Product Introduction
EdgeOnto is an AI Agent SaaS platform for manufacturing, deeply integrating factory systems, capabilities, and knowledge with large language models through a four-layer architecture — MCP Hub non-invasively connects all business systems, Skill Engine encapsulates pluggable manufacturing expertise, Knowledge Engine preserves proprietary factory knowledge, and Agent Engine provides LLM-driven intelligent orchestration linking all three into executable business workflows.
EdgeOnto is not a generic AI chatbot, but an operations hub rooted in the manufacturing shop floor — driving cross-system collaboration with natural language, making knowledge searchable, capabilities reusable, and decisions traceable.
MCP Standard Protocol
Unify ERP, MES, WMS, and IoT connectivity via Model Context Protocol — no system modifications required
What You Think Is What You Get
Shop floor supervisors can query OEE, create work orders, and analyze quality in natural language — no system training required
Skills — Plug and Play
OEE analysis, smart scheduling, quality traceability and other manufacturing capabilities delivered as standardized Skills — enable on demand
Start Light, Scale Deep
Start with lightweight scenarios like knowledge Q&A and progressively expand to autonomous execution — validate AI value with low risk
Three Core Pillars
EdgeOnto decomposes the AI Agent infrastructure into three independent yet collaborative engines — corresponding to Arms & Legs, Expertise, and Memory — enabling each layer to iterate independently and evolve in combination.
MCP Hub
Arms & Legs — ConnectivityNon-invasive connection to all systems — Based on the Model Context Protocol (MCP) standard, unify heterogeneous systems such as ERP, MES, WMS, and IoT so that AI Agents gain the ability to read data and execute operations.
Skill Engine
Expertise — Domain CapabilitiesEncapsulating pluggable manufacturing expertise — Package manufacturing domain knowledge such as OEE analysis, smart scheduling, and quality traceability into standardized Skill modules that Agents invoke on demand, decoupling capabilities from the platform.
Knowledge Engine
Memory — Knowledge BasePreserving all proprietary factory knowledge — Organize factory knowledge including SOPs, equipment manuals, BOMs, and historical fault records into a semantically searchable enterprise brain through RAG vector retrieval and knowledge graph technologies.
Core Capabilities
Factory Knowledge Base Q&A
Factory Knowledge Q&ABuild factory knowledge — process documents, equipment manuals, quality standards, fault cases — into a semantically searchable AI knowledge base. Workers get precise answers in natural language.
- Process Q&A — Query process parameters and operating procedures anytime; Agent responds in real time based on SOPs
- Maintenance Assistance — Access equipment manuals and historical repair records to quickly diagnose faults and provide repair steps
- Quality Document Search — One-click search across ISO, SOP, inspection standards, and other cross-system documents
- New Employee Training — Replace traditional training with Q&A-based learning to shorten onboarding time
Deviation Analysis & Early Warning
Deviation Analysis & Early WarningMonitor production data in real time, automatically identify abnormal fluctuations in key metrics such as output, quality, and energy consumption, and generate actionable corrective plans through LLM root cause analysis.
- Quality Deviation Alerts — Automatically detect abnormal SPC chart patterns and identify quality drift trends early
- Output Anomaly Analysis — Compare planned vs. actual output and automatically pinpoint bottleneck processes
- Energy Anomaly Detection — Analyze equipment-level energy baselines to identify abnormal consumption and provide optimization recommendations
- Root Cause Reasoning — LLM combined with knowledge graphs automatically correlates multi-dimensional data to infer deviation root causes
AI Digital Human Interaction
AI Digital Human InteractionAn interactive AI assistant in digital human form, supporting both voice and text input, enabling frontline workers to access information without navigating complex systems.
- Voice Interaction — Workers query work orders, materials, and equipment status directly by voice
- Production Dashboard Broadcast — Scheduled or anomaly-triggered voice announcements of key production metrics and alerts
- Work Instructions — Digital human provides step-by-step guidance for complex assembly and debugging processes
- Multi-Device Sync — Consistent experience across shop floor displays, PDAs, and mobile phones; information accessible everywhere
Intelligent Decision Support
Intelligent Decision SupportBased on multi-source data fusion and AI reasoning, provide management with multi-scenario comparison and risk assessment for key decisions including scheduling optimization, cost analysis, and procurement.
- Scheduling Optimization — Recommend optimal production schedules by considering delivery dates, equipment status, and material readiness
- Cost Analysis — Auto-generate multi-dimensional cost reports with cost reduction opportunities highlighted
- Procurement Recommendations — Recommend purchasing timing and quantities based on historical data and market trends
- Supply Chain Risk Alerts — Predict risks such as material shortages and equipment downtime, generating contingency plans in advance
AI Customer Acquisition
AI Customer AcquisitionAn AI-powered customer acquisition engine that helps enterprises precisely target customers and auto-generate marketing content, achieving full-chain automation from lead mining to conversion analysis.
