Contact person: Feature Development for Looksmate Platform

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Location: RAWALPINDI, Pakistan

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Time to start: As soon as possible

Project description:
"Looksmate Platform: Feature Development Blueprint
Document Version: 3.0
Date: September 6, 2025
Objective: This document provides a comprehensive blueprint of all user-facing features for the Looksmate platform. It details the user experience (UX) flow, functional requirements, and technical implementation guidelines for the development team.

1. User Onboarding & Profile Management
1.1. User Registration & Authentication
Feature Goal: Provide a secure and seamless way for users to create and access their accounts.

UX Flow:

User lands on a splash screen with "Sign Up" and "Log In" options.

Sign Up: User can register using an email/password form or via a social provider (e.g., Google).

After registration, the user is redirected to the Profile Creation flow.

Log In: User can log in with their credentials or social provider.

Functional Requirements:

Email/password form must have validation (e.g., valid email format, strong password).

Password reset functionality ("Forgot Password") must be implemented.

Successful authentication should generate a session token (JWT) for authorizing subsequent API calls.

Technical Implementation:

Integrate with Firebase Authentication or Auth0 for user management.

On successful registration, create a new document in the users collection with subscriptionTier set to 'free'.

1.2. Profile Creation & Management
Feature Goal: Allow users to build a rich, expressive profile that accurately represents them.

UX Flow:

Post-registration, the user is guided through a multi-step form to provide their details.

Steps include: First Name, Age, Profile Photo Upload, Location (using device GPS or manual entry), Interests (selecting from a list or adding custom tags).

Users can access an "Edit Profile" section from their settings at any time to modify all their information.

Functional Requirements:

Profile photo upload must support cropping and resizing.

Location input should be converted to a standardized geographic address.

Interests should be stored as a list of strings.

Technical Implementation:

Create a new document in the profiles collection linked to the user's userId.

All profile data is managed via standard CRUD operations on the /api/profile endpoints.

2. Core Discovery & Matching Engine
Feature Goal: Provide users with a continuous, personalized stream of potential matches and a simple interface for expressing interest.

UX Flow:

The main "Discovery" screen displays a stack of profile cards. Each card shows the other user's photo, name, age, and key interests.

Users can tap on a card to view the full profile.

Users can swipe right ("Like") or left ("Pass").

When a mutual "Like" occurs, a "It's a Match!" animation/screen is displayed, with options to "Start Chatting" or "Keep Swiping."

Functional Requirements:

The app must fetch a batch of profiles to ensure smooth swiping without constant loading.

The system must prevent showing profiles the user has already swiped on in the current session.

Swipe actions must be recorded instantly.

Match detection must happen in real-time on the backend.

Technical Implementation:

The frontend's primary data source for the discovery queue is the GET /api/discover endpoint. This is a critical call to the AI Matchmaking Model.

Each swipe action (right or left) must trigger an API call to log the interaction in the userBehavior collection (likedProfileIds, passedProfileIds). This data is crucial for training the matchmaking model.

The backend will create a new document in the matches collection upon detecting a mutual like.

3. AI-Powered Feature Layer
3.1. AI Icebreaker Generator (Pro & Elite Feature)
Feature Goal: Help users overcome the initial hesitation of starting a conversation by providing creative, personalized opening lines.

UX Flow:

User gets a new match and navigates to the chat screen.

A button labeled "Suggest an Icebreaker" is prominently displayed at the start of the chat.

Tapping the button displays a loading indicator, then a modal/overlay with 3 unique conversation starters.

The user can tap on one of the suggestions to automatically populate it in the chat input field, ready to be sent.

Functional Requirements:

The button must only be visible and enabled for users with subscriptionTier of 'pro' or 'elite'.

The suggestions must be contextually relevant, using the interests and profile data of both users.

The UI should handle API loading and error states gracefully.

Technical Implementation:

Frontend triggers POST /api/ai/icebreaker.

The request body must contain the unique IDs of both matched users.

