Battle-tested tooling, chosen for your context
We are fluent across the modern stack and opinionated about when to use each part of it. Here is what we build with, and how we decide.
Reference architecture
Experience
React, Next.js, React Native
WebMobilePortalsEdge & API
Edge rendering, rate limits, SSO
GatewayAuthGraphQL / RESTServices
NestJS, Java, .NET, Kafka
Domain servicesWorkflowsEventsAI layer
OpenAI, Anthropic, LangChain
LLM appsRAGAgentsEvalsData
dbt, Snowflake, Redis
PostgreSQLWarehouseVector DBCloud
AWS, Azure, GCP, Terraform
KubernetesIaCObservability
- React
- Next.js
- Angular
- TypeScript
- Tailwind CSS
- React Native
- Node.js
- NestJS
- Java
- Spring Boot
- .NET
- Python
- PostgreSQL
- MongoDB
- Redis
- MySQL
- Elasticsearch
- AWS
- Azure
- GCP
- Kubernetes
- Terraform
- GitHub Actions
- OpenAI
- Anthropic
- LangChain
- Vector DBs
- RAG Systems
- PyTorch
- Snowflake
- BigQuery
- dbt
- Apache Kafka
- Airflow
- Power BI
A reference stack, layer by layer
Boring, proven technology at the bottom; the newest AI tooling only where it earns its place at the top.
Fast, accessible front ends
React and TypeScript on the web, React Native and native where it matters, with Core Web Vitals budgets built into the definition of done.
Performance budgets on every build
Models, retrieval and evaluation
LLM orchestration, vector search and evaluation harnesses that keep quality measurable as models change underneath you.
Evals shipped with every model
Infrastructure as code, everywhere
AWS, Azure or GCP with Terraform, containers and CI/CD pipelines that make environments reproducible and hand-over painless.
Three clouds, one operating model
Frontend
Fast, accessible interfaces built on mature component ecosystems.
Backend
Robust services and APIs in the runtime that fits your team.
Database
Relational, document and in-memory stores chosen per workload.
Cloud & DevOps
Automated, observable infrastructure on every major provider.
AI & Machine Learning
Model-agnostic LLM and ML tooling with evaluation built in.
Data & Analytics
Pipelines and platforms that make data trustworthy and usable.
Every stack decision is a documented choice
We start from your constraints, compare a small number of viable options, prove the risky parts with a spike, and record the decision so anyone can understand why it was made.
Your constraints
Team skills, hosting, compliance, budget
Option A
Managed platform
Option B
Open-source stack
Option C
Hybrid
Decision record
Spiked, costed and written down as an ADR
Fit over fashion
We choose tools for your team, hosting and constraints, not for our portfolio. Boring technology wins more often than not.
Secure by default
Every stack we recommend has a mature security posture, an active community and a clear upgrade path.
Measured performance
Performance budgets, load tests and Core Web Vitals targets are part of the definition of done.
Built to hand over
We favour widely adopted technologies so your team, or any capable team, can own the system after us.
Boring where it should be, sharp where it counts
Terraform, containers and pipelines underneath; evaluation harnesses and observability on top of every model we ship.
Need an independent view on your stack?
Our architecture reviews take two to four weeks and produce a risk register and a sequenced roadmap your team can act on immediately.