Give HR Teams AI That Remembers Every Candidate and Employee Interaction

A recruiter spends forty minutes briefing their AI on a candidate before a debrief call — pulling in resume notes, prior interview feedback, and the hiring manager's stated preferences. The next recruiter on the same role starts from zero. Employee relations conversations, performance coaching threads, onboarding context: none of it persists between AI sessions, so every interaction is the first interaction.

Candidate Profiles That Persist Across the Team — Fact Memory stores structured candidate data with source attribution and conflict detection, so if two interviewers log contradictory assessments, MemoryLake flags it rather than silently overwriting the record.

Interview Notes That Are Searchable Forever — Conversation Memory makes every AI-assisted interview debrief permanently retrievable. Search by candidate name, role, or date — across any AI model your team used that session.

Shared Team Memory With Access Controls — Role-based access control lets you gate sensitive compensation or performance data to HR leadership while keeping general candidate context available to the full recruiting team.

1. Connect — Link your HR team's AI tools (ChatGPT, Claude, Gemini, or any API endpoint), your ATS via REST API, and Google Workspace or Office 365 for email and calendar context.
2. Structure — MemoryLake automatically organizes candidate data into Fact Memory, interview sessions into Conversation Memory, and hiring timelines into Event Memory with chronological ordering.
3. Reuse — The next recruiter to open a candidate file gets full context from every prior AI session: notes, decisions, open questions, and timeline — without anyone copy-pasting a single thing.

MemoryLake is built for HR teams, recruiters, and people operations professionals who use AI models daily and lose candidate or employee context every time a session ends or a team member picks up the work. It's particularly useful for recruiting teams working high-volume roles where multiple interviewers touch the same candidate, and for HR business partners who need consistent context across long employee relations threads.