Technology with purpose. Built around your business.
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Sciematics Insights
Generative AI & LLM Solutions

Make your knowledge easier to use.

Build assistants, copilots and language model applications that help people find information, draft work and use approved business knowledge.

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The business case

Start with a useful outcome.

A language model application needs more than a chat window. It needs reliable source material, permission controls and a way to test whether its answers are supported. We help define the use case, connect the right information and build a review process around the situations where the system may be wrong.

Discuss your requirement
Capabilities

What we can help you build.

The scope is shaped around your systems, your information and the work you need to do.

01

LLM Applications

Use language models for specific tasks such as summarisation, document assistance and structured information extraction.

02

Enterprise Chatbots

Give colleagues or customers a conversational way to reach approved information with clear escalation routes.

03

Retrieval-Augmented Generation, RAG

Retrieve relevant source material before generating a response, with attention to document quality, citations and access.

04

Knowledge Assistants

Help people search policies, manuals and other maintained reference material without losing the source context.

05

AI Copilots

Place drafting, search or analysis assistance inside a workflow while keeping the user responsible for review.

06

Custom AI Assistants

Define a focused assistant around your terminology, tools and working practices rather than a generic chat experience.

Practical applications

Where this can help.

Examples of suitable use cases, to help you think through your own requirements and decide whether there is a worthwhile starting point.

Internal knowledge search

Find guidance across approved documents and point the reader back to the source.

Service support

Prepare a response using current product information and route exceptions to a person.

Document assistance

Draft summaries or extract fields for review before the information is used elsewhere.

A clear working agreement

Know what you are
working towards.

Deliverables are agreed before work begins. A typical engagement may include the following, adjusted to the scope and complexity of your project:

  • A knowledge and permissions readiness review
  • An assistant or application with defined task boundaries
  • A test set covering supported and missing answers
  • Source update, evaluation and handover guidance
Before we begin

A useful first conversation.

Choose a narrow audience and task, then identify the documents that should inform an answer. Include their owners, versions and access restrictions. Better source material is often the first useful improvement.

Talk through your idea
Common questions about getting started

What to expect before and during a project.

Retrieval-augmented generation retrieves relevant information from a source collection and provides it to a language model when it answers a question. It can improve grounding, but still needs evaluation and appropriate access controls.

No. Retrieval can miss relevant information and a model can still generate an unsupported answer. We test source retrieval and response quality separately, including questions the assistant should decline.

Yes, when the hosting, provider terms, data handling and permissions meet the agreed requirements. Private source material should not become visible to people who are not authorised to read it.

Connected expertise

Bring the pieces together.

Cybersecurity

Understand where your applications, networks and working practices are exposed, then turn the findings into a clear plan of action.

Explore service
Start a conversation

What would you like to build?

Tell us what is slowing you down, or what you want to do next. A short description of your business question is all it takes to begin.

Discuss your project