🧠 Neuroacoustic MVP — Technical Scope

Goal: Build a system that generates personalised, neuroscience-informed sound experiences (Focus / Calm / Sleep / High) using AI-generated music and entrainment DSP, personalised via user inputs or wearables.

Duration: 4–6 weeks

Stack: Node.js (API) · React (frontend) · Python (DSP) · ElevenLabs Music API · Docker · AWS/Supabase

1️⃣ MVP OBJECTIVES

🎵 AI-generated base music for each desired state using ElevenLabs Music API.

🧬 Neuroscience entrainment layer (binaural or isochronic beats) blended over music.

⚙️ Real-time adjustment of entrainment parameters (frequency, intensity).

📊 User session tracking (selected state, time, completion).

💡 Simple adaptive loop using HRV or self-feedback.

💻 Modern web interface (React) to select a state and play generated sound.

2️⃣ USER FLOW (MVP version)

User opens web app → selects mental state (Focus / Calm / Sleep / High).

Frontend calls Node.js API → requests base music generation from ElevenLabs.

Node receives music → sends to Python DSP microservice to add neuro layer.

Node returns final track URL (S3/CDN or data URI) → React plays audio.

User gives optional feedback (e.g. “felt calmer”, “too intense”) → stored to DB.

Optimiser adjusts parameters for next session.

3️⃣ CORE FEATURES (Phase 1 MVP)

Feature	Description	Owner
State Selector UI	Simple React interface (4 buttons: Focus, Calm, Sleep, High)	Frontend
AI Music Generation	Generate music from ElevenLabs Music API via Node	Backend
DSP Processor (Entrainment)	Python microservice adds binaural or isochronic beats based on preset frequency	DSP
Adaptive Parameters	Backend logic adjusts diffHz & mix level based on state or user feedback	Node
Session Storage	Save user ID, state, timestamp, settings, feedback	Backend (Supabase)
Web Player	HTML5/React audio player with progress and loop	Frontend
Admin Dashboard (optional)	Simple session list (user ID, state, feedback)	Backend

4️⃣ TECH STACK

🟢 Frontend (React)

React + Vite + Tailwind

Web Audio API for volume control and optional local modulation

Socket.io-client for live updates (future)

Deployed on Vercel / Netlify

🟣 Backend (Node.js)

Express or Fastify REST API

Routes:

POST /session → generate and return track URL
POST /feedback → log user feedback

Integrations:

ElevenLabs Music API
DSP microservice (HTTP)
Supabase (DB + auth)

Deployed on AWS ECS or Railway

🔵 DSP Microservice (Python)

FastAPI + Pydub/Numpy

Endpoint /render

Input: base music URL, diffHz, mixDb, mode
Output: mixed track URL or data URI

Default modes:

Focus: 10 Hz (alpha)
Calm: 7 Hz (theta)
Sleep: 4 Hz (delta)
High: 16 Hz (beta)

🟠 Database

Supabase (PostgreSQL + API)

Tables:

users (id, name, preferences)
sessions (id, user_id, state, params, result_url, timestamp)
feedback (session_id, rating, notes)

⚫ Optional Analytics

Simple metrics: total sessions, average duration, state popularity

Logged via Supabase or Google Analytics

5️⃣ API CONTRACTS (simplified)

🎵 `POST /session`

Request:

json
{
  "userId": "123",
  "state": "focus",
  "durationSec": 120
}

Response:

json
{
  "sessionId": "abc123",
  "trackUrl": "https://cdn.anomate.ai/tracks/focus_abc123.wav",
  "parameters": { "mode": "binaural", "diffHz": 10, "mixDb": -18 }
}

💬 `POST /feedback`

Request:

json
{
  "sessionId": "abc123",
  "rating": 4,
  "comment": "Felt very focused after 3 min"
}

Response:

json
{ "ok": true }

6️⃣ TIMELINE (4–6 weeks)

