Sherpa.ai, a company specialising
in artificial intelligence for data privacy and security, has raised $18
million in a funding round to accelerate the development of its AI platform for
enterprises and governments and expand its work on AI systems built around data
sovereignty.
The round includes new investor Forgepoint Capital, a Silicon
Valley venture capital firm focused on cybersecurity and artificial
intelligence. Existing investors Mundi Ventures, Ekarpen, Allegra Holdings and
SETT also participated.
The funding follows a period of
commercial growth for the company. In recent months, Sherpa.ai has signed
contracts with organisations including Indra, the US National Institutes of
Health (NIH), Centogene Genomics, Caja Laboral, Unicaja and Prosegur. The
projects span sectors including healthcare, finance, industry and government,
where privacy, security and data sovereignty are key considerations for AI
deployment.
As organisations and governments
increasingly prioritise sovereign AI capabilities, Sherpa.ai develops AI
infrastructure designed to enable organisations to train, deploy and operate
models collaboratively without sharing sensitive information. The platform is
intended for use in regulated environments where data privacy and security
requirements can limit AI deployment.
Xabi Uribe-Etxebarria, founder and CEO at Sherpa.ai, said:
This
round allows us to accelerate our vision: to develop and commercialise a secure
and scalable artificial intelligence
platform that enables companies and governments to harness the full potential
of AI without giving up
control, privacy and sovereignty over their data.
In parallel with its commercial
expansion, Sherpa.ai has expanded its research activities by publishing
peer-reviewed studies on privacy-preserving AI, reflecting its ongoing
investment in developing and validating its technologies.
Recent research includes Towards
the Next Frontier of LLMs, Training on Private Data: A Cross-Domain Benchmark
for Federated Fine-Tuning, which explores methods for training large language
models on private, distributed datasets without sharing sensitive information.
Sherpa.ai also collaborated with
the US National Institutes of Health (NIH) and University College London (UCL)
on Training Together, Diagnosing Better, a study examining the use of federated
learning for rare disease diagnosis.
In addition, the company has published
research on Blind Federated Learning and distributed training techniques that
reduce communication requirements by up to 99 per cent, with applications in
sectors including healthcare, finance, cybersecurity and industry.
Sherpa.ai said it plans to expand
the capabilities of its platform throughout the year, including additional
features for enterprise and public sector users.