Fincons & Expert.ai expand AI tie-up for enterprises

Fincons Group and Expert.ai have expanded their partnership to bring neuro-symbolic AI to the enterprise market, targeting organisations that run AI in core business processes.

The agreement combines Fincons' systems integration work with Expert.ai's approach to artificial intelligence, which blends neural models with structured knowledge and symbolic reasoning. The joint offering is aimed at large organisations that need AI to fit into existing IT architectures and operational workflows.

Both companies are targeting businesses moving beyond pilot projects and testing broader use of AI in day-to-day operations. A central focus is multi-agent architectures, in which several AI agents work together in a shared context to handle more complex tasks across business functions.

That shift has created new challenges for companies in regulated sectors such as banking, insurance, energy and utilities. The main obstacles are now governance, knowledge management and accountability, rather than access to the underlying technology.

The partnership is intended to address those concerns by using explicit rules and domain knowledge alongside machine learning models. The goal is to give organisations greater visibility into how AI systems make decisions and where their operational limits lie.

Regulated sectors

Fincons focuses on IT consulting and systems integration for large organisations in sectors including financial services, media, manufacturing, transport, public administration and utilities. It says it has more than 2,500 staff and offices in several European markets, as well as the United States and India.

Expert.ai, listed on Euronext Growth Milan, operates in Europe and North America and focuses on AI software for businesses and public bodies. Its customer base includes companies in insurance, pharmaceuticals and financial information, reflecting industries where explainability and control have become central to AI deployment.

Early work on multi-agent systems has shown that uncertainty over data meaning, decision rules and the boundaries set for AI agents can undermine trust and make broader deployment harder. This is especially acute in sectors with strict compliance requirements, where automated decisions can carry operational or financial risk.

Neuro-symbolic AI has drawn attention as one way to address that problem because it combines data-driven learning with formal reasoning and structured knowledge. Supporters say this can make outputs easier to trace and manage than systems built solely around large language models.

Fincons and Expert.ai are positioning the partnership as a way to embed that model within complex corporate technology environments rather than offer it as a stand-alone AI tool. For large organisations, integration with existing applications, workflows and governance structures often determines whether an AI project remains experimental or moves into routine use.

Giuliano Altamura outlined the rationale for the tie-up.

"This partnership comes at a pivotal moment in the evolution of AI solutions, as multi-agent architectures move from experimentation into core business processes. Governance, responsibility and knowledge management are becoming the real differentiators for scalable and sustainable adoption. It's not just about making AI more powerful, but about making it reliable enough for highly regulated and high impact contexts," said Giuliano Altamura, Chief Business Officer, Fincons Group.

Agent systems

Expert.ai said demand reflects a broader market shift towards agent-based systems that require clearer operational controls. Businesses want AI tools that can be managed within established rules rather than deployed as opaque black boxes, it argues.

Andrea Ricotti described the technical and operational requirements the company sees emerging in the market.

"It is becoming increasingly clear that developing agent-based architectures requires solutions that not only harness the power of the most advanced AI models, but also integrate knowledge, rules and operational responsibilities in a way that is explicit, manageable and scalable," said Andrea Ricotti, SVP Channel Development EMEA at Expert.ai. "In this context, Expert.ai's neuro-symbolic approach-combining generative AI capabilities with semantic understanding-together with Fincons' deep expertise in integrating AI into enterprise systems and processes, creates the ideal foundation for designing agent-based architectures that are reliable, controllable and built to scale."

The partnership reflects a broader shift in the AI market as suppliers respond to corporate concerns over oversight, auditability and operational risk. In industries where automated decisions must be justified to regulators, customers or internal control functions, those factors are becoming as important as model performance.