Chosen data location
Documents, indexes and models hosted in the environment agreed with your company.
KEYA AI / INTELLIGENCE, ON YOUR TERMS
AI that understands your business through your own documents. A private knowledge base, a useful assistant and infrastructure you control.
PRIVATE ARCHITECTURE · CONCEPT VISUALK / AI — 001 RAG
01
Connected knowledge.
Bring policies, guides and business documents into a searchable knowledge base.
02
Contextual answers.
An assistant that searches your resources before composing its response.
03
A defined boundary.
Choose where your data, indexes and models are hosted.
01 / YOUR KNOWLEDGE IN ACTION
Less searching.
More useful answers.
A new colleague, a technical question, a procedure to find. Your assistant makes company knowledge accessible, with its sources.
Interactive illustration using fictional documents and prepared answers. No company documents are transmitted.
Keya Assistant
DEMO · PRIVATE KNOWLEDGEHR TEAMAD
How do I request leave?
Documents
Indexing
Retrieval
Answer
KEYA AI
The HR guide describes three steps:
- Submit the request in the OA system.
- Specify the dates and planned coverage.
- Wait for your manager’s approval before confirming your absence.
HR_Guide.pdf / p. 12 · § 3.2
Leave requests must be submitted in the OA system with the requested dates and planned coverage. The employee’s manager must approve the absence.
RAG · Cited answers
02 / THE RAG ENGINE
Your documents become context.
RAG combines document retrieval with answer generation. The model uses relevant passages from your knowledge base without needing full retraining for every update.
PDF · DOCX · BUSINESS SOURCES
Import PDFs, office files and business content. Connectors, OCR and synchronization are scoped to your sources.
01/ 0403 / PRIVATE BY DESIGN
Your intelligence stays
within your boundary.
Privacy starts with architecture. Together we define hosting, permissions, models and allowed data flows before deployment.
YOUR COMPANY BOUNDARY
Authorized users
Inside your premises.
Installed on your servers or dedicated on-site infrastructure, sized for the models, documents and users.
Internal networkCompany serversLocal models
01
Role-based access
Document permissions are applied during retrieval, before answer generation.
Audit & retention
Access logs, retention periods and backups defined by your internal policy.
Data protection
Encryption, authentication and network rules configured for your infrastructure and agreed scope.
Operating without external AI services requires local inference, embeddings and any OCR tools as well. This scope is confirmed during discovery.
04 / FROM IDEA TO DAILY USE
A deployment that starts with you.
Define
Priority use cases, document quality, users and confidentiality requirements.
Test
A pilot on selected documents, evaluated with your questions and business criteria.
Deploy
Installation, training, answer evaluation and maintenance within an agreed scope.
Before you get started.
Will our documents train a public model?
RAG retrieves passages to answer questions without requiring public model training. A local deployment uses local models. Any external services and their data-use terms must be explicitly agreed with you.
Can the assistant make mistakes?
Yes. Citations, business-specific evaluations and insufficient-context responses help reduce errors. Important decisions still need human review.
Can we start with a few documents?
Yes. Start with a focused set of documents and one clear use case. A pilot checks source quality and answer usefulness before expansion.
What hardware and budget are needed?
This depends on model choice, document volume, concurrent users and integrations. Sizing and pricing follow discovery rather than a one-size-fits-all fee.
Your company has the knowledge.
Let’s give it a voice.
Tell us about your documents, your team and what you want your AI to help achieve.
Let’s talk AIDiscovery · Deployment · Support