Dutch Generative AI Startup Neople Raises $1.65M

Dutch generative AI startup Neople has raised about $1.65 million (€1.5 million) in a funding round led by Peak Capital and CuriosityVentures. Neople offers companies a platform for building digital workers that integrate across various business environments with a goal of making AI more accessible for all types of workers.

Neople Needs

Neople designs digital workers to engage with multiple large language models and trains them on company information, including product descriptions, FAQs, and past conversation data. The AI assistants can adapt their tone of voice and interaction style to match a company’s brand voice and requirements. The virtual co-workers can operate within the same platforms as the employees, including Slack, Microsoft Teams, and contact center software like Zendesk.

“Neople are virtual colleagues, not just a smart chatbot,” Neople CEO Hans de Penning told Voicebot in an interview. “The difference is that chatbots are a good tool for narrow automation, something that works in a narrow focus, but what we aim to do is create the best colleague you could imagine – like onboarding a new employee to your company.”

Neople’s first focus is on deploying more virtual assistants to support customer service teams, an area where generative AI is rapidly expanding. NLX recently integrated generative AI into its conversational designer for virtual assistants and contact center AI platform Observe.AI just debuted its own 30-billion-parameter LLM and related generative AI tools. And customer service automation startups like Ada, NLX, Hyro, and Conversica have all embedded generative AI in some form into their platforms. Though Neople hasn’t faced much competition yet, de Penning said he expects there to be high demand for the technology among businesses. That said, the relative flexibility of Neople’s creations makes him confident that they will stand out among competitors.

“Our Neople have capabilities like smart marketing workflows, elastic search, and more all built in. We use LLMs for natural language recognition and interactions with users, to find the right information and follow optimal workflows,”  de Penning said. The LLM used depends on the type of case we are executing. The same Neople can handle returns for customers, send messages to suppliers, and more – being flexible across different platforms and tools. The intelligence is not just in one of your tools; it’s in all of your tools.”

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