Week	Deliverables	Owner
1	Setup repo, Docker, ElevenLabs API, baseline React UI	Dev Lead
2	Implement /session route + DSP service (static presets)	Backend + DSP
3	Integrate audio playback + basic feedback form	Frontend
4	Deploy on staging (AWS/Vercel) + DB connection	DevOps
5	Add adaptive parameter tuning (simple rule-based)	Backend
6	QA, user testing, polish UX, deploy MVP	All

7️⃣ MVP OUTPUT EXAMPLE

User selects “Focus”

→ System generates music with 10 Hz binaural beat at -18 dB mix

→ Plays in browser

→ After session, user reports “good focus”

→ Optimiser slightly increases duration next time

8️⃣ NEXT PHASE (POST-MVP)

Once MVP is validated:

Add WHOOP / Muse / Apple Health integrations for HRV, EEG.

Personalise entrainment dynamically (Bayesian optimiser).

Add user profile AI that remembers what worked best.

Mobile app wrapper (React Native).

Paid subscriptions and session library.

⚠️ 9️⃣ Notes / Constraints

ElevenLabs currently outputs full tracks; ensure API plan supports desired call rate.

Keep entrainment under -18 dB to avoid auditory fatigue.

Include disclaimer: “For relaxation & focus purposes only, not medical treatment.”

Implement volume guard and session timeout (max 30 min).

✅ 10️⃣ Deliverable Summary

Deliverable	Description
🎛️ Web app (React)	Select state, play session, give feedback
🔗 Node.js API	Handle sessions, call ElevenLabs, integrate DSP
🧠 Python DSP	Add binaural/isochronic modulation
💾 Database	Store sessions & feedback
🌐 Hosted demo	Accessible MVP URL
📘 Documentation	Setup + API spec + state parameter table

MVP Pitch System Architecture Overview Fine Tune Audience by Feedback Neuroacoustic MVP — Technical Scope

🧘‍♂️ Introduction: Neuroacoustic MVP

We’re building a first-generation sound experience that blends AI-generated music with neuroscience-informed frequencies to help people focus, relax, sleep, or recharge — all through sound that adapts to each listener.

The MVP is a lightweight, web-based prototype designed to prove the concept that personalised sound can actively influence mental states.

It’s not about generic meditation tracks — it’s about creating an intelligent sound system that learns from every session.

🎯 What It Does

Personalised Sound on Demand – Users choose the state they want to reach (Focus, Calm, Sleep, or High Energy).

AI-Generated Music – The system instantly creates an original track using ElevenLabs’ advanced music generation engine.

Neuroscience Layer – A second layer of subtle frequency modulation (binaural or isochronic beats) is added, scientifically tuned to guide the brain into the chosen state.

Adaptive Feedback – Users give simple feedback (“felt relaxed”, “too strong”), or the system reads biometric cues like heart rate variability.

Continuous Improvement – Each session refines the next one, learning which sound frequencies and intensities work best for that individual.

💡 Why It Matters

Evidence-based: Built on decades of research showing that rhythmic sound patterns can help the brain reach specific mental states (focus, relaxation, deep sleep, etc.).

Personalised: No two users are the same — our system evolves with each listener’s feedback.

Scalable: Runs entirely online, instantly delivering unique, adaptive audio experiences to anyone, anywhere.

Data-Driven: Over time, the platform learns collective patterns — which sounds work best for which people and contexts — building the foundation for a future AI wellness coach.

🚀 MVP Objective

The MVP’s purpose is to validate three key hypotheses:

AI-generated sound can match the quality and emotional tone of curated playlists.

Subtle neuro-frequencies can create measurable shifts in user state (self-reported calmness, focus, or HRV).

A feedback loop can personalise audio over time without needing human supervision.

If these hold true, the system becomes a foundation for a larger adaptive sound intelligence platform that can power wellness apps, smart devices, or branded experiences.

🛠️ What We’ll Deliver

A working web app where users can select a mood and instantly listen to adaptive, AI-generated audio.

Real-time sound modulation based on proven neuroscience principles.

A feedback system that records user response and gradually personalises future sessions.

