I gang

Scalable Mobile Matching Machine Learning APP

50% of the project is done

We are building a mobile social networking app for users and business with subscription freemium paid plans. This will be help users to connect with like minded people interested in same area, explore local business and other opportunities. Whereas on other hand this will be a powerful platform for business through which they can extend their business locally and connect with local users.

Promote their services or products in common groups or categories. This app will be having advance match making algorithm which will analyze different parameters to show the matching profile and nearby business.

We are providing a new level of experience to our end user with extensive security measures to secure user data and preferences. This is going to be a social matching business app where user can select their interest and based on that system will run our match algorithm considering users preferences and evaluate over 6 degree of separation to find the right match. User can check the profile, send request to connect, chat with each other, exchange files / image / videos etc and even go for group chat or video chat. We are trying to provide a seem less experience for our users who will be the driving force behind this business model. We are providing an option to search group or even create their own group, invite users, create post, view other post or stream. They can like or share or comments on that. On the

other hand we also have an option to find business providing related or relevant services as per users Interest preferences, check them on map within defined radius, check their offerings, join their group or follow them for latest


Business would be able to join, create profile, search for categories and join them, they can also search for different groups created by users or create their own group and add users within. They would be able to see the follow list or

follow other business, they can create business post and mark them featured (optional by paying a fee). They can check the impact or stats of those posts, promote it and extend their reach within their defined geography.

Be creative to engage users with different campaign and branding activities.

We have 3 user type: End User / Business User & Admin. Let’s take look on details of different user activities:


 User

1. Registration / login / mobile verification

2. Profile / Interest Category

3. Match Algorithm / GPS / Radius /

4. Search user or business (near me) / Invite to connect / follow

5. View Others Profile / degree of separation

6. Group Search / Join / Create / Invite

7. Feed or Wall / Comments / like or dislike / emoji / share

They would also be able to hide / unfollow / delete these post or block the sender / user / group.

8. Chat / group chat / share files / images / videos

9. Video chat / group Video Chat

10. Notification / Alerts / Settings

11. Rate & review User or Business

12. Ad Module

We allow business to register on platform and get their account verified (email/phone). They can login through social ID or email id.

13. - Subscription membership plan

14. - Business Profile / Interest Category

15. - Group Search / Join / Create new Group

16. - Match Algorithm / GPS / Radius

17. - View Users profile / activity / add to group or channel

18. - Create post / mark it normal or featured / check post stats

– Free

19. - Channel or Group Feed / Like or dislike or share also own post.

20. - Chat / group chat / share files / images / videos

21. - Video chat / group Video Chat

22. - Notification / Alerts / Settings

23. - Ad Module

This feature remain same as explained for user section.

 Admin

24. – User

User Control panel for admin, through this admin can manage all user list and their devices

26. – Interest

We can add / edit / delete interest or categories, see the list of user / business

27. – Group

28. – Post

user generated content.

29. - Rating & Review

30. – CMS ( like Sales Force)

Skills Required

Evner: WordPress, React Native, Mobile App Development, Android, Machine Learning (ML)

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Om arbejdsgiveren:
( 0 bedømmelser ) Lancaster, United States

Projekt ID: #30978356

Tildelt til:

(9 bedømmelser)

20 freelancere byder i gennemsnit $8432 timen for dette job

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