FlowMind

🌿 Inspiration

Mental health isn’t about doing more — it’s about doing what’s sustainable. Many neurodivergent individuals and people managing anxiety or burnout struggle with traditional productivity tools that pressure constant performance. We wanted to create FlowMind, a calm, AI-assisted companion that supports mental wellness through mindful structure, emotional awareness, and neuro-inclusive design. Our mission: to help users feel regulated, not rushed — and supported, not judged.

💫 What it does

FlowMind is a neuro-friendly, mental-health-focused planning app that uses AI mood-aware scheduling to help users align their routines with emotional and cognitive energy levels. It creates compassionate structure through:

• 🕊️ Mood-Aware Scheduling: The AI agent detects energy and mood patterns to plan focus tasks, self-care, or rest windows at optimal times.
• 💬 Compassionate Nudges: 10-3-1 minute reminders (vibration or soft audio) that gently encourage rather than pressure.
• 🧩 Micro-Steps: Every task becomes 3–5 concrete, emotionally manageable actions.
• 🎧 Calm UI Mode: Reduced motion, high contrast, voice-first interaction — lowering anxiety triggers.
• 🧠 Adaptive Energy Matching: The agent continually learns from skipped tasks and emotional feedback to adjust future routines.

FlowMind helps users feel emotionally seen by their planner — not measured by it.

🛠️ How we built it

• Frontend: Built with Expo React Native + TypeScript for iOS, applying accessibility and wellness design patterns.
• Backend: Node.js + Express server orchestrating communication between Supabase, Google Calendar, and the NeuralSeek mAIstro agent.

• Agentic Workflow (AI Layer):

  • The NeuralSeek mAIstro agent receives a real-time snapshot of user energy, focus limits, mood input, and recent engagement history.
  • It uses contextual reasoning to dynamically generate or modify weekly plans.
  • If mood is low, the agent swaps demanding blocks for lighter “movement snacks,” journaling, or restorative tasks.
  • As mood improves, the agent gradually reintroduces more cognitively demanding blocks.

• Database: Supabase (PostgreSQL) stores anonymized profiles and weekly plans.

• Local-First Privacy: Sensitive neuro-profiles remain in expo-secure-store, ensuring user control even offline.

💭 Challenges we ran into

• Mood Data Interpretation: Translating subjective mood scores into actionable scheduling decisions required fine-tuning the agent’s prompts and reward logic.
• Avoiding Over-Intervention: Ensuring the AI supported mental wellness without feeling intrusive or judgmental was a delicate balance.
• Cross-API Latency: Coordinating NeuralSeek responses with Supabase and Google Calendar while maintaining instant UI feedback tested our async pipeline design.
• User Trust: We built transparency into every recommendation so users could always see why FlowMind suggested a change.

🌈 Accomplishments that we're proud of

• Delivered fully functional mood-aware scheduling powered by NeuralSeek mAIstro’s adaptive reasoning.
• Designed a mental-health-first UX that neurodivergent testers described as “soothing, predictable, and empowering.”
• Created a local-first privacy model ensuring emotional and neuro-profile data stays safe.
• Achieved seamless multi-API integration within the hackathon timeframe — while preserving a calm, human-centered experience.
• Proved that AI can be empathetic when trained around emotional context, not productivity quotas.

🧘‍♀️ What we learned

• Emotional regulation and productivity are interlinked — tech must respect both.
• Agentic workflows can become digital companions when grounded in empathy and self-awareness.
• Minimalist, compassionate design creates a stronger sense of trust and emotional safety.
• AI’s role in wellness is to listen and adapt, not prescribe or evaluate.

🌻 What’s next for FlowMind

• Voice + Emotion Input: Expand mood tracking with natural-language voice reflection analyzed by Whisper + Gemini.
• Contextual Wellness Interventions: Suggest breathing exercises or grounding techniques during low-mood detections.
• Wearable Integration: Use passive biometrics (e.g., HRV, step count) to enrich mood-energy correlations.
• Community Reflection Mode: Anonymous group journaling or shared affirmations to promote connection.
• Clinical Collaboration: Partner with therapists and cognitive scientists to validate FlowMind as a digital wellness aid.

FlowMind represents a new category of AI-driven emotional wellness technology — one that treats mental health and productivity not as opposites, but as partners in living intentionally, compassionately, and in flow.

Built With

• auth0
• elevenlab
• expo.io
• neuralseek
• openai
• react-native
• supabase
• typescript