FigureAsia 35 Under 35 · AI
Mati Staniszewski
Age 30 · Founder and operating leader · Poland, United Kingdom and United States; multilingual audio products used internationally
Giving Artificial Intelligence a Multilingual Human Voice
- Age at the edition eligibility date
- 30
- Field
- Synthetic speech, voice agents and audio accessibility
- Country or region
- Poland, United Kingdom and United States; multilingual audio products used internationally
- FigureAsia U35 Assessment
- 89.6 / 100
Profile
Career and documented record
Mati Staniszewski has helped turn synthetic speech from a narrow production tool into infrastructure for media, accessibility and conversational agents. ElevenLabs’ growth in 2025–2026 demonstrates international demand for expressive audio, while the same realism makes consent, traceability and fraud prevention inseparable from its success.
Mati Staniszewski grew up in Poland and studied mathematics at Imperial College London. He later worked on technology deployments before co-founding ElevenLabs with Piotr Dąbkowski in 2022. Staniszewski leads the company commercially; Dąbkowski and the research organisation hold substantial responsibility for its underlying technical work. The company began with expressive text-to-speech and voice cloning, then expanded into dubbing, speech recognition, sound generation and conversational agents. In January 2025, it raised US$180 million at a US$3.3 billion valuation. It also reported that its impact programme had worked with 80 organisations and helped more than 1,000 people with speech impairments restore personalised voices. These are company disclosures, but they demonstrate an application extending beyond entertainment and customer service. By May 2026, the company said it had surpassed US$500 million in annual recurring revenue after ending 2025 at US$350 million. The acceleration is notable but not audited public-company reporting. The central tension in Staniszewski’s work is equally clear. High-fidelity synthetic speech can localise culture and restore voices; it can also enable fraud and impersonation. In 2025 he described safeguards including provenance, text and voice moderation, account traceability and an audio classifier. Their effectiveness at global scale remains a continuing test.
FigureAsia selection
Why Mati Staniszewski is on the list
FigureAsia selected Staniszewski because ElevenLabs has made expressive synthetic audio a globally significant AI category rather than a specialist feature. Its work spans cultural localisation, interactive entertainment, enterprise communication and voice restoration, giving the technology unusual breadth. Commercial growth alone is not the basis for selection; the stronger case is that the company has made multilingual speech generation practically deployable. FigureAsia also treats misuse prevention as part of the achievement standard: durable consent, disclosure and fraud resistance will determine whether that reach remains socially legitimate.
Verified work
The 2025–26 record
Verified contribution 01
In January 2025, the company raised US$180 million at a US$3.3 billion valuation.
Verified contribution 02
The company reported that its impact programme had supported 80 organisations and more than 1,000 personalised voice-restoration cases.
Verified contribution 03
In October 2025, Staniszewski publicly detailed provenance, moderation, traceability and detection safeguards.
Verified contribution 04
In May 2026, the company reported passing US$500 million in annual recurring revenue, up from US$350 million at the end of 2025.
Field context
The work in its field
The company serves creators, developers and enterprises across languages and industries. It reports broad corporate adoption and rapid revenue growth, although detailed geographic revenue, active-user and retention figures are not independently audited.
Multilingual speech, dubbing and conversational audio have direct significance for Asia’s linguistically diverse media, gaming, service and accessibility markets, where localisation quality remains a persistent constraint.
FigureAsia U35 Assessment
Assessment breakdown
89.6out of 100
Defining contribution
22.5 / 25
A completed piece of work, institution or system that materially changes what the field can do.
Demonstrated impact and reach
18.6 / 20
Observable adoption, scientific use, policy consequence or operational reach, with self-reported metrics labelled as such.
Personal agency and attribution
13.5 / 15
Evidence that the individual shaped the result, separated from team, employer and investor halo.
Technical or institutional originality
13.2 / 15
A new method, product form, research direction, governance mechanism or deployment model.
Durability and field-shaping influence
9 / 10
The likelihood that the contribution will remain useful beyond a single news cycle or model release.
Evidence integrity and responsible practice
8.2 / 10
The quality of the record, the precision of claims and the seriousness with which limitations and harms are addressed.
Asia–world relevance
4.6 / 5
A documented connection to Asia, impact on Asian systems, or clear importance to the region’s place in the international field.