Experience music that adapts to you — in real time.
Our GPU-accelerated recommendation engine blends audio signal, raga/time-of-day, mood/context, and listening behavior into a unified 315‑dimension profile.
Request a Demo📡 Live AI Telemetry: Phase 4 Engine
What is 315-Dimension Feature Fusion?
This is the "Neural Language" of our system. We compress 150 spectral audio features (texture/timbre), 96 Raga-specific melodic mappings, 40 mood/acoustic attributes, and 29 temporal context points (time-of-day/user history) into a single mathematical vector that represents the exact "flavor" of a musical moment.
Why Bidirectional LSTM?
Unlike standard AI that only looks at what you played last, a Bidirectional LSTM processes the sequence in both directions. It understands the "momentum" of your current session while simultaneously looking back to ensure the next recommendation feels like a natural evolution of the entire listening experience.
Next‑Song Prediction
Bidirectional LSTM + attention over 50 tracks deliver fast recommendations tailored to your unique context.
Skip Prediction
Identify likely skips before they happen; pre‑filter queues and optimize shuffle using 7-day behavioral memory.
AI Audio Enhancement
Noise reduction, spectral enhancement, and GPU-driven normalization for consistent studio quality across your library.
Projected Performance
Prediction latency*
Top‑5 accuracy*
GPU utilization*
50‑song batch*
* Internal benchmarks on NVIDIA GeForce RTX 4070/RTX 5060 Ti. Results vary with data and tuning.
Smart Radio
Infinite, AI‑curated playback that respects mood and time‑of‑day. Uses 24-hour recency decay to keep variety high.
Developer‑Ready APIs
- POST /predict/next
- POST /predict/batch
- POST /predict/skip/{song_id}
- POST /enhance/{song_id}
- POST /radio/start
- GET /radio/{station_id}/next
Observability & Control
Real-time GPU status monitoring and health checks ensure Phase 4 remains stable under heavy load.
AI Model Visualizations
A look under the hood at the clustering and feature engineering that powers our recommendation engine.
1. Cluster Distribution
What it shows: How our library is segmented into 40 distinct clusters to balance variety in recommendations.
2. Cluster Embeddings (PCA Plot)
What it shows: A 2D map of musical similarities. Closer clusters represent similar genres or moods.
Get Started
Deploy the Advanced Phase and bring adaptive listening to life. Contact us for a guided demo and integration plan.
Contact SalesDisclaimer
This website is for learning purposes only.
All commercial queries, please mail us at [email protected].
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