Enterprise Integration & Data
Connect your systems and turn data into decisions — seamless integration, robust pipelines, and analytics you can trust.
Make your systems work as one
Most enterprises run on a patchwork of systems that don't talk to each other. We connect them — with reliable APIs, integration layers, and data pipelines that move information where it needs to be, when it needs to be there.
Then we make that data useful: warehoused, modeled, and surfaced through analytics and BI so your teams can act on what's actually happening.
What we deliver
From first integration to enterprise-wide analytics.
API Integration & Gateway
Secure, well-documented APIs and gateways that let your systems exchange data reliably and at scale.
ETL Pipeline Development
Extract, transform, and load pipelines that move and reshape data dependably between every source and target.
Data Warehousing
Centralized, modeled warehouses that give your whole organization one consistent source of truth.
Business Intelligence & Analytics
Dashboards and reporting that turn raw data into the insights leaders need to make confident decisions.
Legacy System Modernization
Migrate ageing platforms to modern architectures without losing the data and logic your business depends on.
Real-time Data Processing
Streaming and event-driven pipelines that act on data the moment it arrives, not hours later.
How we deliver
Audit
Map systems, data flows, and constraints.
Design
Integration patterns and the data model.
Build
APIs, pipelines, and warehouses.
Operate
Monitoring, quality, and governance.
The stack we build on
Frequently asked questions
An API integration answers a question at the moment it is asked, against live data. An ETL pipeline moves data on a schedule into a store designed for analysis. Reporting directly on live transactional systems is the common mistake: it slows the transactional system and still produces inconsistent numbers.
Almost always because each system defines the measure slightly differently and nobody has written those definitions down. The fix is one agreed definition per measure, applied in a single place — a warehouse or semantic layer — rather than recalculated independently inside each report.
Usually yes. Where a legacy system exposes no API, integration is done through scheduled extracts or a read-only database adapter, wrapped behind a service boundary. That buys time to modernise deliberately instead of making a full replacement the entry cost of any integration at all.
Establishing what the system actually does — which is rarely what the documentation says — then moving functionality out in slices behind a stable interface, so old and new run together during the transition. A single-cutover rewrite is the highest-risk option and is worth avoiding on an operationally critical system.
Power BI is the most common in delivered work, including a unified reporting implementation for a multi-entity enterprise client. The tool matters less than the model beneath it: a well-built warehouse is portable across reporting front ends, whereas reports built directly on source systems are not.
Ready to unify your data?
Tell us where you want to go. We'll bring the engineering precision to get you there — fast.