Darwinbox vs Spark Hire

Spark Hire ships across two products, Meet and Recruit, and the last month has been unusually dense. AI Notetaker put a model inside the live interview, generating structured summaries and suggested evaluation notes; role-aligned ratings followed within weeks, using the job description, scorecard and interview questions to rate answers and organise findings into pros, concerns and items for further review. Recruit gained automatic duplicate merging, pre-screen answers that write through to candidate fields, and LinkedIn-driven lead status updates.

The AI work has a clear direction: capture more of the hiring conversation, then reason over it against the role definition. Each release makes the next possible — notetaking produces the transcript, the job description and scorecard supply the criteria, and pre-screen field mapping makes the structured half searchable. The Recruit side is running a parallel data-hygiene arc, since automated evaluation is only as good as the candidate records underneath it.

Expect the role-aligned rating logic to reach further back into the funnel — screening and shortlisting against the same job-description criteria — and continued work on the record quality that scoring depends on.