Data Context Hub interface - Laptop screen

Rethinking
Industrial Intelligence

Industrial AI

Engineering AI

Backend

.NET

Quality Assurance

Frontend

Project Management

They came to us with a vision: to build a smarter way for AI agents to contextualize and act on industrial data. What started as a small integration turned into a complete rebuild — and a long-term product partnership.

10x Faster Reports

From weeks to just one day—with agent-powered automation.

Build for all Environments - Cloud/On-Premise/Hybrid

Full flexibility with enterprise security in mind.

Enterprise-ready Rollout

Pilots deployed at top-tier German industrial firms.

Agent Orchestration at Scale

Vector + graph DBs + orchestration = ready for complex environments.

UI
Highlights

M4AI Crash Analysis model list with target entities such as crash_tests, simulations, measurements, and calculations.

M4AI data-source configuration dialog mapping customers_configuration to the results entity with property and join rules.

M4AI canvas with helper, assistant, and collaborator agents linked to crash_tests and specs data sources.

M4AI Crash Analysis panel with system actions, agent counts, alias, and v2.0 published, v3.0 draft, v1.0 archived versions.

M4AI Explore view showing color-coded clusters for HR project reviews, airbag parts, performance, and employees.

M4AI Crash Analysis model view with target entities list and a crash_tests node connected to a Northwind worker.

M4AI Crash Analysis run showing an agent validating the "seatbelt" property with a thinking panel of execution steps.

M4AI Crash Analysis mobile interface showing an agent validating the 'seatbelt' property in a Bill of Materials node.

Graph-based memory for LLMs

Low-code agent builder

Workflow automation

Built with Phyton, Neo4j, React, Node

Data Context Hub canvas showing an isolated helper agent connected to a crash_tests data source.

Data Context Hub Crash Analysis panel with actions, 6 agents, alias c_analysis_1, and version history.

Data Context Hub model view with crash_tests entity, Northwind worker, customers_Configuration import, and results entity.

Data Context Hub config dialog mapping Northwind results properties (Title, Description, ident, data, link).

Data Context Hub zoomed canvas view of the helper agent linked to the crash_tests data source.

Data Context Hub Crash Analysis system view with actions, agent counts, alias, and published/draft/archived versions.

Data Context Hub canvas showing helper, assistant, and collaborator agents connected to crash_tests and specs.

Data Context Hub explore view with colored node clusters and a side panel of function modules.

Contextual data ingestion

Unified industrial knowledge graph extraction

Data layer management UI

Built with .NET, Node, React

Core
Features

C64.AI is rethinking industrial intelligence. With Data Context Hub and Memory for your AI®, they’re enabling faster, more accurate, and scalable decision-making across some of the world’s most complex industries.

Industrial Agent Builder

Visual environment for constructing AI agents with graph memory.

C64 - Flowchart showing a helper agent that analyzes incoming crash reports and connects to an assistant agent that triages reports and escalates critical issues.

Unified Knowledge Graphs

Aggregate and layer data across sources for contextual insights.

Context64 diagram: crash_tests entity connected through department, group, and findings relationships to a Northwind worker.

Decision Automation

Let agents recommend and take action, faster than ever before.

Enterprise-Grade Infrastructure

Running on Azure, with complex DBs and secure deployments.

C64 - Screenshot of a chat interface where user asks for simulations related to safety belt, AI explains searching 'seatbelt' in data nodes, and user confirms filtering by 'seatbelt'.

Looking
Back

What started as an integration evolved into a full rebuild. Povio became a key strategic and technical partner. We are helping shape product direction, design a modern interface, and build a scalable system across two major platforms: