Expand your organisation’s capabilities with AI.

Handle more work, improve the quality of your services or take on problems that have been out of reach.

We help you identify where AI can contribute, design and build the systems, and adapt the tools and practices around them. Together, we define how to assess progress against your goals.

On this page

Three ways to work together

Start with scoping, go straight into delivery or bring us in alongside your team. Each is a separate way to work together.

Scoping

Identify where AI could improve performance or make a new capability possible. Compare approaches and define how to evaluate the result.

We follow real cases with your team, examine the data and systems, and compare possible approaches. AI is one option; ordinary software or a process change may be the better answer.

What you receive

A description of the current work, dependencies and access requirements.
A proposed scope, architecture and measures for evaluating the result.
A delivery plan with priorities, estimates and decisions still to make.

Delivery

Design, build and release the system, with the integrations, interfaces and controls your project needs.

We carry out the agreed project with your team and our partners. We build the integrations, interfaces and controls, test representative cases, and prepare release and recovery.

What you receive

Working software, integrations and configuration within the agreed scope.
Evaluation cases, test results, access rules and operational logs.
Release and recovery procedures and documentation for your team.

Operational support

Help your team evaluate new possibilities, make technical and product decisions, and improve the systems and practices already in place.

We work alongside internal teams on architecture, AI adoption, product decisions and delivery practices. The scope can include coaching, technical reviews, experimentation or ongoing improvements.

What you receive

Documented decisions on use cases, models, data and infrastructure.
A prioritised plan, reviews of the work and evaluation of experiments.
Working practices and documentation your team can use.

Knowledge

Make your knowledge available for more decisions

Organise and connect your documents so people and AI can find relevant information, check its sources and use it to prepare answers or decisions.

Knowledge base organisation

We organise your documents, identify authoritative sources and define how to maintain them so people and AI can use the same information.

Possible uses

Bring scattered internal procedures together.
Build a shared reference for support teams.

RAG systems

Retrieval-augmented generation searches an index of your content to give the model relevant information and sources to cite in its answers.

Possible uses

Search technical documentation in everyday language.
Prepare a support response using product documentation.

Tools & workflows

Increase the volume your teams can handle

Build agents and interfaces that prepare cases, retrieve information and carry out selected steps, with people reviewing the decisions that need their judgement.

MCP servers

We build Model Context Protocol servers that give AI applications access to selected data and actions in your software, with explicit permissions.

Possible uses

Let an assistant look up a record in your CRM.
Make a stock lookup or ticket creation available to an agent.

Agentic workflows

We connect AI agents to your tools to carry out several steps of a task, with human approval and recovery when a step fails.

Possible uses

Classify a request and prepare it for the right team.
Assemble a case file and request the missing information.

Custom interfaces

We design experiences around the task, with sources, comparisons and approval controls where people need more than a chat box.

Possible uses

Review an AI proposal beside its source document.
Approve or correct suggested actions in a work queue.

Infrastructure

Meet your cost and data management requirements

Evaluate models and hosting options against response time, output quality, cost and data sensitivity. Build the infrastructure and controls around those choices.

Token use & performance

We measure token use, response time and output quality, then adjust models, context and caching against those measures.

Possible uses

Investigate the cost of processing a document.
Reduce waiting time in an internal assistant.

Model hosting

We deploy and operate open-weight or custom models on your premises or in dedicated infrastructure, according to your constraints.

Possible uses

Run a model on your internal network.
Host a specialised model in a private cloud.

Data sovereignty & security

We define where data, workflows and results are processed, who can access them and what is retained, then implement and test those controls.

Possible uses

Restrict document access by team.
Review data flows and keep a record of sensitive actions.

Organisation

Develop the skills and practices to use AI well

Decide what to delegate to AI, how to review its output and how responsibilities should change. Coach your teams and prepare them to maintain and improve the system.

Changes to how teams work

We help teams define what to delegate to AI, what to review and how roles and working practices need to change.

Possible uses

Define who approves an AI-assisted decision.
Train a team using cases from its daily work.

Evolving tools, replaceable vendors

We isolate dependencies and build evaluations so your team can test new capabilities and change models or providers without rebuilding the whole system.

Possible uses

Compare a new model on your real use cases.
Prepare a provider change with exportable data.

Debt, ownership & skills

We review AI-generated code, interfaces and working practices to identify technical, design and organisational debt and keep your team able to maintain the system.

Possible uses

Review a prototype before putting it into production.
Document choices and practise maintenance with your team.

A team shaped around the project

The team depends on your existing systems, the work to be done and the skills you already have. Ratna brings together engineering, product and design, with specialist partners where needed.

We can deliver the system, work alongside your team or coach it on specific topics. Our proposal names the people involved, their contribution and how we will work together.

More about Ratna

Work you can entrust to Ratna

You can also draw on our experience in engineering, product and design to delegate work that matters to your product and organisation, with or without AI.

Refactoring & reducing debt

We prioritise and address technical, design and organisational debt by refactoring code, reworking interfaces and revising working practices.

Possible uses

Refactor a module that has become difficult to maintain.
Clarify an approval process that slows down releases.

Quality assurance & CI/CD

We establish quality assurance practices, automated tests and continuous integration and deployment pipelines to check changes and prepare releases.

Possible uses

Detect regressions before a release.
Automate checks and deployment steps.

Your next product version

We design and build a new version of your product around existing uses and the changes you want to introduce.

Possible uses

Redesign a core user journey.
Replace an ageing application and prepare the migration.

Exploratory prototypes

We build prototypes to test a use case, an interaction or a technical approach before you commit to developing it.

Possible uses

Test a new interface with its intended users.
Check whether an idea works with your data and tools.

Before release, we agree who will run the system. We prepare the documentation, access and recovery procedures for your team, or define the scope of continued support.

Tell us what you want to achieve.

A challenge you have not been able to solve, a service you want to improve, or an idea AI could make possible.

Tell us your goal and what stands in the way. A few lines are enough to start.