AI Development
Turn approved business information into useful search, drafting and employee-copilot experiences. We build generative AI applications with retrieval, source visibility and permission-aware access suited to your organization.
General model knowledge is not a substitute for your company’s current documents. Retrieval-augmented generation, or RAG, finds relevant material from selected sources before producing an answer. The application must manage document updates, access permissions and how to respond when the sources do not support an answer.
Organize and process the approved files and records that the application should search.
Retrieve relevant passages and include source references where appropriate to the user journey.
Support research, summarization and drafting within a defined business workflow.
Test retrieval relevance, answer support, restricted-content handling and the cost of real usage.
Possible projects include internal policy search, product-information assistants and drafting tools that use approved reference material. The solution is designed around the documents and users in scope rather than exposing every file to every employee.
Identify document owners, permitted users, update frequency and examples of useful questions. We review document quality and access rules before building the retrieval and response workflow.
A RAG application can retrieve relevant approved information and use it to compose an answer. Data access and document quality need to be assessed first.
No. Retrieval and evaluation can improve grounding, but the application still needs checks, clear limitations and human review appropriate to its use.
We agree an update process for adding, replacing and removing source material, including how permissions and search indexes stay current.
Tell us about the workflow and outcome you want to improve so we can define a practical next step and a clear project scope.
