We are looking for an experienced full-stack developer to help implement and refine key features for our basketball-focused web application. The platform enables players to showcase their stats, receive endorsements, and earn badges and points for participation — similar to platforms like StackOverflow (for engagement).

This job will involve working with existing code, extending functionality, and helping polish core features.

-----

KEY FEATURES TO DEVELOP OR ENCHANCE

- Video Uploads:
Ensure smooth and reliable video upload support for players.

- Endorsement System:
Users with the "Endorser" role can endorse players for specific badges through a structured form process (badge selection, testimonial).

- Players gain progress toward badges and receive points; endorsers are also rewarded.

- Badge + Group Access Logic:
Players can earn badges through endorsements.
Badges can serve as access keys to private groups, bypassing paid subscriptions.

- Player Statistics & Game Entries
Players log detailed game stats.
The system calculates cumulative player averages and uses them for player rankings.

- Ranking Algorithm:
Weighted formula based on player statistic.
Ranks players automatically.

- Gamification + Points System:
Points earned for actions like uploading videos, getting endorsed, achieving milestones, etc.

- Friendship and Privacy:
Mostly built out. This just needs to be cleaned up.
Add privacy setting for users to set to hide or show their friends on their public profile.

-Messaging System:
Mostly built out, but needs some cleaning up.

- Business Pages:
Users can create business pages with posting and follower support.

- Admin Tools & User Security:
Users can report and block others.
Admins can suspend, ban, mute users and track moderation actions.
Email notifications triggered by account actions (ban, suspend, etc.).

- Job Portal:
Mostly built out, but needs a few finishing touches.

- Grades System:
Players can log academic grades per subject and quarter to earn points.

_____

REQUIREMENTS
- Proficient knowledge in PHP, Laravel, React, Docker, and DigitalOcean
- Ability to work with version control (Git)
- Strong attention to detail and security concerns
- Familiarity with gamification, role-based access, and user engagement strategies

_____

More details will be provided during the interview.

If you’re excited to work on a sports-focused platform that empowers young athletes and encourages engagement through endorsements and achievements, we’d love to hear from you!

Looking for Github expert or someone who knows their way around Github to consult - Fullstack development background w/lots of projects would be ideal.

Fully automate BlackBird Property Management's operations using SuiteDash (central hub), Buildium, JustCall, LeadSimple, Adobe Sign, Stripe, and Venderoo. The Goal is a Zero-touch client onboarding, AI-driven lead processing/maintenance, and seamless platform integration.

Timeline: 10 days (flexible up to 2 weeks)

KEY RESPONSIBILITIES:
1. Integrate SuiteDash with Buildium, JustCall, LeadSimple, Adobe Sign, and Stripe for bidirectional data sync.
2. Configure AI workflows in JustCall and Venderoo for lead qualification and maintenance coordination.
3. Develop self-service portals for owners/tenants with automated document handling (e-signatures via Adobe Sign).
4. Implement payment automation (Stripe) and compliance tracking.

MANDATORY REQUIREMENTS:
1. Proven experience with SuiteDash, Buildium, and JustCall AI.
2. Expertise in Zapier/Integromat for multi-platform automation.
3. Portfolio demonstrating complex workflow builds (property management preferred).
4. Familiarity with AI-driven tools like GigRadar or Vollna for lead generation optimization

MANDATORY BEFORE APPLYING:
Must Be An Expert in SuiteDash Automation, Property Management Tech Stack, AI workflows.
Must Have Case studies showing end-to-end automation (e.g., lead → onboarding → payment).
Must show proof of API integration work.
No Generic proposals without tool-specific examples.

MUST ANSWER THE FOLLOWING QUESTIONS WITH YOUR APPLICATION:
1. Walk me through how you’d sync Buildium property data with SuiteDash in real time?
2. How would you train JustCall AI to classify owner vs. tenant calls?
3. Show me a past project where you automated document signing (Adobe Sign/DocuSign).

