AI DEVELOPMENT & INTEGRATION
AI Development
& Integration
Add AI to the tools and workflows your business already uses. From document search to AI assistants and automation, start with a clear use case and build towards a working solution.
Discuss your AI projectFROM USE CASE TO WORKING SOLUTION
- Choose the right use case
- Prototype and evaluate
- Integrate and improve
Your workflows. Your data. A clear purpose.
WHAT WE CAN BUILD
AI that fits the way your business works
Start with a specific problem: information that is hard to find, documents that take too long to process, or repetitive tasks that slow your team down. The solution can be a focused integration, an internal tool or a feature in your existing product.
AI assistants
Create assistants that help employees or customers find information, prepare responses and complete clearly defined tasks.
Example use case: An internal assistant for product or support questions.Search across your documents
Connect an AI interface to approved knowledge sources using retrieval-augmented generation (RAG), with links back to relevant documents.
Example use case: Answers based on your manuals, policies and product documentation.Document processing
Extract and structure information from documents, classify incoming files and route results into your existing tools.
Example use case: Turn incoming forms or reports into structured records for review.Workflow automation
Combine AI with business rules, APIs and human approvals to reduce repetitive steps in everyday processes.
Example use case: Classify requests, prepare a draft and send it to a person for approval.AI features for existing products
Add summarisation, semantic search, content assistance or other focused AI capabilities to your website or application.
Example use case: Summaries and search inside a customer portal or business application.AI integrations & agent workflows
Connect models to specific systems, with defined permissions, action limits and approval steps for consequential actions.
Example use case: A workflow that retrieves records and proposes an update for confirmation.START WITH THE RIGHT PROBLEM
A useful starting point for your AI project
You do not need a finished specification. Bring a workflow, a business question or a product idea. We can start by defining what success would look like and where AI could add value.
Sometimes a conventional integration or a simpler automation is the better choice. We can discuss that too.
Tell us about your use case →- A clear business goalWhat should become faster, easier or more useful?
- Relevant data and accessWhich information can the solution use, and who is allowed to see it?
- A way to check resultsHow will you measure accuracy, usefulness and acceptable errors?
- An owner for the workflowWho will review results, approve actions and provide feedback?
HOW WE WORK
From a focused use case to a working solution
Agree on the problem and the evaluation criteria before expanding the scope. Each stage should give you evidence for the next decision.
Discovery
Review your workflow, available data, systems, constraints and intended users. Define a focused first scope.
Prototype & evaluation
Test the approach on representative examples. Review output quality, response time and estimated running costs.
Development & integration
Build the agreed interface and integrations, including access controls, error handling and human review where needed.
Launch & improvement
Roll out to the agreed users, collect feedback and monitor results. Plan support and further changes around real usage.
QUALITY, DATA & CONTROL
Plan for real-world use from the start
AI output can be incomplete or incorrect. A production solution needs clear boundaries, evaluation and a practical way to handle uncertain results.
- Evaluate on your tasksUse representative examples and agreed acceptance criteria instead of relying only on an impressive demonstration.
- Keep people in controlDefine which outputs need review and which actions require explicit approval.
- Make costs visibleConsider model usage, hosting, maintenance and evaluation alongside development costs.
Agree on how data will be handled
Before sharing business data with an AI service, define the permitted data flow and the requirements for your project.
- Which information may be processed and by whom.
- Model provider, hosting and retention settings.
- Access permissions and logging requirements.
- Whether sensitive fields need removal or masking.
- What must stay within your existing infrastructure.
MORE THAN A MODEL CONNECTION
Connect AI to a complete software solution
A useful AI feature also needs reliable APIs, data handling, a clear interface and integration with the systems your team uses.
Combine AI work with frontend, backend, testing and cloud infrastructure as your project requires.
Explore our software development services →Ways to start
- Explore an ideaDiscuss a use case and identify what needs to be tested.
- Build a focused prototypeValidate the approach before committing to a wider rollout.
- Extend an existing productScope an AI feature or integration around your current application.
COMMON QUESTIONS
Before you start
Do we need to know exactly what to build?
No. Start with the problem, the users and the outcome you want. Discovery can help turn that into a focused scope and a plan for testing feasibility.
Can AI work with our internal documents?
Yes, subject to access and data-handling requirements. A document search solution can retrieve relevant passages and use them to support an answer. It still needs testing, permission controls and a way to handle missing or conflicting information.
Do we need to train our own model?
Not necessarily. Depending on the task, an existing model with appropriate instructions, retrieval and integrations may be sufficient. Custom training should be considered only when there is a clear reason and suitable data.
Can you add AI to an existing application?
That can be a suitable approach. The first step is to review your application, available APIs, data access and security requirements, then define an integration that fits the existing workflow.
Can an AI agent take actions in our systems?
It can be designed to use specific tools and APIs. Permissions, action limits and approval steps should be defined in advance, especially for changes that affect customers, money or important business records.
How much does an AI project cost?
The estimate depends on scope, integrations, data preparation, quality requirements and hosting. Model usage and ongoing support also affect running costs. Share your use case so we can discuss an appropriate starting scope.
What should we prepare for the first conversation?
A short description of the problem, examples of the current workflow, the systems involved and any data restrictions are enough to start. Please avoid sending credentials or confidential source data through the initial contact form.
LET’S TALK
Have a use case in mind?
Tell us what you want to improve. We’ll discuss the requirements and a practical way to get started.