AIVA

Generates orchestral and cinematic music compositions with MIDI export for classical and film-style scoring. One of earliest AI music platforms; focused specifically on classical and film scoring use cases.

Purpose-built for orchestral/cinematic composition; MIDI output allows professional editing in DAWs, differentiating from Suno/Udio.

aiva.ai Foundation Models - MusicLuxembourgprivate

At a glance

Total raised

$1.7M

last round series a

Headcount

11-50

approximate · public range

Headquarters

Luxembourg

Founded

2016

10 years active

Status

Private

Foundation Models - Music

Latest valuation

$5M

Series A · 2024

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Funding history

Total raised

$1.7M

Rounds tracked

Latest stage

Series A

Latest valuation

$5M

Date	Stage	Amount	Valuation	Lead investors
Jul 4, 2024	Series A	—	$5M	Kayacan Ventures
Jun 17, 2020	Series A	$1.7M	—	NetEase Games
Jan 31, 2020	Undisclosed	—	—	EIC Fund
Sep 1, 2019	Undisclosed	—	—	European Union
Dec 14, 2017	Seed	—	—	Kima Ventures

Founder backgrounds

Denis Shtefan

Co-founder and CTO

Studied at UCL where he worked as a Research Intern at UCL's Communication and Information Systems Group and at the London Centre for Nanotechnology designing quantum device systems. Co-founded AIVA in 2016 in Luxembourg, where as a published researcher and composer, he leads R&D efforts to solve challenges in creative and personalised music generation using AI technologies. His background bridges physics and engineering research with music composition—a rare combination that informs AIVA's technical approach to orchestral and film-score generation. As CTO and published researcher-composer, he has guided the company's vision to build AI that serves as a genuine creative tool.

Vincent Barreau

Co-founder and COO

An engineer and musician, he joined forces with Pierre Barreau to create AIVA in 2016. As head of Operations, he ensures the business uses its resources properly. While Pierre brought vision for AI-augmented composition, Vincent contributed technical expertise in computer science and machine learning. No public record of prior exits or companies before AIVA.

AI bull / bear

Bull case

AIVA has carved out a defensible niche in orchestral and cinematic music generation, targeting professional composers and filmmakers rather than competing in the crowded consumer AI music space dominated by Suno and Udio. The MIDI export capability is a critical differentiator, allowing seamless integration into professional DAWs and enabling the fine-tuned editing workflows that scoring professionals demand. As one of the earliest AI music platforms, AIVA has years of accumulated training data, model refinement, and domain expertise in classical and film composition—a genre with complex harmonic and orchestration requirements that newer entrants struggle to replicate convincingly. The company's focus positions it to capture B2B revenue from game studios, indie filmmakers, and content creators who need production music at scale without licensing costs. As generative AI becomes table stakes in media production pipelines, AIVA's established reputation and purpose-built tooling give it first-mover advantage in a vertical where quality and professional-grade output matter more than novelty.

Bear case

AIVA operates in an increasingly commoditized market as foundation models from OpenAI, Google, and well-funded startups rapidly expand into multimodal generation, including music. Without disclosed funding, AIVA likely lacks the capital to compete on model scale, compute infrastructure, and R&D velocity against competitors raising nine-figure rounds. The narrow focus on orchestral and cinematic music limits total addressable market compared to platforms serving broader genres and use cases. The professional MIDI workflow advantage may erode as competitors add similar export features or as DAW vendors integrate AI composition natively. Meanwhile, stock music libraries and licensing platforms are deploying their own generative tools, potentially disintermediating AIVA's value proposition. With no recent funding announcements or customer traction metrics, the company risks becoming a niche tool overtaken by horizontal platforms that can cross-subsidize music generation with other modalities. The bootstrapped or undercapitalized status raises execution risk as the market consolidates around better-funded players.

Generated by claude-sonnet-4-5-20250929 · May 1, 2026Refreshes quarterly · see disclosures

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AIVA · last 30 days

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Leadership

Pierre Barreau

Co-founder and CEO

Denis Shtefan

Co-founder and CTO

Vincent Barreau

Co-founder and COO

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Products

AIVA Music Generation Assistant
Core platform for AI-powered orchestral and cinematic music composition. Users can generate original soundtracks in over 250 styles within seconds by selecting presets, uploading MIDI or audio influences, and customizing emotional tone and structure. The platform trains on classical masterpieces (Mozart, Beethoven, Bach) and generates full compositions with intros, themes, and outros. Features include professional MIDI editing, sheet music export, multiple file format downloads (MP3, WAV, MIDI), and options for commercial licensing with full copyright ownership on premium plans.
Music Engine
Commercial product suite launched in January 2019 capable of generating compositions ranging from 30 seconds to 10 minutes in diverse genres including orchestral, cinematic, jazz, pop, rock, ambient, and exotic styles (Indian, Chinese). Users can define custom musical structures, edit individual MIDI tracks for fine-tuned control, and regenerate specific sections for refinement. The engine includes preset style curation and integration with digital audio workstations for professional music production workflows.
Lyra Foundation Model
Next-generation transformer-based foundation model for instrumental music generation from natural language prompts. Generates original compositions from 30 seconds to 10 minutes, enabling creators to describe desired musical characteristics and receive AI-composed tracks. Works alongside proprietary OmniCodec neural audio codec for efficient, high-fidelity audio compression and model training to improve generation quality.

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