Services
AI Engineering
We design and build software that uses language models where they help: answering questions from your documents, drafting and classifying text, and running multi-step tasks with tools. Each system is evaluated against real examples before it ships.
The problem it addresses
Teams lose hours searching for information, re-reading documents and doing repetitive judgement work. Generic chat tools don't know your data, can't take action in your systems and are hard to trust.
Who needs it
Companies with large document collections, support or operations teams handling repetitive questions, and product teams adding AI features to an existing application.
What it covers
- AI application development
- LLM integration
- Retrieval-augmented generation
- Knowledge assistants
- Agentic workflows
- Model integration and evaluation
Typical deliverables
- A working application or API integrated with your systems
- An evaluation set and a report on accuracy against it
- Prompt, retrieval and model configuration under version control
- Cost and latency estimates for production use
How to begin. Send us a description of the task and a handful of real examples. We'll tell you whether AI is a good fit and what a first version would cover.
Discuss ai engineeringIntelligent Automation
We map a process as it runs today, then automate the steps that don't need a person: connecting APIs, extracting data from documents, routing work and building small internal tools for what's left.
The problem it addresses
Manual processes are slow, inconsistent and hard to scale. Data gets re-typed between systems, documents wait in inboxes and nobody can see where a request is stuck.
Who needs it
Operations, finance and support teams running recurring processes across several tools, and growing businesses whose manual workarounds no longer keep up.
What it covers
- Workflow automation
- API integration
- Document processing
- Internal tools
- Process optimisation
Typical deliverables
- A process map of the current and automated workflow
- Integrations and automations running in your environment
- Monitoring and alerts for failed runs
- Runbook documentation for your team
How to begin. Walk us through one process that takes too long. We'll identify which steps can be automated and estimate the effort.
Discuss intelligent automationCustom Software
Full-stack development of web applications, backend services and APIs, with the database design, integrations and deployment pipeline to run them reliably.
The problem it addresses
Off-the-shelf tools cover the common case but not the parts that make your business different, and spreadsheets stop working once several people depend on them.
Who needs it
Businesses with a process no product handles well, and teams that need engineering capacity to build or extend an internal or customer-facing application.
What it covers
- Web application development
- Backend engineering
- API development
- Database architecture
- System integration
Typical deliverables
- Source code in your repository, with tests
- Architecture and data model documentation
- A deployment pipeline and hosting setup
- A handover session for your team
How to begin. Tell us what the software needs to do and who will use it. We'll propose a scope for a first release.
Discuss custom softwareData Engineering
We build pipelines that extract data from your sources, transform it into consistent models and load it where it's needed, plus the analytics and processing that sit on top.
The problem it addresses
Data lives in many systems in different shapes. Reports disagree, analysis takes days of preparation and AI projects stall because the underlying data isn't ready.
Who needs it
Teams making decisions from several data sources, companies preparing data for AI work, and products that need to process data reliably at volume.
What it covers
- Data pipelines
- Data extraction
- Data transformation
- Analytics systems
- Intelligent data processing
Typical deliverables
- Scheduled, monitored pipelines
- Documented data models
- Data quality checks
- Dashboards or datasets ready for analysis
How to begin. List the data sources involved and the question you need answered. We'll outline the pipeline and where the data should live.
Discuss data engineeringSaaS Product Development
End-to-end development of software-as-a-service products: scoping a minimum viable product, designing the architecture, and building authentication, billing, multi-tenancy, deployment and monitoring.
The problem it addresses
Founders need to launch quickly without building on shortcuts that become expensive to undo. Accounts, billing and tenant isolation are easy to get wrong early.
Who needs it
Founders building a first product, and companies turning an internal tool or service into a product they can sell.
What it covers
- MVP development
- Product architecture
- Authentication
- Billing integration
- Multi-tenant applications
- Deployment and monitoring
Typical deliverables
- A deployed product with accounts and billing
- Architecture documentation and a roadmap for the next releases
- Monitoring, logging and error tracking
- A codebase your future team can take over
How to begin. Describe the product, who pays for it and what the first version must do. We'll propose an MVP scope and architecture.
Discuss saas product developmentHave a problem worth solving?
Let’s turn your next idea or operational challenge into a practical software solution.
Start a conversation