Technical Specifications

For technical decision-makers, architects, and engineering teams.

This page provides detailed technical information about TeraContext.AI’s implementation architecture, infrastructure requirements, and integration capabilities. For business-focused content, see Solutions or Use Cases.

Architecture Overview

Core Technology Stack

Document Processing Pipeline:

LLM Integration:

Frontend Options:

Implementation Approaches

RAG (Retrieval-Augmented Generation)

Technical Components:

1. Document Ingestion

Input → Parsing → Chunking → Embedding → Indexing → Vector Store

Parsing Support:

Chunking Strategies:

Embedding Models:

Vector Database Configuration:

2. Retrieval Process

Query → Embedding → Vector Search → Reranking → Context Assembly → LLM

Retrieval Strategies:

Context Assembly:

Performance Benchmarks:

GraphRAG

Technical Components:

1. Knowledge Graph Construction

Documents → Entity Extraction → Relationship Mapping → Graph Building → Graph Store

Entity Extraction:

Relationship Extraction:

Graph Database:

2. Graph-Based Retrieval

Query → Entity Detection → Graph Traversal → Subgraph Extraction → Context Assembly → LLM

Graph Traversal Strategies:

Performance Benchmarks:

Multi-Layer Summarization (RAPTOR)

Technical Components:

1. Hierarchical Construction

Documents → Chunk Embedding → Clustering → Summarization → Recursive Clustering → Layer N

Clustering Algorithm:

Summarization:

Layer Construction:

2. Query-Aware Retrieval

Query → Abstraction Level Detection → Layer Selection → Retrieval → LLM

Layer Selection:

Performance Benchmarks:

Infrastructure Requirements

Cloud Deployment (API-Based)

Recommended Configuration:

Low Volume (<10K queries/month):

Medium Volume (10K-100K queries/month):

High Volume (100K+ queries/month):

On-Premise Deployment

Minimum Configuration (Pilot/Small Deployment):

Recommended Configuration (Production Deployment):

Enterprise Configuration (Large-Scale):

Software Stack:

Hybrid Deployment

Architecture:

Benefits:

Complexity: Moderate (requires routing logic and data classification)

Integration Capabilities

Data Sources

Document Management Systems:

File Servers & Storage:

Databases:

Email & Collaboration:

Integration Methods:

Authentication & Access Control

Authentication Methods:

Authorization:

Security Features:

API Specifications

RESTful API Endpoints:

Document Management:

POST   /api/v1/documents              # Upload documents
GET    /api/v1/documents/{id}         # Retrieve document metadata
DELETE /api/v1/documents/{id}         # Remove document
GET    /api/v1/documents              # List documents (paginated)
POST   /api/v1/documents/bulk-upload  # Batch upload

Query & Search:

POST   /api/v1/query                  # Submit natural language query
GET    /api/v1/query/{id}             # Retrieve query results
POST   /api/v1/search                 # Advanced search with filters

Administration:

GET    /api/v1/stats                  # System statistics
GET    /api/v1/health                 # Health check
POST   /api/v1/reindex                # Trigger re-indexing
GET    /api/v1/users                  # User management

Response Format:

{
  "query_id": "uuid",
  "answer": "Generated response text",
  "citations": [
    {
      "document_id": "doc-123",
      "document_name": "Specifications Vol 3.pdf",
      "page": 142,
      "section": "03 30 00 Cast-in-Place Concrete",
      "excerpt": "Concrete strength shall be 4,000 psi..."
    }
  ],
  "confidence": 0.92,
  "latency_ms": 1250
}

SDKs Available:

Rate Limiting:

Performance & Scalability

Benchmark Results

Document Ingestion:

Query Performance:

Scaling Characteristics:

Accuracy Metrics (Domain-Optimized):

Compliance & Security

Certifications & Standards

Security Frameworks:

Data Privacy:

Government/Defense:

Data Handling

Data Retention:

Data Deletion:

No Training on Customer Data:

Support & Maintenance

Deployment Support

Included in Implementation:

Timeline:

Ongoing Support Tiers

Standard Support (Included for 90 days post-launch):

Premium Support (Optional):

Managed Services (Optional):

Getting Started

Technical Evaluation Process

Phase 1: Discovery (Week 1-2)

Phase 2: Proof of Concept (Week 3-6)

Phase 3: Production Deployment (Week 7-12)

Technical Requirements for Evaluation

Provide for Optimal Assessment:

Contact Technical Sales

For detailed technical discussions, architecture consultations, or custom requirements:

Contact Us - Mention “Technical Evaluation” for priority routing to our solutions architects.

What to Expect:

Related Pages: