Agent development.
Agents that read and act across the applications a business already runs, with a person approving what matters.
The Technologies We Run in Production.
How we build agents and how we build software with AI, then the languages, frameworks, platforms, clouds and databases we have built our own products and dozens of client products with. Each page says what the technology is good for, what we build with it and where it is not the right choice, so a stack decision can be made before a contract is.
The technologies we build with.
Languages, frameworks, data stores, clouds, AI libraries and tools our teams run in production, 286 in all; the marks with a page of their own link to it.
Twenty-one technologies, seven categories.
AI engineering, Languages, Frameworks, Mobile, Platforms, Cloud, Databases.
AI-driven software development.
Agents write, test and review code against written rules; a person gates every release and every change leaves a record.
Python.
Data analysis, machine learning, automation and web backends on Django and Flask.
Java.
Enterprise portals, e-commerce platforms, REST APIs and microservices with a long service life.
React.
Component-based front ends and single-page applications for web products and internal tools.
Angular.
TypeScript single-page applications where the codebase is large and the team is too.
Flask.
Lightweight Python web applications, REST APIs, microservices and prototypes.
.NET Core.
Cross-platform web applications, content systems and APIs on the open-source .NET platform.
TensorFlow.
Training, serving and scaling machine learning models, on servers, in the cloud and on devices.
PyTorch.
Deep learning research, prototyping and custom models, integrated and deployed into products.
Scikit-learn.
Predictive models, segmentation and feature engineering on Python's standard machine learning library.
React Native.
Cross-platform iOS and Android apps, migrations and interface design on React Native.
Flutter.
Cross-platform mobile apps in Dart, with interfaces designed for portrait and landscape on both platforms.
Node.js.
Event-driven backends, REST APIs, real-time features and content systems in server-side JavaScript.
Docker.
Containerisation, CI/CD integration, Kubernetes orchestration and container security.
Apache Kafka.
Real-time data pipelines, cluster setup and operation, stream processing and system integration.
AWS.
Cloud migration, infrastructure setup, DevOps automation, security and cost optimisation on AWS.
PostgreSQL.
Custom database design, migrations and upgrades, and performance tuning on PostgreSQL.
MongoDB.
Document databases for catalogues, content, profiles, logging, file sharing and geospatial data.
SQL Server.
Relational database design, development and tuning on SQL Server, usually beside .NET.
Redis.
In-memory caching, session storage, queues and real-time counters beside a primary database.
Where these fit.
Software Services.
Every solution we build is made of these: design, web and mobile development, backends and data, quality and operations, and the planning before any of it.
Custom Software Development.
The capability these pages belong to: how we build custom software, and when we do not.
The solutions these are built into.
Integrated business solutions for operationally complex industries, sold as outcomes rather than hours.
We'll tell you if we're a fit. If we're not, we'll tell you that too.
- Your current stack works and nobody wants to change it
- You want licences resold at a discount and nothing else
- Your internal team owns the operating model and is not handing it over
- You want hours of configuration work and nothing run for you: that is on our services pages, and it is not a managed solution
Most of our best clients come to us with a feeling, not a plan.
"Something isn't working." "We're outgrowing our tools." "We're afraid to make the wrong move." No-Risk Discovery is a short, practical conversation that gets you clarity before you commit to anything big. We'll tell you if we're a fit. If we're not, we'll tell you that too.