As artificial intelligence becomes increasingly embedded in enterprise operations, many organisations are discovering that adopting AI at scale requires more than deploying isolated tools or assistants. Companies often struggle to integrate AI systems into complex legacy infrastructures, resulting in experimental pilots that rarely translate into operational value. Addressing this challenge, Italian startup Alomana has raised €4 million to accelerate the development of its enterprise AI platform designed to transform how organisations deploy and operate artificial intelligence across their workflows.
The funding round was led by CDP Venture Capital through its Corporate Partners I ServiceTech fund. Additional investors include Italia Venture II Fondo Imprese Sud, Founders Factory, Kairos Ventures ESG One, Gresilent Holdings, Italian Angels for Growth and Club degli Investitori. The new capital will support the expansion of the company’s technology platform and help scale enterprise deployments globally.
Building an operating layer for enterprise AI
Alomana is developing what it describes as an AI operating layer for enterprise systems. The company’s platform, called Alo, is designed to enable organisations to run personalised artificial intelligence across their existing applications, data infrastructure and business processes.
While many AI solutions focus on answering questions or generating content when prompted, Alo aims to move beyond assistance and enable automated execution of complex workflows. This approach allows AI systems to carry out tasks across multiple enterprise systems and deliver measurable business outcomes rather than functioning solely as analytical or conversational tools.
By creating a unified intelligence layer that connects to existing enterprise environments, Alomana seeks to reduce the technical complexity companies face when deploying AI solutions across fragmented infrastructures.
Overcoming the limitations of legacy systems
A significant challenge in enterprise AI adoption is the reliance on legacy systems that were not designed to accommodate advanced artificial intelligence capabilities. Organisations often spend months experimenting with prototypes, integrating multiple software tools and building custom workflows.
These projects can become expensive and difficult to maintain, frequently failing to deliver reliable results when scaled across large organisations.
Alomana’s Alo platform aims to address this issue by abstracting much of the integration and customisation work required to deploy AI. The system provides a single environment where organisations can run AI powered workflows across their data, applications and documents without building complex integrations from scratch.
This approach is intended to help enterprises move more quickly from experimentation to production ready systems that deliver operational value.
Autonomous AI execution across enterprise workflows
At the centre of the platform is the Alo Autonomous Engine, which enables AI to execute tasks across different enterprise systems. The technology can analyse large datasets, generate software applications and create specialised AI agents tailored to specific organisational needs.
For example, the system can perform advanced data analysis across extensive databases, automate operational processes and support financial control workflows. It can also generate custom applications and AI driven automation tools designed to handle specialised business tasks.
By consolidating these capabilities into a single operational layer, Alo aims to provide organisations with access to what the company describes as an entire AI team operating within their technology infrastructure.
Deployment across multiple industries
Over the past year, the Alo Autonomous Engine has been deployed across several sectors including finance, manufacturing and pharmaceuticals. In these environments, the platform has been used to support mission critical processes such as risk management workflows, financial control systems, operational automation and complex data analysis.
According to the company, these deployments demonstrate how enterprise AI can move beyond experimental prototypes and generate measurable financial value when integrated into real operational processes.
A team with experience in complex systems
The Alomana team brings together professionals with experience in organisations known for operating in highly regulated and technically complex environments. Members of the team have previously worked at institutions including Bloomberg, the European Central Bank, BCG and NASA.
This background reflects the company’s focus on building enterprise grade AI systems capable of functioning reliably within industries that require strict operational standards and regulatory compliance.
Expanding enterprise AI capabilities
The newly secured investment will allow Alomana to further develop the capabilities of the Alo platform, particularly in the area of autonomous AI execution. The company plans to strengthen its technology infrastructure while expanding its enterprise customer base.
As businesses increasingly seek ways to integrate artificial intelligence into everyday operations, platforms capable of orchestrating AI across existing enterprise systems may play an important role in shaping the future of digital transformation. Alomana aims to position Alo as the operational layer that allows organisations to run AI as an integrated part of their business infrastructure rather than as isolated experimental tools.