AI and LLM models
We select, tune and deploy AI models for specific functions within systems. Solutions can run locally, ensuring control over data and compliance with privacy requirements.
AI deployed for a specific business function
Each deployment is preceded by an analysis of the task and an assessment of whether using a model is justified. The model is matched to the function, and output quality is measured before the solution goes into production.
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Assistants and semantic search
Answering questions from an internal knowledge base and searching across documents.
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RAG and fine tuning
Generating answers based on organisational data and tuning the model to the context.
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Content processing
Speech transcription, content analysis and classification, and automation of text tasks.
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Local deployment
Running models within the organisation, without transferring data externally.
When is deploying an AI model justified?
Deploying an AI model is justified when it addresses a specific business function, for example searching an internal knowledge base, handling enquiries or processing documents. The model is matched to the task, and output quality is measured before the solution goes into production.
Models can run locally within the organisation, without transferring data externally, ensuring GDPR compliance. The solution is integrated with the systems in use via API and covered by quality monitoring.
Project delivery process
Task analysis
The objective is defined and the justification for using an AI model is assessed.
Data and model selection
Data is prepared and a model suited to the function is selected.
Tuning and quality control
The model is tuned to the context, and output quality is measured before deployment.
Integration and maintenance
The solution is integrated with systems and covered by quality monitoring.
Project scope
The scope of work is defined contractually before the project begins.
Available engagement models
Regardless of the model, billing remains transparent and full ownership of the code is transferred to the client.
Fixed price
A fixed scope, agreed budget and delivery date. Recommended when requirements are clearly defined.
- Fixed price and timeline
- Scope defined in advance
- Limited budget risk
Time & Material
Billing based on time spent, with a flexible scope. Recommended for products under active development.
- Flexible scope of work
- Fast project start
- Priorities set on an ongoing basis
Frequently asked questions
For any questions not covered here, please get in touch. We respond within one business day.
It is not necessary. Models can run locally within the organisation, ensuring control over data and GDPR compliance.
Output quality is measured on prepared data before the solution goes into production, against defined criteria.
RAG generates answers based on retrieved organisational data. The model responds using an internal knowledge base rather than general knowledge alone.
Yes. The solution is integrated with the applications and workflows in use via API.
Considering an AI or LLM deployment?
Please get in touch. We respond within one business day.
Contact form
Please provide a brief description of the project. We will respond with a proposed scope and next steps.