UST has invested in aiOla, a deep tech Israeli startup building voice-agentic AI solutions, with an aim to reshape how frontline workflow interact with enterprise systems. The investment, led by UST’s open innovation arm, UST Spark, adds fuel to the company’s ongoing efforts to advance AI-led transformation in industries with high frontline engagement.

aiOla’s platform captures unstructured speech in real-time and converts it into structured, auditable workflows. This allows field workers to perform tasks using natural voice commands, effectively bypassing outdated processes like manual data entry via clipboards or disconnected apps.

From voice to value: Data capture goes hands-free

While AI integration has found traction in back-office functions, frontline workflows have remained stubbornly analog. Clipboards, paper forms, and outdated interfaces still dominate. The result? A gap in data that could otherwise drive operational insights.

aiOla’s solution targets this blind spot. Its voice AI platform is built to function in noisy, jargon-heavy environments, interpreting speech with regional accents, abbreviations, and technical terms. According to the company, the system captures three times the data at triple the speed compared to traditional manual processes.

Frontline workers can now speak commands or notes aloud, whether on the manufacturing floor, hospital ward, or logistics center, and aiOla translates that speech into usable data across platforms like ERPs and CRMs. This hands-free approach not only increases efficiency but also reduces error-prone manual input.

AI meets real-world complexity

Unlike generic voice assistants, aiOla’s platform is designed specifically for enterprise settings. It adapts to site-specific terminology and enforces standardized processes, offering a structured alternative to loosely documented verbal workflows.

With support for over 100 languages, aiOla’s system also ensures global scalability, a crucial requirement for enterprises operating across diverse regions.

Though the financial details of the investment remain under wraps, the strategic nature of the collaboration signals UST’s growing focus on blending AI with real-world operational challenges, especially where human-machine interaction is key.