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Modern data platform, ready for AI
Most enterprises still run AI projects on infrastructure that was never designed for it. We help you build the data infrastructure to support the powerful AI agents that make a difference across your organisation.
The cost of legacy data
If you are still on a legacy system, AI projects hit your data infrastructure and cannot get through.
Informatica, Talend, SSIS, stored procedures: these tools did a job but they were built for a world where data moved slowly and analysts had time to wait.
In a world where an AI agent needs to answer a question in seconds, legacy systems are a blocker, with their slow queries, ungoverned data, and lack of a single source of truth for the metrics that matter most.
And the business logic that defines how your organisation works is buried in pipelines that nobody fully understands any more.
What an AI-ready data platform looks like
A modern data platform is a stack of components built to work together. Infinite Lambda builds on three: Snowflake or Databricks for compute and storage, dbt for transformation, and Fivetran for ingestion.
Snowflake & Databricks:
compute that scales with your data
Optimised for structured analytics, SQL-first teams, ML, and large-scale data engineering. Your data warehouse is fast, governed, and designed to support the kind of concurrent, low-latency querying that AI agents require.
dbt:
transformation logic your team can actually maintain
dbt brings software engineering discipline to data transformation, making it version-controlled, tested, documented, and readable by anyone on the team.
For AI, dbt is where your canonical metrics live. When an agent asks what revenue was last quarter, it is dbt that defines what revenue means and makes sure the answer is consistent across every system that queries it.
Fivetran:
reliable data ingestion without the engineering overhead
Fivetran automates the movement of data from your source systems into your data platform. It handles hundreds of connectors out of the box and manages schema changes automatically, keeping data fresh without manual intervention.
For teams that have spent years maintaining brittle custom ingestion pipelines, Fivetran removes an entire category of maintenance work.
How to Build a modern data platform
Data modernisations used to take years, because legacy systems and logic are difficult to navigate.
There are dependency chains that nobody has mapped, business logic buried in stored procedures written by people who left long ago, and the painstaking work of reconciling data between old and new systems.
To make the process smooth and predictable, we build Flowline to handle all three. Flowline is an end-to-end modernisation solution that crawls your legacy estate, maps every dependency, converts the logic to dbt and Fivetran, and reconciles the data row by row.
The archaeology that would take your team months happens automatically.
Looking to modernise?
It all starts with a Flowline crawl of your existing infrastructure. It tells you what you have, what it will take to modernise it, and what your semantic layer could look like.
Request a free demo and we will show you what it surfaces on a legacy estate like yours.