Graity Core — Knowledge Infrastructure

Knowledge Infrastructure Platform

Graity

Core — Unified Intelligence Engine

KNOWLEDGE INFRASTRUCTURE FRAMEWORK

The gravitational core of your organisation.
Every piece of knowledge, pulled to one intelligent centre.

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The Problem

Knowledge is Scattered, Dead & Unusable

The Root Cause

Corporate Knowledge Entropy

Documents live in silos. Expertise dies in audio files. Institutional memory decays with every departure. Your AI has no real data to think with.

Dead DataFiles stored but never updated, queried or used.

Source DependencyKnowledge vanishes when access to a tool is lost.

Manual EverythingSomeone has to update, clean, and re-index manually.

AI in a VacuumYour AI models run on internet data, not company reality.

Structural Solution

Introducing Graity Core

The Automated Knowledge Factory

Graity Core

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Lifecycle Management

Auto-collects, updates, deduplicates and re-indexes — zero manual effort.

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AI-Layer Processing

Every document gets OCR, AI parsing, semantic summaries and vector prep.

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Universal Input

Files, audio, video, live docs, APIs, meetings — 99% of corporate data formats.

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Enterprise-Safe

Granular access by role, team, client. Your data never leaves your perimeter.

Input Layer

Every Data Type. One Intelligent Flow.

Data Coverage

99%

Corporate Formats

Input Type	Processing Logic	Business Value
📄PDF / Office Docs	OCR extraction + secure copy	Reliable knowledge archive, source-independent
🔴Google Workspace	Live sync + auto re-index triggers	Always up-to-date, even if original access is lost
🎙️Audio / Video	Whisper transcription → text pipeline	Expertise from calls, workshops and recordings
🔗External Docs / URLs	Full catalogue parsing from one link	Scale knowledge base with a single action
▶️YouTube	Subtitles only — no heavy storage	Extract meaning, not media weight
💬Meetings / Slack / CRM	Via connectors → transcript → index	Institutional memory from every conversation

Processing Engine

From Raw Data to Strategic Intelligence

Processing Layers

Multi-stage pipeline

OCR & Text Extraction

Every format → single unified text standard. CloudConvert for edge cases.

Any format → text

AI Parsing & Normalisation

AI reads structure, speech (Whisper) and visual context. Data becomes machine-readable.

Data → meaning

Semantic Enrichment

Summary by text content + summary by visual context (slides, diagrams, charts). System understands context, not just words.

Text → context

Quality Control Loop

Duplicate detection, trigger-based updates, source copy preservation. Self-cleaning knowledge base.

Clean → current

RAG Vectorisation

Chunking → vector embedding (OpenAI / Gemini) → Qdrant storage. Semantic search, not keyword matching.

AI-ready