- Smart Customer Profiling — Multi-dimensional data analysis to precisely identify potential customers
- Content Auto-Generation — Batch-generate marketing copy, emails, and social media content
- Lead Intelligence — Automatically identify high-quality leads and push to the sales team
- Marketing Performance Analysis — Auto-track ROI and optimize campaign strategies
AI Customer Service
AI Customer ServiceA 24/7 intelligent customer service system integrating NLP and sentiment analysis to deliver efficient, accurate, and empathetic customer service.
- Smart Q&A — 24/7 automated responses to common customer questions
- Ticket Auto-Classification — Automatically identify issue types and route to the appropriate department
- Sentiment Analysis — Monitor customer sentiment in real time and auto-escalate high-risk complaints
- Knowledge Base Integration — Connect product documentation and FAQs to ensure accurate and consistent replies
Application Scenarios
Built on the EdgeOnto four-layer architecture, embedding AI Agents into the daily operations of the manufacturing shop floor.
📉 Scenario 1: Production Line OEE Anomaly Root Cause Analysis
The shop floor supervisor notices Line 3 OEE drop from 85% to 62% — cross-referencing MES, ERP, IoT data and calling the shift lead across 4 systems takes 2-4 hours on average, and the root cause may still be missed.
The shop floor supervisor asks in natural language: 「Why did Line 3 OEE drop today?」Agent Engine understands the intent, pulls MES downtime records, ERP material data, IoT device parameters, and WMS mold change records via MCP Hub; the OEE Analysis Skill calculates loss factors; Knowledge Engine retrieves similar historical cases — within 10 seconds, a complete root cause report is output: 「The OEE drop was primarily caused by a 14:20 mold change exceeding standard time (45min vs 25min standard). Related factor: Material Batch A had higher viscosity causing demolding difficulty.」
Root cause time slashed from 2-4 hours to 10 seconds. Cross-system correlation at 100%. Response moves from hours to seconds. OEE closed-loop time compressed 90%+.
📋 Scenario 2: Cross-System Order Creation and Processing
After creating a CRM order, a planner manually enters it into ERP, a scheduler plans it in MES, and warehouse staff reserve materials in WMS — spanning 4 systems and 3+ roles, taking 4-6 hours with error-prone handoffs.
After the salesperson confirms the order in CRM, Agent Engine automatically triggers the cross-system workflow: MCP Hub reads order details from CRM → writes to ERP to create a production order → queues it in MES → notifies WMS to lock material inventory. The entire process runs in Assisted Create mode — Agent generates operation previews for each step, with human confirmation required at critical decision points (e.g., delivery date conflicts). Order processing shifts from 「human-driven」 to 「Agent-driven」.
Order processing reduced from 4-6 hours to 3 minutes (with human confirmation). Error rate drops to zero. Cross-system consistency at 100%. Staff freed for high-value work.
👷 Scenario 3: Rapid Onboarding — Knowledge Q&A as Training
New employee training takes 2+ weeks of one-on-one mentoring, consuming skilled worker time. Process documents are scattered — new hires struggle to find information, leading to high error rates.
New employees ask the Knowledge Engine in natural language on day one: 「What are the standard steps for SMT feeder changeover?」 「What is the quality tolerance range for this process?」 Agent retrieves the latest SOPs, operation videos, and historical knowledge base in real time for precise answers. The AI Digital Human provides voice-guided step-by-step assistance for first-time operations, with the system comparing operational data against standards in real time and correcting deviations immediately.
Onboarding reduced from 2 weeks to 3 days. First-month error rate drops 60%. Mentor time freed by 80%. Training costs reduced 50%+.
Deployment Modes
SaaS Cloud Deployment
Quick deployment with low startup cost, ideal for small and medium-sized manufacturers. Maintenance-free, ready to use out of the box, with continuous feature updates and security hardening. Encrypted data transmission with tenant space isolation.
Recommended: Small & medium factoriesHybrid Cloud Deployment
Balancing performance and security — core data (production parameters, process formulas) stays in the local private environment, while non-sensitive services run in the cloud. Enterprise-grade API gateway for unified traffic management, meeting tiered data governance requirements.
Recommended: Enterprises with tiered data governanceFully Private Deployment
All services deployed on internal servers or private cloud — data never leaves the factory, meeting the strictest compliance and security requirements. Supports deep integration with existing IT/OT systems, with custom model fine-tuning and tailored development.
Recommended: Large enterprises / regulated industries