- Alinia AI raises $2.4 million in Pre-Seed funding for secure deployment of generative AI.
- Challenges include maintaining control and safety amidst rapid adoption and navigating forthcoming regulations.
- Co-founders Ariadna Font Llitjós and Carlos Muñoz Ferrandis bring extensive expertise in AI governance.
- Alinia’s Alignment process ensures adherence to expected behaviors, policies, and regulatory mandates.
- The Alinia Alignment Platform consolidates tools for comprehensive AI governance.
- Funding round led by Speedinvest and Precursor, with participation from notable angel investors.
- Alinia intends to recruit additional talent to enhance its alignment platform.
Main AI News:
Alinia AI, a platform facilitating the secure and controlled deployment of generative AI aligned with organizational policies and objectives, has successfully raised $2.4 million in Pre-Seed funding.
While the adoption of generative AI is on the rise, its rapid integration poses significant challenges.
Among these challenges is the imperative to maintain control and safety to mitigate risks of producing inappropriate or damaging content.
Furthermore, navigating forthcoming regulatory frameworks such as the EU AI Act, Biden’s Executive Order, or Canada’s Bill C-27 presents an additional layer of complexity, necessitating thorough safety assessments and comprehensive documentation.
The assessment of generative AI performance and reliability, considering both safety and business perspectives, remains a major hurdle for enterprises today.
This complexity is particularly pronounced for companies employing advanced techniques like fine-tuning and RAG, managing LLM versions, and coordinating across diverse teams comprising machine learning, governance, and business domain experts.
Alinia AI was co-founded by Ariadna and Carlos Muñoz Ferrandis.
Ariadna Font Llitjós previously served as the Head of ML Platform at Twitter, where she spearheaded the implementation of responsible AI practices across the organization. Prior to that, she held the position of Director of Development at IBM Watson during the nascent stages of enterprise AI, overseeing the development of pioneering AI assistants and other enterprise solutions. She holds a PhD in NLP from Carnegie Mellon University.
Carlos Muñoz Ferrandis, on the other hand, brings his expertise as the former Tech & Regulatory Affairs Counsel at Hugging Face, where he played a key role in governing open LLMs and was deeply involved in EU AI Act compliance efforts. With a PhD from the Max Planck Institute for Innovation and Competition in Munich, he also served as an external advisor for OECD AI on AI regulation.
“The technology is not yet mature for real-world business applications. Enterprise leaders rightly fear the repercussions of deploying generative AI systems that deviate from expected behaviors. Protecting reputation is a top priority,” says Ariadna Font Llitjós, co-founder and CEO of Alinia.
“Through our Alignment process, we ensure that AI systems conform to established behaviors, policies, and regulatory mandates – empowering enterprises to leverage this transformative technology while mitigating associated risks.”
Font Llitjós witnessed firsthand, during her tenure at Twitter, the adverse impact of unintended bias in training data and ML algorithms on vulnerable populations.
This insight drives her mission at Alinia, enabling other companies to deploy generative AI responsibly for the benefit of their employees and customers.
The Alinia Alignment Platform aims to deliver a comprehensive AI governance solution – consolidating various tools – encompassing evaluation, real-time monitoring, state-of-the-art optimization techniques, and documentation features to ensure compliance across every stage of the LLM lifecycle.
It equips customers with clear and precise evidence of how LLM-powered applications behave across diverse enterprise scenarios, adhering to specific tasks and regulatory guidelines.
“In my experience at Hugging Face, ensuring governance and safety in LLM development demands significant time and effort. However, when on the brink of releasing a foundational model with millions of potential users, governance and safety become non-negotiable,” asserts Carlos Muñoz Ferrandis, co-founder and COO.
The funding round was led by Speedinvest and Precursor, with participation from KFund and notable angel investors including Clem Délangue and Thom Wolf (Hugging Face Co-Founders), Tom Preston (GitHub Co-Founder), Xavier Amatriain (Google Core AI VP), and Oriol Vinyals (Google DeepMind VP of Research).
Fred Hagenauer, Partner at Speedinvest, comments: “Ari and Carlos possess exceptional expertise to address the alignment challenge within the generative AI landscape. Their deep understanding and experience in early enterprise AI, RAI, and contemporary LLM governance make them uniquely qualified. Supporting them was an obvious choice for us.“
Oriol Vinyals, VP Research at Google DeepMind, emphasizes: “The responsible development and utilization of powerful machine learning models should be a collective concern, and diversity is crucial in this domain. Ari and Carlos’ commitment to tackling this nuanced challenge with Alinia is immensely valuable.”
Tom Prestner, Co-Founder of GitHub, adds: “Alinia’s emergence is perfectly timed. Most companies are still in the exploratory phase, experimenting with LLMs internally for non-critical business operations. However, this paradigm is poised to shift soon.”
Alinia intends to allocate the funding towards recruiting additional talent to enhance the Alinia Alignment Platform, establishing an end-to-end alignment process prioritizing safety and regulatory compliance – facilitating the secure and inclusive utilization of generative AI across diverse LLM modalities and languages.
Conclusion:
Alinia AI’s successful funding round highlights the growing importance of responsible AI deployment in the market. Their innovative approach addresses critical challenges in ensuring AI systems adhere to regulatory requirements and ethical standards, positioning them well to capitalize on the increasing demand for safe and reliable AI solutions. This signifies a shift towards a more conscientious approach to AI adoption, emphasizing the need for robust governance and compliance measures in the evolving landscape of artificial intelligence.
