Overview
Modern manufacturing generates enormous amounts of data from machines, PLCs, MES, ERP, sensors, and quality systems. But most of it remains siloed, underutilized, and disconnected from modern AI and automation initiatives.
The Manufacturing Data Lake for GenAI Agents solves this problem by creating a unified, AWS native, AI ready data foundation across your plant operations. In just 4 weeks, manufacturers can harmonize OT and IT data into a scalable, secure data lake ready for analytics, predictive maintenance, and GenAI powered copilots.
By enabling real time insights, automation triggers, and GenAI assistants directly from your data, this solution transforms your operations without requiring a full system overhaul.
Key Capabilities
-
Unified Manufacturing Data Layer Integrates MES, ERP, IoT, SCADA, and quality data into a single AI ready lake.
-
AI & GenAI Ready Optimized for GenAI agents (on Amazon Bedrock or SageMaker), enabling natural language Q&A, predictive insights, and automation.
-
Shop Floor to Cloud Visibility Real time APIs and dashboards give operators, supervisors, and executives the same trusted data source.
-
Predictive Maintenance & Quality Detect anomalies, forecast equipment failure, and track yield in near real time.
-
Secure & Compliant by Design Role based access, audit logging, encryption, and governance aligned with AWS best practices.
This solution is designed to maximize AWS adoption and leverages Amazon S3 central manufacturing data storage with AWS Glue ingestion and harmonization of MES, ERP, IoT data.
Highlights
- AI Ready Data Lake in 4 Weeks: Purpose built for manufacturers.
- Power GenAI Agents with AWS Bedrock: Natural language Q&A on plant data.
- Predict Downtime & Optimize Yield: ML and GenAI drive smarter operations.
Details
Unlock automation with AI agent solutions

Pricing
Custom pricing options
How can we make this page better?
Legal
Content disclaimer
Support
Vendor support
Drop us an email at contact@applify.co For urgent inquiries, give us a call at +12067178200