Studied, designed, built, deployed, maintained
We are the technology departmentfor companies that need oneand don’t want to build one.
Software, data and AI — studied, designed, built, deployed and maintained. End to end, by the people who architected it. 12 engagements since 2022, and every client is still with us.
- 2022
- Building since
- 12
- Engagements
- 100%
- Client retention
- 0
- Layers subcontracted
Two ways in
Most firms tell you what to build or build it. We do both, and we are accountable for both.
Which is why our advice tends to be buildable, and our builds tend to survive contact with the business.
When you do not know what to build yet.
You have a business problem, a budget and competing opinions about the answer. We come in, learn the operation properly, and hand you a decision you can defend — with the architecture, the sequencing and the honest risks attached.
- Business process analysis and system research
- End-to-end solution architecture
- Build-versus-buy and platform selection
- Technology and AI consulting
- Scalability and cost planning
You leave with a plan, whether or not you hire us to build it. Twice we have paused paid work to say so.
When you know, and need it built properly.
A senior team that embeds in your organisation and functions as your internal technology department — designing, building, deploying and maintaining the system, then staying on to extend it.
- Data platforms — warehousing, pipelines, BI you own
- Applied AI and agents, with deterministic policy gates
- Full-stack product engineering and legacy rescue
- Kubernetes, CI/CD, security and access control
- Maintenance, extension and on-call after launch
You get working software, and the team that will still be maintaining it in three years.
Same people on both sides of the line. The engineer who will maintain the system is in the room when the architecture is decided.
How we workThe stack we hold
Six layers between a business problem and a system that solves it.
Most partners own one or two and subcontract the rest — which is where projects go quiet. Open a layer to see what we actually do there.
Before architecture, before tooling. We map your processes, your data and your people, and say honestly where the real constraint is — even when the answer is that the project you asked for is not the project you need.
What we do here
- Business process analysis
- System research & discovery
- Technology & AI consulting
- Modernisation roadmaps
- Build vs buy assessments
Tools
- Process mapping
- Systems audit
- Reverse engineering
- Roadmapping
The decisions that are expensive to reverse: what the system is made of, where the boundaries sit, and what happens to it at ten times the load with a different team maintaining it three years from now.
What we do here
- End-to-end solution architecture
- Data modelling & schema design
- Scalability & performance planning
- Security and access design
- Migration strategy
Tools
- Event-driven
- Microservices
- Monolith-first
- Multi-tenant
- Zero-downtime migration
Pipelines that do not silently break, a warehouse your executives actually trust, and dashboards built around the decisions being made rather than the metrics that were easy to compute.
What we do here
- ETL/ELT pipeline engineering
- Cloud data warehousing
- BI implementation & customisation
- Reporting automation
- Data sanitisation & QA
Tools
- Snowflake
- ClickHouse
- PostgreSQL
- dbt
- Airflow
- Dagster
Agentic systems that do real work rather than demos. We design what the agent reasons over, which tools it is allowed to call, and the guardrails that make its output something you can act on.
What we do here
- Custom agentic AI frameworks
- LLM integration & evaluation
- Semantic search & RAG
- ML and statistical modelling
- Simulation & predictive modelling
Tools
- LangGraph
- LangChain LCEL
- MCP
- Temporal
- ReAct agents
- Vector search
The surface people actually touch: internal platforms, customer portals, storefronts, map-driven applications. Built to be handed over, extended and lived with — not to look good in a screenshot.
What we do here
- Full-stack web & mobile applications
- UI/UX design & prototyping
- E-commerce & payment flows
- WordPress builds, rescues & hardening
- Geospatial & cartographic interfaces
Tools
- React
- Next.js
- Python
- TypeScript
- WordPress
- Mapbox
Delivery is the beginning, not the end. We deploy it, monitor it, patch it and extend it — which is why every client we have partnered with since 2022 is still a client.
What we do here
- DevOps & CI/CD
- Kubernetes & container orchestration
- Cloud deployment & cost control
- Monitoring & incident response
- Long-term maintenance & support
↑ all six, in-house
The toolbox
59 technologies. One team that has shipped with all of them.
We are not specialists in one corner of this — that is the whole point.
