PSPTechHub AI Training
PSPTechHub + AI: Making Manufacturers Predictive, Automated and Decision-Ready
Build AI capability around manufacturing data, enterprise documents, process intelligence, quality workflows, operational risk, automation and production-grade deployment.
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- 2Retrieve
- 3Reason
- 4Tool: SAP Lookup
- 5Validate
- 6Respond
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PSPTechHub AI Training converts AI concepts into deployable enterprise capability. The program covers Generative AI, RAG, Agentic AI, LLM evaluation, prompt engineering, vector databases, cloud AI, document intelligence, computer vision, predictive analytics, MLOps, LLMOps, observability, governance, APIs and production deployment.
About PSPTechHub in AI
PSPTechHub AI capability is grounded in enterprise use cases, not demo-only AI. Delivery patterns include Agentic AI for accounts payable automation on Oracle ERP, Vertex AI decisioning with confidence scoring and explainability, RAG assistants for enterprise knowledge retrieval, model benchmarking on Amazon Bedrock, multi-agent orchestration using CrewAI, healthcare predictive models, fraud detection, document intelligence, AI call assistants, sentiment analysis, RCA bots, code review automation, virtual trainers, computer vision using YOLO and OpenCV and deployment pipelines using FastAPI, Docker, MLflow, LangSmith, Weights and Biases, Azure OpenAI, AWS and GCP.
AI in Action
Enterprise AI dashboard with RAG confidence, document queue, model evaluation, agent workflow status, fraud flags, latency, cost and audit trail.
- 1Plan
- 2Retrieve
- 3Reason
- 4Tool: SAP Lookup
- 5Validate
- 6Respond
10:41 retrieval k=8 · sources=4
10:40 tool=mes.query · 2.1s
The PSPTechHub AI Advantage
AI Beyond PoC
Training moves from prompt demos to architecture, APIs, retrieval, evaluation, observability, security and deployment.
Grounded Decisioning
RAG, vector search, confidence scoring, explainability and evaluation reduce ungrounded AI responses.
Manufacturing Fit
AI training connects document intelligence, quality checks, operator support, RCA, predictive analytics and enterprise workflows.
Training Structure
Role-based training designed around implementation, integration, deployment, validation and production support.
Foundation Track
- Audience
- Business analysts, developers, AI beginners, solution teams
- Coverage
- AI, ML, deep learning, GenAI, LLMs, embeddings, RAG and enterprise AI use cases
- Practical output
- AI use-case map for manufacturing and enterprise teams
Builder Track
- Audience
- AI engineers, developers, data teams
- Coverage
- Python, prompt engineering, LangChain, LangGraph, LlamaIndex, FastAPI and vector databases
- Practical output
- Working RAG assistant over enterprise documents
Integration Track
- Audience
- Backend teams and enterprise architects
- Coverage
- REST APIs, SQL, cloud storage, ERP integration, workflow orchestration, authentication and audit logging
- Practical output
- AI API connected to documents, database and business workflow
Deployment Track
- Audience
- Technical leads and AI platform teams
- Coverage
- Docker, CI/CD, MLflow, LangSmith, Weights and Biases, monitoring, evaluation, cost, latency and governance
- Practical output
- Deployment-ready AI service with evaluation metrics
Capstone Track
- Audience
- Project delivery teams
- Coverage
- RAG, Agentic AI, document intelligence, confidence scoring, audit trail, dashboard and deployment
- Practical output
- Production-style AI workflow with dashboard and governance layer
Curriculum
Hands-On Labs
Project-Backed Learning
Accounts payable automation with Oracle ERP, Vertex AI, confidence scoring and audit logging
RAG assistants for enterprise knowledge retrieval and document QA
Amazon Bedrock model benchmarking for latency, cost and accuracy
CrewAI multi-agent workflows for retrieval, reasoning, validation and response generation
Healthcare malnutrition risk and clinical deterioration prediction
Insurance policy assistant with GPT, LangChain and Pinecone
Real-time AI call assistant with transcription, sentiment and fraud detection
RCA bot using Azure AI Search and cognitive services
AI-powered code reviewer using LangGraph and local LLMs
Computer vision inspection and object detection using YOLO and OpenCV
Tools and Platforms Covered
Who Should Attend
Outcomes After Training
Build RAG applications over enterprise documents
Design Agentic AI workflows with tool usage
Evaluate LLM output for accuracy, latency and cost
Deploy AI services through secure APIs
Build document intelligence and computer vision prototypes
Apply AI governance, audit logging and explainability
Convert AI use cases into production-ready delivery architecture
Required AI Topic Not Covered Above?
PSPTechHub can build a custom AI training roadmap around manufacturing quality, SOP intelligence, AP automation, call center automation, RCA bots, predictive maintenance, document intelligence, computer vision inspection, GenAI governance or private cloud AI deployment.
Build Customized Training PlanRequest Platform Training Plan
PSPTechHub + AI turns manufacturing data, documents, defects, risks and decisions into predictive execution, intelligent automation and measurable operational control.
Book Corporate TrainingFrequently Asked Questions
What is covered in PSPTechHub AI Training?
The program covers Generative AI, RAG, Agentic AI, LLM evaluation, prompt engineering, vector databases, cloud AI, document intelligence, computer vision, predictive analytics, MLOps, LLMOps, observability, governance, APIs and production deployment.
Does PSPTechHub AI Training include Generative AI and RAG?
Yes. GenAI fundamentals and full RAG architecture — ingestion, chunking, embeddings, retrieval, reranking and context injection — are covered with hands-on labs over policy and SOP documents.
Does training include Agentic AI?
Yes. Agentic AI is covered using LangGraph, CrewAI and AutoGen, including tool calling, memory, multi-agent orchestration and a multi-agent capstone workflow.
Does training include LangChain, LangGraph and vector databases?
Yes. LangChain, LangGraph, LlamaIndex and vector databases including FAISS, Pinecone, ChromaDB, Qdrant and Elasticsearch are covered with implementation labs.
Does training include MLOps and LLMOps?
Yes. The Deployment Track covers Docker, CI/CD, MLflow, LangSmith, Weights and Biases, monitoring, evaluation, cost, latency and governance.
Does training cover manufacturing AI use cases?
Yes. Project-backed learning includes AP automation on Oracle ERP, RCA bots, document intelligence, predictive maintenance patterns, healthcare risk prediction and computer vision inspection with YOLO and OpenCV.
Build Platform Capability with PSPTechHub Training
PSPTechHub training converts implementation experience into role-based capability for industrial teams working across MES, IIoT, PLM, ALM, AI, cloud, low-code and automation.