Operations and maintenance
Find a procedure or part reference across manuals. Keep version dates and page references visible so staff can confirm the answer against the current source.
PakVision DocFinder™
Private AI Search Across Your Company Documents
Source-grounded answers with exact citations. Turn contracts, manuals, financial records, and regulatory filings into a private, permission-aware question-and-answer assistant that admits when evidence is missing — deployed on-premises, hybrid, or private cloud inside Pakistan.
01
Hybrid Retrieval Engine
Searches by meaning and by exact wording at once, so it reliably catches exact clause numbers, tax codes and technical part identifiers.
02
Ranking The Best Answer
The best-matching passages are ranked a second time on your own hardware, so only genuinely relevant material reaches the answer generator.
03
Granular Access (RBAC)
Vector chunks are indexed with enterprise Active Directory / LDAP access control tags. An employee only retrieves answers from documentation their role is authorized to view.
Deployment and data controls
Engineered for Pakistani Enterprise & Hybrid Topologies
Decide where documents, indexes, model processing, logs and backups may reside. Review the chosen architecture against your organisation’s policies before connecting confidential records.
PakVision DocFinder™ gives you complete deployment flexibility: run it entirely on your own hardware, inside a secure private cloud, or across both, with every connection encrypted.
✓ On-Premises, Hybrid or Private Cloud
✓ Review External Service Access
✓ Agree Encryption & Access Controls
// Illustrative document retrieval
Fictional sample document
QUERY: "Who approves a purchase above the team limit?"
RETRIEVAL: Purchasing_Procedure_Example.pdf [Page 4, Section 2] — fictional demonstration document
ILLUSTRATIVE ANSWER: The example procedure requires approval from the department manager before an order is placed. [Source: Purchasing_Procedure_Example, p.4]. Confirm the current authorised procedure before acting.
PLAN YOUR PROJECT
Plan private enterprise RAG in Pakistan
PakVisionAI’s private knowledge search uses retrieval-augmented generation (RAG) to find relevant passages in company documents and produce answers with source references. The project is scoped around your document formats, employee permissions, refresh requirements and chosen on-premises, private cloud or hybrid environment.
Start with a document collection that has a clear owner and recurring questions: operating procedures, product manuals or internal policies. Fix missing or contradictory source material before judging answer quality.
Employee policy questions
Answer from approved internal policies while preserving document-level permissions. Include questions from users who should not have access in the test set.
Contract and document review
Locate clauses and supporting passages for a reviewer. Treat the answer as document assistance; authorised staff remain responsible for interpretation and decisions.
What to prepare for discovery
- Document formats, approximate page count, languages and scan quality
- Source owners, document versions and update frequency
- Employee groups and access-control requirements
- Representative questions, expected source passages and hosting constraints
What affects the cost?
Document ingestion and OCR, connector development, permission synchronisation, model hosting, search volume, storage and ongoing evaluation affect cost. Include the work needed to update or remove documents after launch.
Compare one-time and recurring costs using the enterprise AI proposal checklist →
Request a scoped Private knowledge search proposal →How to evaluate the pilot
Agree the baseline, test data and pass criteria before implementation. These are evaluation methods, not published PakVisionAI performance results.
| Measure | How to assess it |
|---|---|
| Answer grounding | Have a reviewer check whether each answer is supported by the cited passage on a held-out question set. |
| Permission boundaries | Test whether users can retrieve restricted documents through direct questions, paraphrases or follow-up prompts. |
| Missing and stale evidence | Check abstention when an answer is absent and measure the time for changed or deleted documents to stop appearing. |
Is this the right approach?
Choose keyword search when exact terms are sufficient. Choose RAG when users need a supported answer across passages. Fine-tuning changes model behaviour; it does not by itself provide current source citations or document access controls.
Planning guidance updated . About PakVisionAI · Discuss your requirements
Private knowledge search: common questions
What is enterprise RAG?
Retrieval-augmented generation combines document retrieval with a language model. The system finds relevant source passages, then uses them to form an answer. An enterprise implementation also needs permissions, source updates, evaluation and a clear response when evidence is missing.
Can private knowledge search run on our own servers in Pakistan?
On-premises, private cloud and hybrid deployments can be scoped. Agree where documents, indexes, models, logs and backups are processed and stored, including any external service connections.
Can RAG search scanned PDFs and complex multi-page documents?
The answer depends on OCR quality, fonts, layout, document structure and the retrieval model. Include representative scans, tables and complex business questions in the pilot before committing to archive-wide coverage.
Does a source citation guarantee an answer is correct?
No. A cited passage can be incomplete, outdated or misinterpreted. Evaluate citation support, document freshness and missing-evidence behaviour; keep human review for consequential decisions.
Will our company documents train a public model?
Specify model providers, training-use restrictions, retention, logging and external API access in the proposal. A private deployment can be designed around your data-control requirements, which should be verified before sensitive documents are connected.
Can we restrict which employees can see which documents in search results?
Document-level and folder-level permissions can mirror your existing access-control system, so an answer only draws on documents the requesting employee is already authorised to view. Test this explicitly with accounts that should be denied access, including indirect phrasing and follow-up questions.
How can we check that a cited AI answer respects document permissions?
Repeat representative questions using approved accounts with different roles, including requests for restricted material. Review the answer, cited passage, source link and follow-up questions. A citation is useful only when it supports the answer and the user is authorized to access that source.
Talk To An Engineer • Deployments Nationwide
Run Enterprise AI on Your Private Infrastructure.
Discuss your cameras, documents, phone system or business workflow with our team. Define a focused pilot, deployment approach, acceptance criteria and delivery schedule before implementation.
✓ Agree secure data access
✓ On-premises, hybrid or private cloud
✓ Agreed data access controls
✓ Scoped support coverage