Hello builder! 👋
I'm on the hunt for a skilled developer to help bring to life a new AI-driven content tool. The goal? To create a powerful web app that generates high-performing long YouTube scripts (3000+ words), tailored for audience retention, storytelling youtube principles and specific persona.

🔧 What We’re Building
Imagine a tool that writes YouTube scripts, but not just any scripts. It learns from real performance data (like audience retention, drop-off points, watch time, etc.) and uses that feedback loop to improve future scripts automatically.

Check out this related SaaS concept for inspiration:
https://arvow.com/ or https://writesonic.com/

🧱 Tech Stack
We’re looking for someone with proven experience using:
Next.js (React-based frontend)
Vercel (for deployment and hosting)
Supabase (as the backend/database layer)

Bonus if you have experience integrating with:
YouTube APIs (Analytics, Reporting)
Machine learning workflows (optional for now)

🧠 Ideal Candidate
You’ve built (or contributed to) a text generation or content-writing app
You’re familiar with AI/LLMs (we’ll handle most of the ML logic, but your experience helps)
You write clean, modular, scalable code
You can collaborate async, communicate clearly, and bring creative suggestions

📣 Interested?
If you’ve built something similar, send me a message with examples or a portfolio.
Know someone who fits this? Feel free to forward this post!

Let’s build the future Youtube App Mr Beast will use, trust!

🚀 React + Firebase Dev Needed – Build MVP for Home Maintenance App (Solo Founder, Strong Vision)

Overview:
I’m building an MVP for AllProperly.com — a property maintenance and planning app designed for homeowners, adult children caring for aging parents' homes, and rental property owners. Think Monarch Money for your house — but with sharing, collaboration, and a living home history log like Carfax.



I’ve got:
- A clear product roadmap ✅
- Figma wireframes (inspired by MonarchMoney) ✅
- Brand guidelines + logo in progress ✅
- API strategy in place (Estated + more) ✅
- Tasks structured in Jira ✅
- Budget of $5k USD 💰

Now I’m looking for a smart, proactive React + Firebase developer to bring the MVP to life.


Tech Stack:
- React + TypeScript
- Firebase (Auth, Firestore, Hosting, Functions)
- Estated API (property data autofill)
- Google Calendar sync (optional for V1.1)
- Responsive design (desktop first, mobile coming next)

You’ll be responsible for:
- Building the MVP in 5 structured sprints (we already have the Jira roadmap)
- Integrating Estated API for property data
- Google Sign-In and account handling
- Task + property management flows
- Creating a simple activity log per home
- Implementing early support for shared property access

Nice-to-haves (can be post-MVP):
- Calendar UI for task reminders
- PDF generation (Home History Report)
- Stripe integration for future premium plan

Timeline:
- 4–5 weeks, starting ASAP
- Full-time or part-time as long as you're consistent and communicative
- Weekly standups with me (Founder/Product)



You’re a great fit if you:
- Have built Firebase-backed apps before
- Are thoughtful about clean, scalable code
- Work well with founders who care deeply about UX and emotion
- Like working async but can stay on a timeline



To apply:

Send me:
- 2–3 React+Firebase projects you’ve built (links or repos)
- Your hourly rate or flat rate idea
- Why this project interests you

?
Let’s make home care beautifully simple — and help families stay in sync while doing it.


I'm looking to develop a robust web application designed for on-premise deployment to serve as a Governance, Risk, and Compliance (GRC) tracking system. The application should integrate seamlessly with Radius for authentication and support a flexible database system, allowing the use of MySQL, PostgreSQL, SQLite, Oracle Database, or Microsoft SQL Server.

Key Requirements:
- Develop a GRC tracking system with functionalities for risk assessment, compliance monitoring, and incident management.
- Integrate Radius for authentication.
- Implement Role-Based Access Control (RBAC) to manage user permissions effectively.
- Ensure the application is compatible with various database systems.
- Provide examples of previous web applications you have developed.

Ideal Skills and Experience:
- Proven experience in developing web applications with complex integrations.
- Strong understanding of GRC systems and their functionalities.
- Expertise in Radius integration and RBAC implementation.
- Proficiency in working with multiple database systems.
- A portfolio showcasing similar projects or relevant experience.

