Making LLMs More Reliable with RAG: Why Inputs Matter More Than Models | KMWorld x Adlib
RAG doesn’t magically “fix” LLMs, your inputs do. In this session, Jason breaks down the five biggest myths tanking enterprise AI reliability.
Large Language Models are only as smart as the data you feed them. Yet most enterprises still treat RAG as a silver bullet for accuracy—when the real issue is upstream: unstructured, inconsistent, and low-quality documents.
In this KMWorld webinar, Adlib’s Chief Architect Officer Jason Jakob exposes the top misconceptions about RAG and explains how enterprises can drastically improve precision, recall, and compliance by fixing their inputs—before models ever touch them.
You’ll see why AI accuracy starts with clean, contextualized, and validated data—and how Adlib’s hybrid AI workflow turns messy content into machine-navigable, compliant, AI-ready pipelines that make LLMs more reliable.
You’ll Learn
- What RAG really does—and doesn’t do. Why retrieval doesn’t fix poor inputs and how to build smarter chunking and embedding strategies.
- The five biggest myths derailing AI reliability. From “RAG will fix accuracy” to “OCR is solved.”
- How hybrid OCR + LLM pre-processing improves accuracy. Combine advanced OCR, semantic chunking, and metadata enrichment to cut hallucinations and human review time.
- How enterprises are deploying this today. See real-world insurance and manufacturing examples achieving 20% faster validation and ~$1.4M annual savings.
- What’s next for enterprise RAG. A look at GraphRAG, agentic workflows, and audit-ready AI pipelines.
Why Watch
By 2026, Gartner predicts 60% of AI projects will be abandoned without AI-ready data. Enterprises are discovering that accuracy problems aren’t caused by weak models—they’re caused by broken document pipelines.
Watch this session to learn how to build trust in your AI results by starting where it matters most: the input layer.
Who Should Watch
- AI, Data, and Automation Leaders
- Information Management & RIM Professionals
- CIOs, CTOs, and IT Transformation Executives
- Compliance & Quality Managers in Regulated Industries
Watch On-Demand
Get immediate access to the full 45-minute session, including live Q&A, demos, and actionable insights on making your LLMs more reliable with RAG.
Our Speakers
Jason Jakob
Jason Jakob is a Chief Architect Officer at Adlib Software, where he leads the Adlib platform that transforms unstructured documents into AI-ready data with classification and extraction at scale. Previously CTO at Entelegis (industrial energy-management SaaS) and co-founder/CTO of Onlinetel (taken public on the TSX), he has also consulted across medical, retail, and manufacturing for clients including Toyota and AMC. Jason studied business at Wilfrid Laurier and is an MBA candidate at the University of Cumbria.
