Meiro launches local AI CDP for regulated sectors

Meiro has launched Local AI CDP for banks, insurers and other regulated sectors. The product is designed to keep AI inference within infrastructure controlled by the customer.

The launch comes as regulators and policymakers raise concerns about AI governance, sovereignty and resilience in financial services. The product is now generally available in markets including the UK, the Nordics, Australia and the Middle East.

Local AI CDP is intended to let organisations run AI models, including large language models and smaller specialised models, within their own environments rather than sending customer data to external model providers. This allows institutions to use customer profiles for tasks such as personalisation, audience building, reactivation, next-best-action and analytics, while keeping the model in the same deployment as the data it reads.

Meiro is targeting a problem that has emerged as banks, insurers and telecom groups look to apply AI agents to customer records. Marketing and data teams want to use transactions, product holdings, behavioural signals and service histories in AI-driven services, but security, legal and compliance teams are often reluctant to approve transferring that data to external platforms.

That tension has also been reflected in official policy work. The UK government's Financial Services AI Adoption Plan identified AI sovereignty and resilience as barriers to wider AI use in financial services, while Australia's prudential regulator, APRA, warned that "governance, risk management, assurance and operational resilience practices are not keeping pace with the scale, speed and complexity of AI adoption."

Meiro says the product can be deployed on-premises, in a private cloud, within a customer's own AWS, Azure, Google Cloud or Oracle account, in hybrid form, or as a managed service with regional data residency. The core functionality remains the same across those deployment options.

Customers can also choose the underlying model and, in most configurations, switch models without rebuilding the wider customer data stack. That is intended to reduce reliance on any one external AI provider while preserving existing marketing operations.

Deployment model

Meiro distinguishes the product from approaches that focus on where data is stored but not where AI inference takes place. It argues that warehouse-native and zero-copy architectures may still leave open the question of whether customer context is being processed by an external model.

The company describes its approach as keeping both the AI model and the customer data it uses within the organisation's own boundary. At the same time, the product still connects to data sources and destination systems in the usual way, meaning the restriction applies to AI processing rather than all network traffic.

The rollout reflects a broader effort across regulated industries to adopt AI without weakening internal controls over sensitive information. In sectors such as banking and insurance, where customer data is closely tied to compliance obligations and operational risk, the location of model processing has become as important as the location of storage.

Meiro, which is headquartered in Singapore and was founded in 2017, focuses on customer data software for regulated and data-sensitive industries. It serves customers across Asia-Pacific, the Middle East and Europe in sectors including banking, financial services, telecom, retail and travel.

Pavel Bulowski, chief executive officer of Meiro, said: "Your customer data should not become someone else's AI training set. It is the hard-won asset that makes your business valuable. AI is only useful when it understands real customer context, but companies should not have to send that context to Big Tech or frontier labs to use it. Meiro brings the model to the data, inside the boundary the business controls."