Please share examples of web applications you have built to demonstrate your capability in handling this project.

📄 Job Description:

We’re looking for a developer (or small team) to help us build a lean MVP for NeuroBuddy — a HIPAA-conscious web app that allows users to upload neurocognitive test results (e.g., QEEG reports) and receive AI-generated interpretations.
We're using a hybrid no-code approach — ideally Bubble.io for the frontend and Firebase or another HIPAA-aware backend for secure data storage.

This project is designed to test proof of concept quickly, with the option to scale if validated.

🎯 Core Features for MVP:

User registration/login (Firebase Auth or similar)
File upload (PDF or structured form)
Dashboard to view uploaded files and AI results
AI-powered report generation (OpenAI API integration)
Monthly subscription billing (Stripe)
Basic admin panel to view/manage users and submissions

🔐 Important Notes:

MVP will not store PHI directly in Bubble.
We want to follow HIPAA best practices even if not formally compliant in v1.
All AI input/output will be de-identified.
Secure file handling is a must.

🧠 Ideal Experience:

Bubble.io development (required)
Firebase, Xano, or AWS (for secure file storage)
OpenAI API integration
Stripe subscription setup
Experience with HIPAA-conscious architecture is a big plus
Familiarity with mental health or healthcare apps preferred

📅 Timeline:

MVP completion target: 3–4 weeks
Quick iteration and responsiveness valued

✅ To apply, please include:

Examples of similar no-code or AI-powered apps you've built
Experience with HIPAA-aware development
Preferred backend for PHI-safe storage
Your availability over the next 4–6 weeks

the platform contain 7 services required to be with programming languages :
1- Python Django
2- Mango DB
3- Celery
4- Redis
5- Nginx
6- Gunicorn
7- Fast API (with Dynamic API)
8- AI
9- Docker
10- Multi-Tenant Design and architecture
11- React and Typescript.

interactive web design and functional , operate as SaaS or on-premises blackbox Design , Multi-Tenant services
the project include handling data and files with interactive dashboards and AI agents with High performance required,

**** Project is large size. *****

to start the project a lot of legal documents will be signed including NDA , NCA and refund with Criminal agreement ( in case of non comply with the output or delay).

Payment submission is based on the Milestone approval and submission ( Not include any non fit work or changes based on the development mistakes, any delay from the development side will not under our responsibilities)

**** Price for the entire Project not for each milestone. ****
**** Due Date For entire project 6 months ****
****** no farther information can be shared ******

Project Overview: AI-Powered Preventive Health Coach Embedded in a Moodle-Based Learning Ecosystem

1. Vision & Purpose
You are being invited to help build a next-generation preventive health education platform that combines science-backed lifestyle medicine, emotionally intelligent coaching, and personalized AI guidance in a scalable, compliant, future-proof architecture. The goal is to support individuals on health journeys—improving metabolic health, sleep, stress resilience, mindset, longevity, and daily habits—by marrying structured curriculum with a real-time AI companion that understands their progress, context, and needs.
This platform is not just another course delivery site. It is a hybrid learning + coaching system where evidence-based knowledge (from preventive medicine, nutritional science, exercise physiology, sleep science, and behavioral psychology) meets a kind, supportive AI coach that acts like a smart companion—reminding, nudging, adapting, and celebrating progress—while safely handling boundaries (never diagnosing, always escalating appropriately when needed).
The learner journey starts inside a Moodle course, where structured content (modules, exercises, lifestyle resets) is delivered, tracked, and certified. Layered on top is the AI Health Coach: a dynamic, personalized system that interprets the user’s learning status, self-reported health data, and historical interaction to deliver context-aware, motivational, actionable guidance. Over 2–3 years the architecture must allow the coach to be reused or extended into a standalone B2C mobile/web application, retaining all intelligence, history, and personalization.

