Developer Builds Open-Source Memory Layer to Stop Recruiter Bots Forgetting Candidates

A developer has built an open-source tool called Recall to solve a common flaw in AI recruiter bots — their inability to retain information between separate conversations with candidates. Without an external memory layer, each new interaction starts from scratch, meaning a candidate who spent twenty minutes sharing their preferences can be treated as a stranger days later. Recall works by extracting key details from conversations — such as career goals, salary expectations, and work-style preferences — and storing them using Hindsight, an open-source agent memory layer by Vectorize. When a new job opportunity arises, the relevant stored context is retrieved and fed back into the model's prompt, enabling personalised and consistent responses. The developer tested the system by comparing responses with and without the memory layer active, using the same candidate, role, and question to isolate the effect of recalled context.