-informational){kind=icon}
A premium networking companion that turns LinkedIn QR scans into actionable relationship intelligence. ✨
Networking events are high-signal and high-chaos:
- You meet a lot of people quickly.
- You intend to follow up… but names blur, notes vanish, and context decays by the time you get home.
- LinkedIn connections get added, but the relationship memory (what you discussed, why it matters, next steps) is lost.
The result: missed follow-ups, weaker relationships, and a CRM-like burden that most people don’t maintain.
LinkLog helps you capture the connection and the context in the moment:
- Scan LinkedIn QR codes quickly during live conversations
- Attach short, structured conversation notes
- Organize people you met into a clean, meaningful summary
- Surface follow-up actions and relationship insights after the event
Think: “Scan → remember → follow up well.”
| Category | Highlights |
|---|---|
| ⚡ Capture | Fast LinkedIn QR scanning, quick-add notes, lightweight tagging (placeholder) |
| 🧠 Recall | Automatic session/event grouping, clean “who I met” summaries, searchable history (placeholder) |
| 🎯 Follow-up | Follow-up actions list, reminders (placeholder), priority cues (placeholder) |
| 📈 Insights | Relationship signals and recap prompts (placeholder), interaction timeline (placeholder) |
| 🔒 Trust | Local-first posture (goal), explicit consent messaging, privacy-first defaults (see note below) |
- Arrive at a conference and start a new “Event” session in LinkLog.
- You meet Jamie → scan Jamie’s LinkedIn QR in seconds.
- Add quick notes:
- “Building ML tooling for sales ops”
- “Intro to Priya next week”
- “Interested in pilot in May”
- Repeat across the event—LinkLog keeps everything organized automatically.
- When you get home, LinkLog shows:
- People met (with LinkedIn profile references)
- What you discussed
- Next actions
- Relationship insights to help you follow up thoughtfully
Scan → Note → Organize → Summarize → Follow up
- Scan: capture LinkedIn QR codes during conversations
- Note: add quick context (topics, promises, next steps)
- Organize: group contacts by event/session and tags
- Summarize: end-of-day recap with action list
- Follow up: export/share (placeholder) or use reminders (placeholder)
LinkLog is designed as a mobile-first capture system with a clean separation between scanning, storage, and summarization.
-
UI layer (SwiftUI)
Event/session views, contact detail screens, summary and follow-up views. -
Scanning & extraction
QR detection + LinkedIn link parsing. (Implementation may use iOS frameworks and/or a lightweight detection pipeline.) -
Data layer
Local persistence for contacts, notes, and sessions (framework TBD). -
Insights layer (optional / roadmap)
Lightweight heuristics and/or on-device summarization (TBD), designed to respect user privacy and consent.
| Entity | Example fields |
|---|---|
| EventSession | name, date, location (optional), notes (optional) |
| Contact | displayName (if available), linkedInURL, scannedAt, tags |
| InteractionNote | bullets, followUpActions, sentiment/relationship cues (optional) |
Update this section as the implementation solidifies.
- App: Swift / SwiftUI
- Scanning: AVFoundation + Vision (TBD)
- Persistence: Core Data / SwiftData (TBD)
- Analytics: TBD (privacy-first)
- CI/CD: TBD
- macOS (latest recommended)
- Xcode (version TBD)
- iOS device or Simulator (camera access recommended for QR scanning)
- Clone the repo:
git clone <REPO_URL>
cd "LinkedIn Scanner"-
Open the project in Xcode:
- Open
LinkedIn Scanner.xcodeproj
- Open
-
Build & run:
- Choose a target device (prefer physical device for camera scanning)
- Press Run
If/when LinkLog introduces external services (export, analytics, sync, AI insights), add configuration here.
| Variable | Required | Purpose |
|---|---|---|
TBD_API_KEY |
No | Placeholder for future integrations |
TBD_ENDPOINT |
No | Placeholder for service endpoints |
LinkLog is built for real-world conversations—so privacy matters.
- Consent-first: Only scan someone’s LinkedIn QR with their permission.
- Transparency: Use the app to record notes only when it’s appropriate and disclosed.
- Data handling: The product direction is local-first by default, with any sync/export features (if added) designed with explicit opt-in and clear controls.
If you’re demoing LinkLog at events, consider adding a simple line like:
“Mind if I scan your LinkedIn QR so I remember to follow up?”
- Event mode: richer session templates and quick fields
- Smart follow-ups: better action extraction and reminders
- Relationship insights: lightweight summaries and “why this person matters” cues
- Export: CSV / Notes / CRM integrations (TBD)
- Sync (optional): encrypted cross-device sync (TBD)
- Business cards: scan + unify with LinkedIn (TBD)
Contributions are welcome—especially around scanning reliability, data modeling, and UX polish.
- Fork the repository
- Create a feature branch:
git checkout -b feature/your-feature-name- Make changes and ensure the app builds
- Submit a pull request with:
- What changed
- Why it matters
- Screenshots/screen recordings if UI changes
- Keep UX premium: minimal friction, clear typography, strong defaults
- Prefer local-first patterns; gate networked features behind explicit user intent
- Add small tests where feasible (TBD)
TBD — add a license file and update this section.
LinkLog was chosen because it’s:
- Clear: immediately communicates “LinkedIn + logging”
- Professional: feels credible for demos and investors
- Product-shaped: easy to extend (LinkLog Events, LinkLog Insights, etc.)