Who it is for
Companies that manage large document sets, tender documentation, contracts, technical manuals or internal knowledge that is difficult to search reliably.
Services
RAG & Document Intelligence
PentaFrame builds RAG systems and document intelligence platforms that let teams search, cite and work with PDFs, Excel files, contracts, tenders, manuals and internal knowledge bases.
What we build
- RAG pipelines for company documents
- AI document search interfaces
- Source-cited answers
- Document ingestion and parsing workflows
- Permission-aware knowledge bases
- Tender and contract intelligence tools
Typical use cases
- Tender and procurement documentation
- Contract and commercial document review
- Technical manuals and procedures
- Internal knowledge bases
- PDF, Word and Excel search
- Commercial documentation and product data
Our approach
- Analyze document types, access rules and user questions.
- Build ingestion, indexing and retrieval pipelines.
- Design citations and source traceability into the answer flow.
- Add permissions and operational controls before rollout.
Deliverables
- Document ingestion workflow
- Search and question-answering interface
- Vector/database architecture
- Source citation and audit trail
- Access control and deployment documentation
RAG and document intelligence FAQ
What is a RAG system?
A RAG system combines retrieval from your documents with AI generation, so answers are grounded in selected source material instead of only model memory.
Can we search internal documents with AI?
Yes. We can build private search over internal PDFs, Word files, Excel files, manuals, contracts and knowledge bases.
Can the system cite the source documents?
Yes. We design retrieval flows that show source references so users can verify where an answer came from.
Can it work with PDFs, Excel files and Word documents?
Yes. The exact parsing strategy depends on document quality, layout and volume, but those formats are common inputs.
How do you manage permissions and sensitive data?
We map user roles, document visibility and storage rules so retrieval only exposes information users are allowed to access.
Related services
Relevant case studies
Need AI search over company documents?
Send us the document types and user questions you want to support. We can define a secure RAG architecture.
Book a consultation