Data & AI ArchitectureBuild
Agents are only useful if they can access the right information, act in the right systems and do both within clearly defined permissions. We design and build the data and integration architecture that makes this possible inside your existing environment, without waiting for a new enterprise data platform.
Your data does not need to be perfect. It needs to be usable.
In most banks and insurers, the information a process needs already exists, across core systems, document stores, mailboxes, data platforms and partner applications. The problem is that it was never organised for agents that need to retrieve, reason over and act on it during a live process.
Waiting for every source to be consolidated into a new data platform delays the business case. We instead start from the process going into production: what information does the agent need, where does it live, how fresh must it be, what may the agent do with it and what evidence must remain afterwards?
We start with the processes moving into production and work backwards from what they require. For each agent and workflow, we define the documents, records, transactions and context it needs; the source systems they come from; their required quality and freshness; and the permissions under which they may be used.
We then build the access layer for that scope: extraction and transformation where information is unstructured, retrieval where context needs to be assembled, and interfaces where agents need to read from or act in operational systems. Identity, permissions, lineage and logging are part of that architecture from the beginning.
In parallel, we define what should become reusable across further implementations like shared data services, interfaces, retrieval patterns and architecture principles, and what should remain specific to an individual process. Each new use case should extend the foundation rather than create another isolated AI stack.
The data foundation for agents to operate in the real business.
Operational data, interfaces and access controls designed around the processes being automated today, with an architecture that can be extended as further agents and workflows move into production.
Operational data access
The documents, records and transactions each agent needs made available at the required quality and freshness, with permissions, lineage and evidence appropriate for production use.
Interfaces to existing systems
Controlled ways for agents and workflows to retrieve information and execute actions across core, satellite and partner systems without creating another system of record.
Reusable AI architecture
Shared patterns for models, agents, retrieval, integrations, identity and data access that future implementations can build on instead of starting again.
Bring us one process and its data.
Tell us which process you want agents to work in and where its information lives. In a 45-minute working session, we look at what the agents would need to access, which systems are involved and what has to be in place before production.