Voice AI startup aiOla raises $25 million, eyes United Airlines collaboration
Startup eyes real-world speech recognition challenges in aviation and beyond.
aiOla, an Israeli voice and conversational AI company, has raised $25 million in a Series A2 funding round, bringing its total funding to $58 million to date. The round includes a strategic investment from United Airlines Ventures, which could pave the way for broader collaboration between the airline and the startup.
Full list of Israeli high-tech funding rounds in 2025
aiOla develops systems designed to convert spoken information into structured, machine-readable data, even in environments where generic voice recognition often fails. The company’s technology is built to handle noise, multiple languages, heavy accents, and technical jargon, aiming to help field workers and frontline staff record information on the fly rather than relying on manual data entry.
United Airlines Ventures said it is exploring ways to apply aiOla’s voice tools across its operations, from ground crews to maintenance teams. The goal is to turn spoken instructions and reports into real-time, structured data that feeds directly into backend systems, potentially streamlining tasks that today require forms and manual updates.
“aiOla’s technology addresses a basic but widespread challenge: how to reliably capture spoken information in complex environments and use it immediately,” said Andrew Chang, Managing Director of United Airlines Ventures. “We see broad potential across the travel industry and beyond.”
The funding comes as demand for voice AI continues to expand. The global market for speech recognition tools grew by about 25% last year, reaching $5.4 billion, according to industry estimates. While tech giants like OpenAI and ElevenLabs are pushing the field forward, aiOla says its strength lies in tailoring its speech engines to specific industries and workflows, an area where general-purpose models often struggle.
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The company’s flagship system, called Jargonic, uses a patented model to detect industry-specific terms with high accuracy. aiOla says the model can be quickly adapted to new domains, offering companies a way to automate reporting and data entry without overhauling existing processes.
“Voice is still the simplest way to get information from the field to the system,” said Amir Haramaty, aiOla’s president and co-founder. “But in practice, it’s still underused because so much speech recognition falls short when there’s noise, multiple speakers or specialized terminology.”
