Back to Under the Hood
Document Intelligence Engine

From Document to Knowledge

Watch how Pelles transforms raw documents into a semantically-rich knowledge graph. Every page undergoes multi-modal analysis, contextual understanding, and neural encoding— orchestrated in parallel at scale.

Processing Accuracy:99.7%
Avg. Confidence:94.2%
Knowledge Density:High

The Intelligence Pipeline

Documents flow through six orchestrated stages, each applying specialized AI models to extract, understand, and encode information into queryable knowledge.

Document Ingestion

The intelligence pipeline begins when a document enters the system. Pelles accepts 100+ formats— from standard PDFs to specialized construction files like Primavera P6 schedules and MS Project plans.

.pdf.docx.xlsx.xer.mpp.dwg.csv

Click to simulate document ingestion

The Document Processor

Each page traverses an orchestration graph—a directed state machine that ensures deterministic flow, automatic recovery, and observable transformations at each node.

Context Initialization

Hydrate the processing context from cloud storage, initialize lazy-loaded properties, and prepare the analysis pipeline.

// Output

ProcessingContext { pageRef, documentMeta, analysisConfig }

Neural Architecture

Multiple specialized models operate in concert, each optimized for distinct cognitive tasks. Intelligent fallback chains ensure resilience—if one model underperforms, another compensates.

Primary LLM

Language Understanding

  • Contextual Classification
  • Semantic Summarization
  • Entity Extraction

Vision Model

Visual Intelligence

  • Table Detection
  • Drawing Analysis
  • Layout Understanding

Neural Embedding

Semantic Encoding

  • High-Dimensional Fingerprints
  • Similarity Mapping
  • Knowledge Linking

Resilience Chain

Primary Model
Secondary Model
Tertiary Model
Success

Automatic failover with quality-aware model selection

100+

File formats

99.7%

Accuracy rate

4x

Auto-recovery

3072

Vector dimensions