This capital will fuel continued growth and product expansion for Spike, which offers healthcare and digital health businesses a solution to safely, efficiently, and compliantly incorporate AI into their applications, addressing increasing customer demand.

The healthcare industry generates approximately 30% of the world's data volume, partially due to the adoption of medical and commercial IoT/wearable devices by over a billion users, according to LEK. This figure is expected to rise further, thanks to rapid advancements in sensor hardware technologies. As a result, healthcare and healthtech businesses, ranging from science-backed fitness studios and digital health apps to nutrition clinics and hospitals, are seeking to incorporate AI into their operations.

By leveraging new health data, large language models (LLMs), computer vision, and other machine learning (ML) techniques, these organisations can offer hyper-personalised and preventative health products to their end-users. However, integrating these technologies often faces challenges, including strict regulatory compliance on sensitive health data, LLM hallucinations, intense competition for AI engineering talent, lengthy development timelines, and high costs.

Through its white-labeled SDKs, Spike provides non-diagnostic and easy-to-implement RAG AI (Retrieval Augmented Generation) products for health professionals and end-users, such as personal trainer co-pilots for fitness progress summaries on wearable data, dietitian co-pilots with nutrient value assessment from meal photos, nurse co-pilots to manage post-treatment patient follow-up, and physician co-pilots to detect early anomalies from electronic health records (EHR) and lab test data.

Spike's competitive advantage is its health data API aggregator platform, feeding high-quality biomarkers from 300 sources, which helped secure Spike's place at NVIDIA's Inception Program designed for GenAI startups in Silicon Valley. Spike's customer base includes global insurance leader Seguros SURA, fitness apps Longevo and FITTR, sleep innovation company EMMA, women's wellness app Moody Month, and vagus nerve stimulator Pulsetto.

Povilas Gudzius, Spike CEO and Co-founder, commented, “Advancements in retrieval-augmented generation AI mean that LLMs are no longer taking a ‘best guess,’ but are now able to seek out specialised context producing outputs that are much more accurate and considerably less prone to hallucinations. By incorporating this technology on top of Spike’s high-quality health data API, we’re enabling our clients to easily leverage these tools and improve the health of millions of end users.”

Donatas Keras, Partner at Practica Capital, commented, “We were impressed by the Spike team’s technical expertise and go-to-market skills. Given their rapid traction and widespread adoption of AI products with formidable competitive moats, leading this round was a natural fit for us. As the influx of sensor data changes some parts of the health industry, Spike is well-positioned for significant growth, and we are excited to partner with such a forward-thinking team.”

Álvaro Sanz, Partner at TheVentureCity, commented, "The fact that Spike was able to close an oversubscribed round and accumulate significant investor interest, particularly in this down market, is a validation of Spike's potential."

Spike was founded 18 months ago by Povilas Gudzius, who previously worked on the Quant data and AI team at Bloomberg in NYC, and Cambridge-educated Chief Data Officer Nikita Pajanok. The team is supported by Auguste Kakneviciute, former Lead of IoT Sales at Ubuntu; Monika Da Silva Xavier, ex-Google; Anton Autushka, ex-Head of Engineering at Wannaby (sold to Farfetch) and 18 other talented tech specialists.

The seed investment will fuel Spike’s development of regulatory-compliant and safe Generative AI products and expansion to support a broader range of medical, wearables, and IoT sensor data aggregation from over 600 devices. Those will expand to Electronic Health Records (EHR) data, blood testing, lab testing, genomics data, and FDA-approved devices and datasets.