We design and build data lakes, lakehouses and warehouses, implement analytics on top of them, and develop custom big data applications shaped around what your business actually needs.
We provide insights-as-a-service: actionable business insight out of your data, through pipelines designed around your goals rather than a generic template.
We review your business processes against the goals you have set, and propose the best way to digitise them. As a big data development partner we make that work data-driven and transparent in decision-making terms — project assessment, design, implementation, testing, deployment and support, on demand.
We collect, clean and structure your data for analysis and visualisation, then design the pipeline around it — real-time streaming, batch, or a lambda architecture — and build the lakes and warehouses underneath. That includes warehouse architecture consulting and development, implementation, advancement or migration.
We arrange lakes and warehouses for effective storage, retrieval and insight mining. Raw data arrives from all your sources; taking your specifics into account we clean and analyse it, and keep finding new ways to use it to add business value.
On top of the data we build custom AI models that simplify decision-making. Handing big data analysis to a model prevents human error, improves efficiency and cuts cost.
We visualise the insight we mine so it is readable by the person who has to act on it. We agree the reports and dashboards up front, then build a system that generates them from the data in your lakes and warehouses — which is where visualisation stops being decoration and starts reshaping strategy.
Need big data app development?
Our cross-functional team of data scientists, engineers, architects and consultants turns data into business value — maximising the investment with current AI tooling.
Understand behaviour and intent from the data you already collect.
Find where process time and spend actually go, then remove it.
Automate the repetitive decisions that currently need a person.
Build and promote products against evidence rather than instinct.
Reduce spend by deciding earlier and on better information.
See market movement and competitive position while it still matters.
We analyse your business environment, domain specifics, performance and data sources, define the challenges and set the goals. Our analysts and engineers then propose the solutions that address them.
We aggregate data into representations suited to storage and processing. Preparation covers standardisation, missing values, outlier filtering and whatever else the material needs — including the specifics of text and image data.
We analyse with current statistical methods and a range of machine learning and data science algorithms. The insight surfaces the roadblocks and the non-obvious parts of a process so they can be improved quickly.
We deploy on AWS, Azure or Google Cloud. Where you prefer on-premise, we build a custom system on the Python scientific and ML stack and integrate it into your infrastructure with the databases, containerisation and frameworks the use case calls for.
Here is the high-level architecture of a data foundation solution: sources feed ingestion and storage, transformation makes the data usable at any size, and the serving layer turns it into reporting, apps, alerts, APIs and shared datasets.
Thirty minutes with an engineer, not a salesperson. You leave with a rough scope, a cost band and an honest read on feasibility.
30 minutes with an engineer · No slide deck · Reply within one business day