KnowledgeX

Turn Enterprise KnowledgeInto Intelligent Answers

Semantic RAG, knowledge graphs, and domain-aware AI — connected to your data sources, powered by your expertise, governed by your rules.

11-Phase Pipeline|6+ LLM Providers|<2s Response
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The Challenge

The Enterprise Knowledge Crisis

Scattered Knowledge

Critical information is buried across documents, spreadsheets, and databases — impossible to search, difficult to trust, and slow to surface when it matters.

Slow Time-to-Insight

Teams spend hours manually gathering data, cross-referencing sources, and computing metrics that should be available in seconds.

Siloed Systems

Documents live in one tool, databases in another, and domain expertise in people's heads. No single layer connects them into actionable intelligence.

Traditional search, static FAQs, and manual data extraction cannot scale. Enterprises need a knowledge layer that understands context, computes answers, and cites sources.

The Platform

From Raw Data to Computed Insights — In Seconds

An 11-phase semantic pipeline that ingests, understands, and computes answers from your enterprise knowledge.

01

Multi-Source Ingestion

PDFs, DOCX, CSV, XLSX, databases. Semantic chunking with intelligent table extraction.

02

Semantic Processing

Domain detection, intent classification, entity extraction, formula identification, graph expansion.

03

Live Data Connectors

PostgreSQL, Databricks. Natural language to SQL. Read-only, encrypted, production-safe.

04

Multi-LLM Orchestration

OpenAI, Anthropic, Ollama. SSE streaming with tool orchestration. Right model for right task.

05

Cited, Computed Answers

Source attribution, confidence scoring, formula computation, semantic analysis. Real-time streaming.

Get Started in Minutes

From scattered data to computed insights

01

Plug In Your Knowledge

Upload documents, connect databases, or link APIs. KnowledgeX ingests from any source — PDFs, MySQL, PostgreSQL, Databricks, and more.

AI
02

AI Learns Your Domain

Documents are chunked, embedded, and enriched. Entities and relationships are auto-extracted. Domain formulas are detected. Your knowledge becomes structured and searchable.

42.3%93% confidence
03

Ask Anything, Get Computed Answers

Ask questions in natural language. Get computed answers with source attribution, confidence scoring, and semantic analysis — all in real-time.

Why KnowledgeX

What Sets KnowledgeX Apart

Enterprise knowledge platforms are not created equal.

CapabilityKnowledgeXM365 CopilotDIY RAG Stack
Query documents with source citations
Query databases in natural language
Compute metrics via formula engine
Domain-aware semantic layer
Knowledge graph relationships
Choose your own LLM
Deploy on your infrastructure
Production-ready in days, not months
Full support
Partial
Not available

Beyond M365 Search

Copilot searches your SharePoint. KnowledgeX queries your databases, computes metrics, and understands your domain terminology — not just your file names.

Production-Ready, Not a Science Project

Skip months of LangChain engineering. Get semantic RAG, text-to-SQL, formula computation, and full observability out of the box.

Semantic Layer Native

Built-in business glossary, formula libraries, and knowledge graphs. AI speaks your language, not just your keywords.

Quantified Impact

Measurable Impact on Enterprise Knowledge Operations

Seconds
Not Hours, to Insight

Replace manual research with AI-computed answers — sourced, cited, and confidence-scored in real time.

One
Interface for All Knowledge

Documents, databases, and domain semantics unified in a single conversational layer. No more switching between tools.

Zero
Data Exposure Risk

Full on-premise deployment with encrypted connectors. Your data never leaves your infrastructure.

A Day With KnowledgeX
8:30 AMAnalyst
What was our inventory turnover ratio last quarter?
Searched 10-K filings → computed COGS / avg. inventory via formula engine → returned 4.2x with source citation to p.47
9:15 AMManager
Which suppliers had delivery delays in Q3?
Queried PostgreSQL supply chain DB via text-to-SQL → cross-referenced with uploaded vendor performance reports
2:00 PMExecutive
How does our gross margin compare to industry benchmarks?
Combined uploaded industry reports with database financials → computed margin delta with 91% confidence scoring

Under the Hood

The Query Processing Pipeline

From question to computed, cited answer — orchestrated through five processing stages.

User Querytext · attachments
query text
KnowledgeX Pipeline
PARSE

Input Processing

MarkItDown · Vision API
parsed content
ENRICH

Semantic Enrichment

SemanticX · FormulaOrchestrator
enriched query
RETRIEVE

RAG Retrieval

pgvector · HNSW · Table-Aware
context chunks
REASON

LLM Processing

OpenAI · Anthropic · Ollama
tool calls
Tool Registry
Knowledge
Search KB
Query DB
List Tables
Semantic
Semantic Query
Explain Relations
Graph
Search Graph
Traverse
Entity Context
Find Path
MCP
Dynamic Tools
LLM response
DELIVER

Streamed Response

SSE · Langfuse · Persistence
SSE stream
StreamedSSE · Citations
Infrastructure Layer
PostgreSQL + pgvectorVector storage & HNSW
MinIODocument storage
RedisQuery caching
LangfuseLLM observability
Neo4jKnowledge graphs
TemporalWorkflow orchestration
Document Processing Pipeline
Upload
MinIO
Parse
MarkItDown · 17+ formats
Table Extract
LandingAI
Semantic Chunk
Chonkie
Embed
SentenceTransformers · OpenAI
Store
pgvector · HNSW

Enterprise Ready

Built for Production. Governed by Design.

On-Premise Deployment

Deploy fully air-gapped. No data leaves your infrastructure. Complete control over your knowledge layer.

Encrypted Connectors

Read-only database access with TLS encryption and Fernet credential vaulting. Production-safe by design.

Full Auditability

Every query, source, and computation is traced end-to-end via OpenTelemetry and Langfuse.

Your Models, Your Rules

Bring your own LLMs via Ollama. Run Llama, Mistral, or any model locally. Zero vendor lock-in.

Temporal Orchestration

Production-grade workflow engine for reliable, fault-tolerant AI pipelines with automatic retries.

Source Attribution

Every answer cites its sources with page numbers, table references, and confidence scoring.

Your knowledge, structured.Your questions, answered.

Upload documents, connect a database, and start asking.

On-Premise Ready
Zero Data Exposure
Multi-LLM Support
Source Attribution