AI Applications
AI that answers from your own documents and links each answer to its source.
Systems Integration that links AI to your existing tools and data
We connect AI applications and new software to the systems you already run, so they reach the right data under your access rules. Connections start read-only. Your systems of record stay in place.
APIs, data feeds, events and file exchange
An AI application is only as useful as the data it can read and the actions it may take. We link your records system or ERP, document stores, sign-in, business applications and external feeds. Where a system has no API, we use controlled file exchange.
Problems it solves
A new tool proves its value but cannot reach the data it needs.
- An AI pilot worked on a data copy but cannot reach live systems.
- Staff copy data from one system to another by hand.
- Each new tool adds a sign-in and another copy of the same records.
- No one can say which system changed a record, or when.
How we work on an integration
We start read-only wherever possible, so the first connections cannot change your records.
Discovery
We list each system’s owner, interfaces, formats and access rules, then agree each link’s purpose and the build order.
Pilot on your data
We build the key links against a test environment, then live data, and show data moving end to end.
Production
We add agreed write-back, error handling, retries, logging and alerts, then document each interface.
A single read-only connection to begin
We connect one source system to the tool that needs its data, read-only and under your access rules. Every call is logged, the connection is tested in a staging environment and we agree how failures are reported. The pilot ends with a connection your IT team has reviewed and a plan for the next ones.
What we need from you
We need the list of systems, an owner for each, the access rules that apply and interface documentation or a test environment.
What you get
- An integration map: systems, owners, interfaces and data flows
- Connectors and APIs for the agreed systems
- Scheduled data feeds with validation and error handling
- Single sign-on and role mapping
- Interface documentation and runbooks for your IT team
- MCP endpoints where AI assistants need your data
Related solutions
Data Platforms
One clean data model, so dashboards, search and AI show the same figures.
Modernization
Modernize legacy systems step by step, each new part checked against the old one.
Frequently asked questions
Our core system has no API. Can it still be integrated?
Often, yes: through agreed read access to its database, scheduled exports or file exchange. In Discovery we check which options the system owner and vendor support.
Will the AI be able to change our records?
Only if you decide it should. Any write-back is limited to agreed actions, runs under defined permissions and is logged.
What is MCP, and do we need it?
The Model Context Protocol is an open standard that lets AI assistants call tools and read data in a controlled way. You need it only if your staff use AI assistants.
Name the systems your AI needs to reach
For each system, note the data it holds. We will map the links and access rules, then propose the first connection.