2. High-Level Objectives
Primary Outcomes - Deliver personalized, adaptive coaching that helps users translate course material into sustainable behavior change. - Ensure that every recommendation is grounded in scientific evidence, tied back to course content when applicable, and delivered with empathy and clarity. - Establish trustworthy boundaries: the coach is supportive but not therapeutic; it defers diagnosis and escalation to qualified professionals when red flags appear. - Build a persistent memory per user so the system becomes more intelligent and tailored over time, recognizing past behaviors, preferences, and what interventions worked. - Integrate seamlessly with Moodle to leverage course state, deep-link into relevant lessons, and surface on-platform interventions. - Architect the solution for data protection
compliance in the Swiss/DACH context (nFADP/GDPR-style), particularly given the sensitivity of health-related data. - Design for model autonomy and evolution, such that dependence on external hosted models can be reduced over time and new frontends (like a custom app) can reuse the same intelligence.

3. Strategic Value
This system sits at the intersection of:
- Education: Structured, evidence-based lifelong learning delivered via Moodle.
- Behavioral Science: Psychology of change embedded in conversation and micro-action planning.
- Health Optimization: Lifestyle medicine for chronic prevention (e.g., metabolic reset, stress management, sleep hygiene, etc.).
- Technology & AI: A smart, adaptive coach that personalizes, remembers, and improves.
- Compliance & Trust: Data-handling standards that make it acceptable for partnerships with insurers and institutions in regulated markets.
That combination creates a defensible product: learners get real results, the platform can earn institutional credibility through tracking & certification, and the AI coach becomes a sticky, intelligent layer that differentiates and scales.

4. System Overview (Conceptual)
At a high level the system is composed of:

1. Moodle Learning Environment – Hosts the course curriculum: modules on sleep, nutrition, movement, stress, longevity; tracks completion, quizzes, competencies.

2. AI Health Coach Engine – Independent microservice that consumes user state and produces personalized advice and next actions.

3. Multi-source Knowledge Layer:
- ChatGPT (or equivalent) for delivery: persona, empathy, behavior-change framing, motivational language.
- MedGemma / Gemma self-hosted model for clinical reasoning and medical evidence synthesis.
- Primary literature retrieval (PubMed, leading institutions) and internal course content via a retrieval-augmented generation pipeline to avoid hallucination.
4. Persistent Memory – Stores user interaction history, preferences, interventions tried, and outcomes to tailor future coaching.
5. Integration Layer – Brings together learning context (from Moodle), health metrics (self-reported or tracked), and memory to assemble a sanitized, relevant user profile for the coach.
6. Frontend Embedding – An in-line coach interface inside Moodle for real-time interaction, feedback capture, and redirection to course content.
7. Compliance & Security Framework – Consent capture, pseudonymization, encryption, access auditing, red-flag detection, and user data lifecycle management.

5. Core Functional Expectations (What the AI Coach Actually Does)
- Understand the learner’s context: what modules they’ve done, where they are stuck, their health inputs (e.g., sleep quality, mood, weight trends), and their personal goals.
- Respond with a persona that is kind, supportive, empathetic, non-judgmental—acknowledging effort before suggesting the next step.
- Ground advice in:
- The course content (linking to relevant modules).
- Scientific evidence (via MedGemma and literature retrieval).
- Coaching psychology (via ChatGPT-style framing for motivation and habit initiation).
- Enforce boundaries: If a user shares something outside the intended coaching scope (relationship stress, mental health crises), the system shows empathy, pivots to immediate coping strategies (mindfulness, breathing), and if serious red flags appear, suggests seeking professional help.
- Personalize over time: Remember what advice worked, adapt phrasing to user preference, escalate or modulate intensity based on adherence and historical behavior.
- Collect feedback: Capture explicit (ratings) and implicit (compliance/outcomes) signals to refine future recommendations and build training data for evolution.
- Fail gracefully: If evidence is insufficient or a user query is ambiguous, provide transparent clarification (“I don’t have enough context to be sure—here’s a small experiment to try, and if it persists, here’s how to escalate.”).

