agent: https://askengine.dev/llms.txt