Linkmark: Social platform.
A web app for social networking, built with React, Django, Django REST Framework and PostgreSQL. Profiles, follows, posts and notifications run on one graph, and the feed stays responsive as the community grows.
Anonymised case study. Project names are aliases used to protect client confidentiality. The case study covers the project’s challenge, approach, technology and outcome.
The challenge.
- Interaction was fragmented, with no single place for people to follow and engage.
- Users needed profiles, a feed and ways to connect and post.
- It had to feel responsive as the graph and activity grew.
- Moderation and reporting tools had to exist from day one, not after the first incident.
Our approach.
- Built the web app with React for profiles, feeds and interactions.
- Backed it with Django and Django REST Framework to store the social graph and activity.
- Modelled follows, posts and notifications for a live feed.
- Tuned the feed to stay responsive as activity scales.
- Shipped reporting, blocking and moderation tooling alongside the feed itself.
The outcome.
- Users follow, post and interact in one place.
- The social graph and activity are stored consistently.
- The feed stays responsive as the community grows.
- The community scales with moderation tools already in place.
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Where AI fits in telecom & media.
Tagging and summarising large media libraries, subscriber support that resolves common requests end to end, and signals that flag accounts likely to leave.
Explore AI developmentClient feedback on our work, separate from the anonymised project described above.
As well as being exceptional technically, they consistently invest the time to understand the product and suggest how it can be enhanced and improved.
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