Your data is yours.
Reclaim it.

LinkedIn's standard API only gives apps your name, headline, email, and photo. It does not expose your work history, employment dates, or connections list unless you are granted an enterprise partnership.

But you already own the full timeline. Go to LinkedIn → Settings → Data privacy → Get a copy of your data → Request archive. Within minutes to days you will receive a ZIP containing Positions.csv (every job, company, start date, end date), Connections.csv, and more.

Upload Connections.csv to Human Context to build your graph. When we add Positions.csv parsing, the same export will answer: "Did I meet this person while I was at IBM, or at Microsoft?"

Your inbox is a relationship journal. Google Takeout lets you download Mail (mbox) and Calendar (ICS) exports that contain the events, meetings, and threads that define when relationships happened.

Go to takeout.google.com, deselect everything, then select Mail and Calendar. Choose an export window — for example, the last three years. Import the resulting files to anchor people to real events and dates.

On a Mac, open Contacts, select all contacts, then File → Export → Export vCard. On iCloud.com, open Contacts, click the gear icon, and choose Export vCard. The vCard file contains names, phone numbers, emails, companies, and notes.

Human Context can parse vCard files to seed your network with the people you already know. Notes fields are especially useful — they often contain the context you jotted down after a meeting.

On Android: open Contacts → Fix & manage → Export to file. On iPhone: if you sync with iCloud, export from iCloud.com as a vCard. These files are yours and can be imported directly into Human Context.

Phone contacts are often richer than you expect — they include company names, titles, and the notes you added after a call. That metadata becomes relationship context.

Corporate platforms lock your data not because it is valuable to them, but because it is valuable to you. When you bring your own positions, events, emails, and contacts into Human Context, the platform can answer real questions: where did I meet this person, who connects us, when was our last real conversation, and was it while I was at a specific company?

The more timeline data you import, the less the AI has to guess. Your relationship graph becomes grounded in your actual history, not just names and job titles.