Retrieval-Augmented Generation is reshaping how market research teams use AI, but not all RAG architectures are created equal. This article explains the differences between Vector RAG, Graph RAG, and Hybrid RAG, why Evals are essential for reducing hallucinations, and how STRATEGENCE’s RAGE approach turns AI into a decision guidance system grounded in market research rigor.

This holiday season, we’re honoring the people who move research and innovation forward. From early AI adopters to modern analytics experts, our team sees the future before it has a name. Here’s our tribute to the forward thinkers who turn insight into real direction.

What can Batman teach us about market research innovation? Quite a lot. From fighting villains of bad data to saving time and cost with AI-powered tools, discover how STRATEGENCE turns insights into superpowers and why Stratman always answers the call when businesses send up the STRAT Signal.

At STRATEGENCE, we examined 30+ frontier generative AI models and found that even the most advanced "genius agents" need structure. By treating them like curious 5th graders, we use our ART (Alignment, Relevance, Triangulation) + RAG approach to guide, prompt, and enrich their outputs, turning fragmented data into reliable insights and real market advantage.

Discover the “RiiSE” framework for building an agile, hybrid insights program that blends traditional and modern research methods. This stepwise approach uses Parallel Pathing, Bootstrapping, Proximity, and Critical Path strategies to drive continuous learning, faster decision-making, and scalable insights. Ideal for organizations seeking to innovate their market research process.