The backend sends these profiles' data (interests, likes) to the Google Gemini API with a carefully crafted prompt.

The frontend receives and displays the array of 3 strings returned by the API.

3.2. AI Social Companion (Elite Feature)
Feature Goal: Act as a personal "wingman" or social coach, providing users with suggestions for dates, events, and connections.

UX Flow:

User accesses the "Looksmate Coach" from the main navigation menu.

This opens a dedicated chat interface.

The user can type natural language queries (e.g., "What's happening near me this weekend?", "Suggest a good first date idea").

The Coach replies in a conversational, helpful manner.

Functional Requirements:

The feature must be locked and inaccessible to non-Elite users. A paywall/upsell message should be shown if they try to access it.

The chat interface must maintain conversation history.

Responses should be quick and context-aware.

Technical Implementation:

Each message sent by the user triggers a POST /api/ai/social-coach/query call.

The backend manages the chat state and makes contextual calls to the Google Gemini API based on the user's query.

The API response is returned to the frontend and displayed as a new message from the "Coach."

3.3. AI Safety & Trust: Live Verification
Feature Goal: Increase user trust and safety by verifying that a user is a real person who matches their profile photo.

UX Flow:

From their profile, a user initiates the "Live Verification" process.

The app requests camera access.

An overlay appears with a shape for their face and a text prompt (e.g., "Please smile and turn your head to the right").

The app records a 2-3 second video of the user performing the action.

The video is automatically submitted for review. The UI shows a "Verification in Progress" state.

Once approved, a "Verified" badge appears on their profile. If it fails, they are notified and can retry.

Functional Requirements:

The required action should be randomized to prevent spoofing with static images.

The process must be quick and have clear instructions.

The verification status must be clearly visible on user profiles throughout the app.

Technical Implementation:

The frontend uses a video recording library to capture the live video.

The captured video file is sent to POST /api/verification/live-video.

The backend processes the video to confirm liveness and match it against the user's main profilePhotoUrl.

Upon completion, the backend updates the isLiveVerified boolean in the profiles collection.

4. SaaS Monetization & Subscription Management
Feature Goal: To implement a multi-tiered subscription model that offers progressively more value and generates revenue.

UX Flow:

A "Go Pro" or "Upgrade" button is visible throughout the app.

This leads to a pricing page clearly outlining the features of the Free, Pro, and Elite plans.

User selects a plan and taps "Subscribe."

The user is redirected to a Stripe Checkout page to complete the payment.

After successful payment, they are redirected back to the app, and their new features are unlocked instantly.

Users can manage their subscription (e.g., cancel, view billing history) from a "Settings" page.

Functional Requirements:

The application must dynamically restrict or grant access to features based on the user's subscriptionTier.

Free Tier: Limited to 25 swipes/day.

Pro Tier: Unlocks unlimited swipes, smart filters, and the AI Icebreaker.

Elite Tier: Unlocks the AI Social Coach, the Analytics Dashboard, and access to exclusive events.

Technical Implementation:

The frontend fetches plan details from GET /api/subscriptions/plans.

The "Subscribe" button triggers POST /api/subscriptions/create-checkout-session, which integrates with the Stripe API.

A backend webhook must be configured to listen for [login to view URL] events from Stripe to securely update the subscriptionTier field in the users collection.

5. User Analytics Dashboard (Elite Feature)
Feature Goal: Provide elite users with valuable insights into their profile's performance.

UX Flow:

Elite users can access an "Analytics" tab in their profile or settings.

The dashboard displays key metrics like:

Total Profile Views (last 30 days).

Who has viewed their profile (a list of users, if privacy settings permit).

Personal Match Rate (Likes vs. Matches percentage).

Functional Requirements:

Data must be accurate and updated regularly (e.g., every 24 hours).

The dashboard must be visually clean and easy to understand.

Technical Implementation:

The backend must aggregate analytics data, such as incrementing the profileViews counter in the profiles collection.

The frontend populates this page using data from the GET /api/analytics/my-profile endpoint." (client-provided description)