6. Data Sources & Roles
- ChatGPT (or equivalent conversational LLM)
Role: Persona, empathy, conversational scaffolding, behavior change psychology, micro-planning, motivational reinforcement.
Constraint layer: Restrict topic drift; anchor responses to health program relevance; detect and manage out-of-scope disclosures.
- MedGemma / Gemma
Role: Clinical evidence synthesis, high-fidelity medical reasoning for lifestyle interventions (e.g., strategies to improve insulin sensitivity, evidence-based sleep hygiene), and flagging risk patterns.
Provides the scientific backbone that supports “why” a suggestion makes sense.
- Primary Literature (PubMed, Harvard, etc.)
Role: Supplement and update the knowledge base with the latest systematic reviews, meta-analyses, and domain-specific findings; indexed for retrieval to ground answers and increase credibility.
- Course Content
Role: Canonical source of interventions. Advice that maps to curriculum modules includes deep links and contextual operationalization (e.g., “See Module 5 for the full routine; try this 5-minute practice today.”).
- User Memory / Interaction History
Role: Enables adaptation, personalization, and continuity across sessions.

7. Compliance & Privacy Requirements (Strategic Imperative)
- Explicit consent management for all health-related personalization.
- Pseudonymization of identities; separate storage of PII and behavioral/health logs linked only by internal identifiers.
- Sanitization before external calls: Nothing that can identify the user (name, exact birthdate, raw sensitive medical records) is sent to third-party services unless absolutely necessary and with consent—only abstracted context goes out.
- Auditability: Every recommendation must be traceable—including which evidence/sources it referenced, what triggered a red-flag, and what feedback was provided.
- Data residency: Sensitive data lives in Switzerland or EU-hosted compliant infrastructure.
- User rights: Export, correction, and deletion must be supported for both the learning history and coaching memory.
- Escalation logic: Build-in red-flag detection with safe fallback language and referrals to qualified care when thresholds are met.

8. Future Evolution
- Engine swap capability: External dependencies (e.g., initial use of hosted ChatGPT) must be encapsulated behind an abstraction so they can be replaced by self-hosted or custom fine-tuned models in the future without changing the API or user-facing integration.
- Standalone App Reuse: After establishing proof-of-concept and traction inside Moodle, the same AI coach backend (context assembly, memory, personalization, evidence retrieval, safety logic) must be reusable in a completely new front-end (web/mobile app) to serve consumers directly.
- Learning loop: Data collected from interactions is not only used for immediate personalization but also forms the basis for gradual model improvement—either via refining prompt templates, training internal preference models, or fine-tuning open models.

9. Candidate Profile: Required Tools & Skills
This section describes the concrete capabilities the candidate must possess. Only candidates who can honestly say they have mastery or deep working experience in the core areas below should proceed; the detailed brief will be shared after vetting.

A. Core Technical Skills & Knowledge
1. Backend Development (API-first) - Strong experience building, deploying, and maintaining RESTful APIs with Python (FastAPI preferred) or Node.js (Express/Fastify). - Design of pluggable / swappable model integration layers (adapter patterns).

2. Large Language Models & Prompt Engineering - Hands-on experience integrating ChatGPT/OpenAI APIs or similar LLMs. - Skilled in prompt engineering for persona enforcement, behavior change framing, and safe output shaping. - Ability to implement scope filters to detect and manage out-of-scope input (e.g., using classifiers or heuristic parsing).

3. Open / Self-hosted Model Integration - Familiarity with models like MedGemma / Gemma or other domain-specialized open models; experience deploying and interfacing with them. - Understanding of building or integrating local inference stacks and fallbacks. - Knowledge of techniques for gradual autonomy: replacing external models with internal ones without breaking interface contracts.

4. Retrieval-Augmented Generation (RAG) - Experience with vector databases: Qdrant, Weaviate, Milvus, RedisVector, or equivalent. - Building pipelines to index heterogeneous content (course content, literature summaries, evidence snippets) and retrieve contextually relevant vectors to supplement generation.

5. Learning System Integration - Familiarity with xAPI and Learning Record Stores (LRS) (e.g., Learning Locker) or ability to consume structured learning data from Moodle via its APIs. - Understanding how to map course progress into upstream context for the coach.

