8nap AI Search – Documents Conversation

• Digitizes E2E lifecycle of documents classification, storage, and info. retrieval
• Has Multilingual language models, Augmented OCR, ICR, Digital Low Code
• Customizes search capabilities with AI and LLMs for conversational experience
• Has configured search service with intuitive user experiences and traceability
• Is GDPR compliant with required preventive and proactive controls in place
• Scales to manage large volume and has continuous learning ability

**Features:**

• **ML-Based Document Classification**

Automatically classifies documents using structure, metadata, and content, streamlining retrieval and context understanding.

• **Context-Aware Knowledge Enrichment**

Transforms static documents into dynamic, navigable knowledge units for faster discovery and reuse.

• **Smart UI Interaction & Navigation**

Supports deep document linking, source tracking, and citation management, enhancing transparency and traceability.

• **Multilingual Search with RBAC**

Provides secure, role-based access to multilingual document search, making it scalable across global teams.

**Key Implementation Details:**

• Document Process – Include details related to OCR, classification, parsing, extraction, and translation.
• Document Enrichment – Mention any enrichment using ML/AI services like Amazon SageMaker.
• Knowledge Store – Include where documents, vectors, and metadata are stored (e.g., Amazon S3, OpenSearch, RDS).
• LLM – Details of the use of Large Language Models (e.g., Amazon Bedrock).
• GUI and Authentication – Describe frontend, hosting, exposure, load balancers, authentication/authorization methods like Cognito.
• Monitoring & Logging – Operational monitoring and logging leverage AWS CloudTrail, Amazon CloudWatch, and the ELK stack.