Applied Expertise in Wolfram Technology for AI

Level 2 Project

The Wolfram Technology for AI Level 2 certification is designed for developers, researchers and data practitioners who want to demonstrate that they can apply Wolfram LLM integration tools to solve a real, self-directed problem. Projects are built entirely as Wolfram Notebooks and must make meaningful use of one or more Wolfram LLM functions, such as LLMFunction, LLMSynthesize, LLMTool, LLMGraph, ChatObject, SemanticSearch or CreateVectorDatabase, while incorporating at least one element of the broader Wolfram technology stack, such as curated computable data, a Neural Net Repository model or a custom computation exposed as an LLMTool. The project should demonstrate that Wolfram computation and LLM reasoning are stronger together than either is alone.

The following are representative examples of the kind of original, applied work suitable for Level 2 certification. Refer to the grading rubric for specific requirements related to LLM function coverage, integration depth, notebook structure and design documentation.

• Intelligent Research Assistant: a domain-specific Q&A system over a document corpus using semantic search and LLM synthesis, enriched with live Wolfram|Alpha data.


• Computation-Augmented Chatbot: a multi-turn conversational agent equipped with custom LLMTool definitions that call Wolfram Language functions to deliver precise, verifiable answers.


• Automated Data Analysis Pipeline: a workflow that ingests raw data, applies LLM-based classification and summarization and generates a narrative report with Wolfram visualizations.


• LLM Orchestration Graph: a multi-step AI workflow using LLMGraph with branching logic and Wolfram computation embedded at key decision points.


• Semantic Knowledge Explorer: a notebook interface for a knowledge domain using vector search and LLM synthesis, enriched with curated Wolfram data and original visualizations.

Grading Rubric »