6. Personalization & Memory Systems - Designing per-user memory layers: what to store, how to version, how to retrieve safely, how to use it to modulate future advice. - Experience avoiding leakage between user profiles (strict isolation).

7. Moodle Embedding / Integration - Experience embedding external widgets/APIs inside Moodle course pages. - Token/session propagation from Moodle to external systems securely. - Deep-link creation into lessons/modules.

8. Identity & Security - OAuth2 / JWT mechanisms: secure token handling and session management. - Experience with SSO flows or integrating with identity providers (e.g., Keycloak or equivalent).

9. Data Privacy & Compliance Engineering - Practical implementation of GDPR-style privacy controls: consent versioning, pseudonymization, deletions, export, audit logging. - Understanding of secure handling of sensitive health data (encryption-at-rest, in-transit, access controls). - Building red-flag detection and safe escalation flows.

10. DevOps & Infrastructure - Containerization (Docker) and ideally orchestration knowledge (Kubernetes or equivalent) for scaling components independently. - CI/CD pipelines, rollout/versioning strategies for model swaps. - Observability: logging, monitoring (performance, security), alerting. -

Experience with hosting in regulatory-compliant regions (Swiss/EU) and managing secrets (e.g., using Vault, KMS).

11. Database Design - Relational (PostgreSQL) or hybrid storage: schema separation for PII vs behavior data; encryption strategies. - Capability to scale read/write patterns for memory & context retrieval.

12. Evidence Provenance & Content Handling - Ability to ingest, structure, tag, and surface scientific evidence (guidelines, literature abstracts) in a way that’s queryable and can be attached to advice. - Familiarity with building or normalizing content using controlled vocabularies/ontologies (helpful but not strictly required at first).

B. Tooling & Ecosystem
- Git (version control, branching strategies).
- OpenAI API (or equivalent) integration.
- Vector DBs: Qdrant, Weaviate, or alternatives.
- Moodle platform (practical understanding of how to integrate outside services).
- Identity systems: JWT, OAuth2 flows, Keycloak or equivalent.
- Secure storage/encryption libraries.
- API documentation frameworks (OpenAPI/Swagger).
- Testing tools: unit/integration testing expertise, especially for data sanitization, persona output validation, safety logic.
- Observability stacks: ELK/Prometheus/Grafana or managed equivalents for logging/monitoring.
- Deployment automation: scripting blue/green or canary deployments for model updates.

C. Soft / Strategic Skills
- Strong sense of product thinking: able to translate health coaching objectives into technical implementation with user empathy.
- Clear communication: can explain trade-offs, design decisions, and potential risks, especially around safety and compliance.
- Documentation discipline: produce maintainable API specs, onboarding guides for future app integration, and model swap procedures.

- Data ethics mindset: conscious of bias, safety, user autonomy, and responsible AI practices.
- Collaborative: able to work with the client’s content/Moodle setup owner and evolve the coach jointly.

10. Nice-to-Have / Differentiators
- Prior experience with health coaching, lifestyle medicine, or preventive health tech.
- Familiarity with Swiss/EU compliance frameworks specifically (nFADP, HIPAA parallels, etc.).
- Experience fine-tuning LLMs via LoRA or parameter-efficient techniques.
- Exposure to human-in-the-loop systems for health-critical advice.
- Experience building adaptive dialogue systems that adjust based on user feedback and memory.
- Knowledge of semantic normalization (SNOMED CT, ICD, etc.) for better internal consistency (especially useful if scaling to more clinical depth).
11. Candidate Delivery Expectations (Screening Signals)
Before sharing the detailed brief, you should ask each candidate to demonstrate:
- A concrete example of a multi-source assistant they built or architected (LLM + external knowledge + personalization).
- How they handled persona enforcement and boundaries in a conversational AI (example prompts or system design).
- Their approach to data privacy in a health-related context (how they separate identity from behavior, consent capture, deletion).
- An outline of how they would design a memory system for per-user personalization without cross-leakage.
- A sketch of how they’d structure model abstraction to allow backend swaps (e.g., replacing ChatGPT with a self-hosted model).
- Experience embedding a service in a third-party platform (Moodle or similar) and propagating identity securely.