A live demo environment to showcase to partners and investors.

🌍 Vision Beyond the MVP

The long-term goal is to build a closed-loop system that understands and responds to human physiology — a soundtrack that listens back.

By combining sound, AI, and biosignals, we can help people manage energy, focus, and emotional balance in a natural, effortless way.

🧘‍♂️ Introduction: Neuroacoustic MVP

The MVP is a lightweight, web-based prototype designed to prove the concept that personalised sound can actively influence mental states.

It’s not about generic meditation tracks — it’s about creating an intelligent sound system that learns from every session.

🎯 What It Does

Personalised Sound on Demand – Users choose the state they want to reach (Focus, Calm, Sleep, or High Energy).

AI-Generated Music – The system instantly creates an original track using ElevenLabs’ advanced music generation engine.

Neuroscience Layer – A second layer of subtle frequency modulation (binaural or isochronic beats) is added, scientifically tuned to guide the brain into the chosen state.

Adaptive Feedback – Users give simple feedback (“felt relaxed”, “too strong”), or the system reads biometric cues like heart rate variability.

Continuous Improvement – Each session refines the next one, learning which sound frequencies and intensities work best for that individual.

💡 Why It Matters

Evidence-based: Built on decades of research showing that rhythmic sound patterns can help the brain reach specific mental states (focus, relaxation, deep sleep, etc.).

Personalised: No two users are the same — our system evolves with each listener’s feedback.

Scalable: Runs entirely online, instantly delivering unique, adaptive audio experiences to anyone, anywhere.

Data-Driven: Over time, the platform learns collective patterns — which sounds work best for which people and contexts — building the foundation for a future AI wellness coach.

🚀 MVP Objective

The MVP’s purpose is to validate three key hypotheses:

AI-generated sound can match the quality and emotional tone of curated playlists.

Subtle neuro-frequencies can create measurable shifts in user state (self-reported calmness, focus, or HRV).

A feedback loop can personalise audio over time without needing human supervision.

If these hold true, the system becomes a foundation for a larger adaptive sound intelligence platform that can power wellness apps, smart devices, or branded experiences.

🛠️ What We’ll Deliver

A working web app where users can select a mood and instantly listen to adaptive, AI-generated audio.

Real-time sound modulation based on proven neuroscience principles.

A feedback system that records user response and gradually personalises future sessions.

A live demo environment to showcase to partners and investors.

🌍 Vision Beyond the MVP

The long-term goal is to build a closed-loop system that understands and responds to human physiology — a soundtrack that listens back.

By combining sound, AI, and biosignals, we can help people manage energy, focus, and emotional balance in a natural, effortless way.

AI Music App Frontend

Neuroacoustic MVP — Technical Scope

🧠 Neuroacoustic MVP — Technical Scope

1️⃣ MVP OBJECTIVES

2️⃣ USER FLOW (MVP version)

3️⃣ CORE FEATURES (Phase 1 MVP)

4️⃣ TECH STACK

🟢 Frontend (React)

🟣 Backend (Node.js)

🔵 DSP Microservice (Python)

🟠 Database

⚫ Optional Analytics

5️⃣ API CONTRACTS (simplified)

🎵 POST /session

💬 POST /feedback

6️⃣ TIMELINE (4–6 weeks)

7️⃣ MVP OUTPUT EXAMPLE

8️⃣ NEXT PHASE (POST-MVP)

⚠️ 9️⃣ Notes / Constraints

✅ 10️⃣ Deliverable Summary

🧘‍♂️ Introduction: Neuroacoustic MVP

🎯 What It Does

💡 Why It Matters

🚀 MVP Objective

🛠️ What We’ll Deliver

🌍 Vision Beyond the MVP

🧘‍♂️ Introduction: Neuroacoustic MVP

🎯 What It Does

💡 Why It Matters

🚀 MVP Objective

🛠️ What We’ll Deliver

🌍 Vision Beyond the MVP

🎵 `POST /session`

💬 `POST /feedback`