Product information
Product and service information assistants.
AI Knowledge Search for
Fintech
Find answers in your approved product and operational documents.
Zimozi builds AI knowledge search for fintech teams. Using retrieval augmented generation, or RAG, the system retrieves relevant material before preparing an answer with source references.
Procedure search
Operations procedure search.
Support knowledge
Support knowledge assistants.
WHAT WE BUILD
Knowledge tools we build.
Product information
Product and service information assistants.
Procedure search
Operations procedure search.
Support knowledge
Support knowledge assistants.
Technical documentation
Technical documentation search.
Policy retrieval
Policy and internal guidance retrieval.
A PRACTICAL FIRST STEP
Make internal information easier to use.
The starting point
Product guidance, procedures and technical documents often sit in separate systems. An assistant can help staff locate relevant sections without searching every folder manually.
How we scope it
We review ownership, versions and update frequency so the system can distinguish current material from outdated documents.
Product information
Product and service information assistants.
Apply permissions to the search
The retrieval layer must respect the user's access, not just the interface. Sensitive documents require a suitable deployment, identity controls and data handling arrangements.
Check retrieval and answers separately
Testing examines whether the right information is retrieved and whether the generated answer is supported by it. Source references make review easier but do not guarantee correctness. Refresh procedures keep the knowledge current.
From idea to everyday use.
Discover
Understand the users, current process and intended result.
Assess
Review the data, systems, access and review needs.
Develop
Build a focused pilot around the agreed use case.
Deploy
Connect the solution to the workflow and test exceptions.
Evolve
Monitor quality, usage and costs, then improve.
BUILT FOR REAL WORKFLOWS
Apply permissions to the search.
The retrieval layer must respect the user's access, not just the interface. Sensitive documents require a suitable deployment, identity controls and data handling arrangements.
IN PRACTICE
A practical use case.
Check retrieval and answers separately
The situation
A support employee asks which documents are needed for a particular account type.
The workflow
The assistant retrieves the current approved guidance, summarises the requirements and links to the source. Conflicting or missing information is referred to the document owner.
In context
This example illustrates a potential workflow, not a claimed customer result.
Project scope
Testing examines whether the right information is retrieved and whether the generated answer is supported by it.
Delivery details
Source references make review easier but do not guarantee correctness. Refresh procedures keep the knowledge current.
Frequently asked questions
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No. RAG retrieves information at query time. Fine-tuning changes model behaviour through additional training.
Yes, with appropriate source access, permissions and deployment arrangements for those documents.
The ingestion and update process refreshes the relevant material. The agreed support scope defines ownership and timing.
YOUR NEXT STEP
Turn your document collection into a useful knowledge tool
Tell us where your information lives and who needs to access it.
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Tell us about
your project.
Share a short brief, or book a time to talk with our team.