Wherever the data currently hides
- PostgreSQL
- MySQL
- Ponderosa ERP
- Excel / VBA
- xAPI events
- On-chain streams
Pipelines that do not silently break
- Dagster
- dlt
- Rivery
- Celery
- Custom durable workers
One place the numbers agree
- Snowflake
- ClickHouse
- BigQuery
- dbt
- DataHub lineage
Agents that reason over it, and gates that overrule them
- LangGraph
- LangChain LCEL
- Temporal
- MCP
- Cortex Search
- Policy engines
What people actually touch
- Next.js
- React
- Apache Superset
- Metabase
- Streamlit
- MapLibre GL
- Kubernetes
- Docker
- AWS
- Azure
- GitHub Actions
- Jenkins
- OIDC / JWT / RBAC
- Audit logging
Every stage above is built and operated in-house — hover to trace the flow.
Also worked with
Platforms we have assessed, costed, or worked against inside a client’s estate — listed apart from the toolbox because we have not run them in production ourselves: BigQuery, Tableau, Power BI, Metabase, Terraform, Google Cloud.
Selected work
12 engagements. None of them abandoned.
Replacing Sisense with a BI layer they own
Sisense replaced by a customised Superset the client owns outright, on rebuilt pipelines and a purpose-built analytical warehouse — embedded back into their own product, at CAD 600k below the licensed alternative in year one.
Owning the BI stack instead of renting it
A complete BI ecosystem the client owns outright, built instead of signing for an enterprise SaaS platform priced to grow with them.
A data and AI platform for a live game economy
Ingestion, a layered warehouse and an ML workspace over a live game economy — with a conversational layer that queries Snowflake directly through MCP.
An AI analyst for venture capital
A digital analyst that runs the top of the funnel autonomously: hundreds of millions of rows a week, a custom multi-agent router, and one-button outreach written back to the CRM.
An AI-powered learning platform for aviation training
We paused the BI work we were paid for to migrate the platform first — then built the KPI warehouse and shipped Eddy, an agentic assistant deployed as a first-class Open edX XBlock.
An AI bid analyst for public procurement
A supervised agent system with its limits designed in rather than documented: Temporal owns the workflow, and a deterministic policy engine can overrule the model.
Retrieval-augmented quoting for field maintenance
A quoting system grounded in the client’s own casebook and historical jobs, built alongside structured discovery that documented what the business needed it to decide.
A loyalty commerce platform, ERP to storefront
Three coordinated workstreams as their embedded engineering team: a live Java ERP kept shipping, a headless storefront built from scratch, and a migration toolkit that moved the data between them.
An outsourced technology department
They did not need a tool; they needed a technology department. Two years on we are still shipping — and an AI agent now ranks technicians for each event.
A rescue, and a shipping product
A cartographic application for insurance agents, inherited with more than fifty critical bugs and a budget nearly gone. We fixed the structural causes and deployed it — because the previous team never had.
Documenting the undocumentable
Years of Excel macros and MS Access reverse-engineered into the first complete blueprint of the business anyone had produced — then a phased migration, and a compromised estate rebuilt and secured.
The yardage book, turned into a data product
Every shot a player used to write down by hand — club, lie, number on the card — captured as structured data, modelled into hole-by-hole game plans, and updated live against tournament feeds while the round is still being played.
The record so far
Outcomes, not deliverables.
- 12
- engagements
- 100%
- client retention
- 300%+
- faster deal review
- $200k+
- saved annually
Across employee recognition, retail, gaming, venture capital, EdTech, professional sport and more
Every organisation we have partnered with is still working with us
Multi-agent AI analyst for a US venture capital firm
A BI stack the client owns, replacing enterprise SaaS licensing
How we work
Four commitments, and the ones that cost us money are the ones that matter.
We study before we build
Every engagement opens with analysis of the business logic, not a technology choice. Twice we have paused paid work to tell a client the project they asked for was the wrong one. Both times it saved them a rebuild.
We take the whole problem
Requirements, architecture, UI, backend, data layer, models, deployment, monitoring and the handover documentation. There is no seam where we stop and a gap begins.
We build what survives us
Architectural boundaries enforced in CI. Evidence-linked outputs. Deterministic policy gates around model decisions. Migrations, ADRs, runbooks. Another team can pick up what we hand over.
We stay
Delivery is where the relationship starts. Maintenance, extension and on-call are part of the offer, not an upsell.
Start here
Start with a problem, not a brief.
Tell us what is slow, what is manual, what is stalled, or what nobody understands any more. We will tell you honestly whether it is worth building.