Technology
AI and engineering for software products and platforms.
Technology companies have the highest AI literacy and the most demanding engineering standards. We work as an extension of product and engineering teams — moving fast, writing production-quality code, and owning outcomes.
Common challenges
The problems technology teams bring to us most often.
AI feature integration
Adding LLM-powered features to existing products requires careful architecture decisions around latency, cost, and reliability that most product teams are still learning.
Data pipeline reliability
Software products generate event streams and usage data that are valuable but often poorly ingested and modelled — limiting the product intelligence teams can build.
Scaling infrastructure
Growth-stage software companies frequently hit infrastructure ceilings. Cloud architecture decisions made early have long-term cost and reliability consequences.
What we build
Specific systems and capabilities we deliver for technology clients.
LLM-powered product features
Design and implementation of AI features — search, summarisation, generation, and classification — integrated into your existing product stack.
Developer tooling
AI-assisted code review, documentation generation, and test writing tools built for engineering teams.
Data infrastructure
Event pipelines, warehouses, and feature stores that give product and data teams reliable access to the data they need.
SaaS architecture
Multi-tenant architecture, authentication, billing integration, and API design for B2B software products.
Platform engineering
Cloud infrastructure, CI/CD, observability, and developer experience improvements that let engineering teams ship faster.
Related industries
Other sectors we work with.
Working in technology?
Tell us what you are building. We will come back with a clear, honest plan — no pitch, no vague estimates.