Glossary – AI & Automation Core
The AI & Automation Core represents the foundation of Anubavam's enterprise AI stack, where modular intelligence, workflow orchestration, and automation converge. This category defines the essential technologies, models, and frameworks that power end-to-end automation, learning, and data-driven decision-making across industries.
Understanding AI & Automation Core
The AI & Automation Core represents the foundation of Anubavam's enterprise AI stack, where modular intelligence, workflow orchestration, and automation converge. This category defines the essential technologies, models, and frameworks that power end-to-end automation, learning, and data-driven decision-making across industries.
Glossary Terms
| Term | Description |
|---|---|
| Modular AI Engines | Reusable AI building blocks such as OCR, NLP, recommendation, and forecasting engines that automate end-to-end workflows. |
| OCR (Optical Character Recognition) | AI technique that reads text from scanned images and documents, enabling accurate digital data extraction. |
| NLP (Natural Language Processing) | AI discipline that enables machines to understand, interpret, and respond to human language. |
| Recommendation Engine | AI system suggesting next actions, products, or insights based on behavioral or contextual data. |
| Forecasting Models | Predictive algorithms that project trends or outcomes such as demand, revenue, or risk. |
| Intelligent Document Processing (IDP) | Automated extraction of structured data from forms and PDFs using OCR and NLP. |
| Machine Learning Models | Algorithms trained on data to make predictions, detect patterns, or classify information automatically. |
| Predictive Analytics | Use of machine learning to forecast outcomes like student retention, sales success, or policy lapses. |
| Generative AI | AI that creates new outputs such as text, images, or code, powering marketing, learning, and conversational tools. |
| Knowledge-base Chatbot | Conversational AI assistant built on organizational data for instant, accurate query resolution. |
| AI Orchestration (MCP Framework) | Middleware layer that connects multiple AI modules to function as one unified workflow. |
| RPA (Robotic Process Automation) | Automation of repetitive, rule-based tasks using software bots and workflow triggers. |
| AI Readiness Assessment | Diagnostic framework that measures an organization's capability to scale AI responsibly and efficiently. |
Insights into AI & Automation Core
Mastering these foundational AI concepts enables organizations to connect data, automation, and intelligence into a single ecosystem. Concepts like AI Orchestration and Predictive Analytics show how AI-driven workflows are reshaping enterprise operations through continuous learning and efficiency.
Related Categories
Data, Cloud & Infrastructure
Data and cloud infrastructure form the backbone for scalable AI adoption. This category defines systems and processes that ensure data reliability, real-time access, and operational efficiency across enterprise ecosystems.
Analytics & Intelligence
Analytics and intelligence convert raw data into actionable insights. This category explains how AI integrates with analytics to provide real-time visibility, KPI tracking, and predictive decision-making for modern enterprises.
Business & Operations
This section focuses on how AI transforms everyday operations by optimizing workflows, improving process efficiency, and driving organizational agility through data-driven decision-making.