AI Strategy for LMS
Budget: $250 – $750 USD
Our learning management system is ready to evolve and I need an LLM specialist to map out a clear, technically sound roadmap for weaving generative AI into the platform. I’m not after code yet—what I want first is informed, practical guidance that weighs the pros, cons, and effort of features such as personalized learning paths, automated grading, and real-time chatbot assistance so I can decide where to focus our development budget.
You’ll need to explore our current course catalog, user analytics, and content pipeline, then recommend the best approach to leveraging large language models—whether that means fine-tuning OpenAI GPT-4, using a retrieval-augmented-generation (RAG) setup with LangChain, or employing an on-prem model like Llama-3 together with a vector store such as Pinecone or Weaviate. Because our LMS serves corporate training, special attention to compliance, security, and data privacy is crucial.
Deliverables I expect:
• A concise report (10–15 pages) outlining recommended AI use cases, required data prep, model choices, and integration architecture
• A phased implementation timeline with milestones and estimated effort
• A live 60-minute walkthrough so my product and engineering teams can ask questions
I’m able to provide sandbox access to the LMS, anonymized user data, and any existing SCORM/XAPI content you need for evaluation. If additional datasets or synthetic data generation are required, call that out in your plan.
This is a focused strategic engagement; once we have the roadmap in hand, we can discuss a follow-on build phase if it makes sense for both of us.
You’ll need to explore our current course catalog, user analytics, and content pipeline, then recommend the best approach to leveraging large language models—whether that means fine-tuning OpenAI GPT-4, using a retrieval-augmented-generation (RAG) setup with LangChain, or employing an on-prem model like Llama-3 together with a vector store such as Pinecone or Weaviate. Because our LMS serves corporate training, special attention to compliance, security, and data privacy is crucial.
Deliverables I expect:
• A concise report (10–15 pages) outlining recommended AI use cases, required data prep, model choices, and integration architecture
• A phased implementation timeline with milestones and estimated effort
• A live 60-minute walkthrough so my product and engineering teams can ask questions
I’m able to provide sandbox access to the LMS, anonymized user data, and any existing SCORM/XAPI content you need for evaluation. If additional datasets or synthetic data generation are required, call that out in your plan.
This is a focused strategic engagement; once we have the roadmap in hand, we can discuss a follow-on build phase if it makes sense for both of us.