KonnectxD

// konnect-core v3.0

Beneath Every App Is Konnect Core

The data pipeline, knowledge graph, and AI layer that power 52+ apps across the entire asset lifecycle. Not just storage — computable reality.

Explore the Architecture ↓

// pillar.02 — core-data-fusion

The Medallion Architecture

From chaos to graph. From graph to insight. Raw data flows through Bronze → Silver → Gold tiers into curated, query-optimized intelligence.

BronzeBronze — IngestionETL / ELT

Raw data capture from CAD, BIM, PIMS, IoT, and manual input. Schema-on-read. No assumptions — just ingest everything.

SilverSilver — TransformationDATA LAKE

Graph of relationships: Tags ↔ Systems ↔ Documents. Equipment hierarchies, functional topology, quality validation.

GoldGold — Curated IntelligenceWAREHOUSE

Curated, trusted, query-optimized. Powers ML Feature Store, analytics, reporting, and all downstream apps.

// example: P&ID pipeline

Bronze

DWG / DEXPI file ingested
→ Raw P&ID capture, schema-on-read

Silver

Tags ↔ Systems ↔ Documents
→ Equipment hierarchies, topology

Gold

Interactive SVG Viewer
→ Tag Browser, System Navigator
→ Testpack Builder, Punch List

// pillar.04 — knowledge-graph

Beyond SQL. Context and Topology.

Data lives as triplets: Subject → Predicate → Object. Not rows — relationships the system understands natively.

Pump
Pump-101
——→feeds
Tank
Tank-B
——→through
Line
Line-101-LPG

"Pump-101 feeds Tank-B through Line Number 101-LPG-0079" — not a row, it's a relationship.

// pillar.05 — computable-moc

The First Truly Computable Project Execution System

Software engineering principles applied to physical engineering. Baseline. Branch. Merge. Every change tracked, auditable, reversible.

Baseline

The immutable "Master Branch" — Contractual Truth. The single source of approved reality.

Branch

Teams work in isolated sandboxes. Test changes without risk. Multiple branches can run in parallel.

Merge Request

Formal validation before committing to baseline. Reviews, approvals, audit trail — just like a PR.

// pillar.06 — ai-embedding

Predictive, Not Reactive

Vector embeddings for every node in the graph. Continuous AI scoring powers proactive decisions — not retrospective reports.

Ingest

Ingest

Documents, models, sensor data

Graph

Graph

Knowledge Graph triplets

ML

Machine Learn

Vector embeddings per node

Calculate

Calculate

Predictive scoring output

Risk

Risk Index

Proactive hazard detection. Identify high-risk tags, systems, and work packages before they escalate.

Cost

Cost Forecast

Budget variance predictions based on historical patterns and current progress trajectories.

Schedule

Schedule Health

Delay probability scoring. Predict which activities will slip before the critical path is affected.

// pillar.03 — project-genome

Clone Success. 80% Complete from Day One.

ROADMAP

Capture your Corporate DNA — Class Libraries, Tagging Hierarchies, Standards. New assets inherit the genome of past successes.

Clone Successful Projects

80% completion from day one. Start with proven structures, not blank sheets.

Corporate DNA

Standards, Class Libraries, Tagging Hierarchies. Encoded as reusable templates.

Portfolio Standardization

100% compliance across assets. Consistent data models, naming conventions, procedures.

Genome