Simplicode / Services / RAG Development & AI Document Search
RAG & document search in Jakarta
Retrieval-augmented generation (RAG) is a method where an AI model first retrieves the relevant passages from your documents and then writes an answer based only on those passages. Simplicode builds RAG search for contracts, policies, manuals and product data, with every answer linked to the page it came from.
What webuild
(04)
Document ingestion
PDF, Word, spreadsheets and scanned files split by section and indexed with their metadata.
Cited answers
Every answer shows the document, page and passage it used, so people can check it in one click.
Access control
Users only retrieve documents they are already allowed to open.
Evaluation
A test set of real questions runs before each release to catch wrong or uncited answers.
How itworks
4 steps
Scope
Map the process, the data and the success metric. Output: a scope document and a fixed price.
Build
Weekly releases to staging. Your team can try the system from week two.
Evaluate
Automatic tests for answers, cost and safety before every release.
Launch
Production, monitoring, and handover of the repository and documentation.
Commonquestions
Does RAG work with Indonesian and English documents?
Yes, RAG works with Indonesian and English documents in the same index. Questions can be asked in either language.
Where are our documents stored?
Documents stay in your own cloud account or database. Simplicode does not copy them to a shared service.
Otherservices
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02AI workflow automation
Email, spreadsheet and ERP steps your team still copies by hand, handled by a system that logs every action.
03Web & mobile apps
Dashboards, portals and field apps your team opens every day, built with Next.js and React Native.