12. Summary
This project is the fusion of credible health education, intelligent coaching, and adaptive AI in a gated, compliant environment. The ideal candidate is not just a coder but a systems thinker who can:
- Fuse conversation, evidence, and curriculum into coherent, safe advice
- Build memory-driven personalization that feels human
- Maintain privacy and compliance as a first-class citizen
- Architect for evolution and reuse beyond the initial platform
If you have those capabilities and can speak concretely to how you’d implement the core pieces, you’ll be invited to receive the full detailed technical brief and proposal request.

🚀 Overview
The You Report is a personal wellness and productivity dashboard that summarizes a user’s day based on their sleep, activity, calendar, music, emails, and more. The system pulls data from services like Google, Spotify, Fitbit, Apple Health, and weather APIs, calculates a mood/recovery score, and delivers both daily and weekly insights via email and a secure web dashboard.

We’re looking for a developer to build the full system in one sprint — including backend, APIs, OAuth connections, and a lightweight frontend UI. While we’ve prototyped some logic in Google Apps Script, this is a fresh build. You’ll receive working samples, but implementation should be clean, stable, and mobile-ready.

✅ What You’ll Deliver (Single Sprint Scope)
🔐 User System
User registration, login, logout

JWT or Supabase-style session handling

Table: users with email, created_at, full_name, and service flags (e.g., spotify_connected)

🔌 OAuth & Integrations
Secure OAuth flow and token storage for:

Spotify (music activity, mood)

Google (Gmail + Calendar)

Fitbit (steps, sleep, HR)

Apple Health (via TryTerra API or similar)

Optional: Android Health (Google Fit)

OpenWeather (via zip or coordinates)

Tokens must refresh automatically and be linked to user accounts.

📊 Reports
Daily Reports (we’ll provide working Apps Script logic):

Accept JSON via POST /reports

Store summary + HTML + insights

Calculate score from mood, sleep, steps, music, weather

Weekly Reports:

Aggregate past 7 days

Return trend analysis + summary

Both types of reports must be available as:

JSON (for frontend display)

HTML (for email delivery)

📬 Email System
Automatically send daily + weekly HTML reports

Use SendGrid, Mailgun, or Gmail API

Email in batches and log delivery

🖥️ Frontend Dashboard (Simple Web UI)
Clean, minimal frontend (not using existing prototype)

User login and session

Connect/disconnect integrations

View list of past daily and weekly reports

Show status of connected services

You can use Softr (preferred), or propose a simple custom UI using your preferred stack (e.g., Next.js, Webflow, or lightweight React/HTML if faster).

Frontend should be clean, mobile-friendly, and require minimal maintenance.

⚙️ Handoff
REST API (clean routes)

Supabase/DB schema with docs

.env config

Setup instructions (self-hosted or cloud function-based)

Bonus: deployable to Supabase, Vercel, or Firebase Functions

Postman/Swagger docs optional

🧪 Provided to You
Working Google Apps Script that generates report content

Sample JSON payloads + HTML templates

OAuth middleware for Spotify

Sample report generation prompts

Guidance on scoring logic

📱 Mobile-Ready (Important)
System must be built with future mobile apps in mind:

OAuth flows must support mobile redirect URIs

REST API + token-based auth

Sessions and endpoints should be compatible with future iOS/Android builds (e.g., React Native or Flutter)

💰 Budget + Timeline
Fixed price: $1,200

Timeline: 5–7 business days

Bonus available for:

Early delivery

Clean, scalable backend

Mobile-readiness

Solid frontend UX with minimal code

✅ To Apply
Please apply only if you're confident you can complete this full system within 5–7 days. In your proposal, include:

One or two relevant projects (OAuth, health data, or personal dashboards)

Your preferred backend stack (Supabase, Firebase, Backendless, etc.) and why

Your approach to automated email delivery

Whether you’d use Softr or something else for the frontend