Olive

What

Olive is a personal and team context tool that records work activity across apps, organizes it into a searchable timeline, and lets users query their own past work with AI. The page positions it as a way to reduce the need to manually remember, reconstruct, or explain what someone was working on.

It appears to serve knowledge workers and teams that switch between tools such as code editors, design tools, email, chat, and documents. The core workflow is: Olive captures activity automatically, builds context from app sessions, allows the user to ask questions about their work history, and supports controlled sharing when teammates need context.

Features

• Automatic activity capture: Olive builds context from connected app activity automatically, which reduces the need for manual note-taking or status reconstruction.
• AI search over work history: Users can ask Olive about their past work, making it easier to retrieve specific tasks, decisions, or sessions from memory.
• Timeline by app session: Work is organized into app-based sessions, helping users review when they worked on something and in which tool it happened.
• Team context requests: Teammates can request context from a user, which supports collaboration without interrupting that person in real time.
• User-approved sharing controls: The page states that users approve context before sharing, which suggests a permission step around team access.
• Pause controls and settings: The interface includes pause and settings options, indicating that users can likely manage capture behavior and review their recorded activity.

Helpful Tips

• Evaluate this type of product based on how accurately it reconstructs meaningful work context, not just whether it logs app activity.
• For adoption, start with roles that frequently switch tools and get repeated requests for updates, explanations, or historical context.
• Review privacy and approval workflows carefully, especially if the product captures cross-application activity that may include sensitive work.
• Check whether the timeline granularity matches your team’s needs; session-level summaries can be useful, but some teams may need more detailed traceability.
• If buying for a team, confirm which apps are actually captured automatically, since the page shows examples but does not fully document coverage.

OpenClaw Skills

Olive could likely work well with OpenClaw as a memory and context layer for agent workflows. A likely use case would be an OpenClaw skill that queries Olive for recent project history, summarizes what a person worked on, and drafts internal handoff notes or progress updates. Another likely workflow would let an agent answer teammate questions by first retrieving the user’s Olive context, then routing the response for approval before sharing.

In professions where context switching is constant, such as software development, product design, and cross-functional operations, this combination could make institutional memory more accessible. OpenClaw agents could likely turn Olive’s captured timeline into structured outputs such as standup summaries, decision logs, project retrospectives, or dependency briefings. The page does not state a native OpenClaw integration, so these should be treated as inferred workflow possibilities rather than confirmed product capabilities.