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Beatoven AI Debuts Maestro for Text to Music with Artist Payouts
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Beatoven.ai unveils Maestro, its first AI model that generates music from text prompts. -
The AI is trained only on licensed music, ensuring safe and commercial-ready tracks. -
Artists whose samples were used in training will receive 30% of related revenue.
Bengaluru based startup Beatoven.ai has introduced its first in-house AI music generation model, Maestro, aimed at transforming the way music is created and shared. Unlike previous models that remixed existing samples, Maestro generates original instrumental tracks from simple text prompts.
The standout feature of Maestro is that it’s trained entirely on licensed datasets, making the output safe for commercial use without copyright concerns. This gives creators freedom to use AI generated music for films, videos, podcasts, and more.
What sets Beatoven.ai apart is its artist first approach. Through partnerships with data providers like Rightsify, Soundtrack Loops, Symphonic Music, Vadi Sound, and others, the company ensures transparency and fairness. Using Musical AI’s attribution system, artists whose data contributed to the AI’s learning will receive 30% of the revenue linked to their samples.
Mansoor Rahimat Khan, CEO, said ‘Maestro is trained on a dataset 30 times larger than the company’s previous models, making it more versatile across genres and capable of producing high-quality instrumentals. While vocals and sound effects aren’t yet included, these features are expected in future updates’.
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Access to Maestro will be available through a $20 monthly subscription tier, offering unlimited track generation but a 15 minute download cap. Beatoven also plans to offer enterprise access for studios and production houses.
Unlike AI models like Suno AI that mimic human vocals, Beatoven focuses on co-creation tools that support human creativity. “We want Maestro to complement artists, not replace them”, Khan said.
With this launch, Beatoven.ai aims to lead the ethical and collaborative future of AI generated music.
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