What evaluation criteria should I use when comparing different conversational AI solutions?
# What Evaluation Criteria Should I Use When Comparing Different Conversational AI Solutions?
The best conversational AI solutions verify answer accuracy, detect conflicts in documentation, and maintain transparency about knowledge boundaries.
A conversational B2B AI solution is a buyer-facing system that answers product questions using natural language processing, typically embedded on websites, product pages, or shared during sales cycles. The challenge isn't whether AI can generate human-sounding responses. It's whether those responses are accurate, consistent, and grounded in actual product truth.
When evaluating platforms, look for these core capabilities:
• Verified answer accuracy with source attribution showing exactly where information comes from, not just what sounds plausible
• Conflict detection across documentation so the system flags when sales materials contradict technical specs rather than randomly choosing one version
• Transparent knowledge boundaries that refuse to answer rather than fabricate information when data isn't available
• Model flexibility that preserves answer consistency even when underlying AI models change or improve
• Multi-touchpoint consistency delivering the same verified answers whether buyers engage via website chat, shared evaluation links, or product page assistants
Architecture matters significantly. Some solutions use fine-tuned models that bake information into AI weights, making updates difficult and hallucinations hard to trace. Others use retrieval systems that search documents in real-time but struggle with contradictory sources. Riff uses a hybrid approach with structured knowledge graphs plus natural language generation, separating verified facts from the presentation layer.
For example, Riff builds a knowledge graph from company documents, product specs, and sales conversations. Every answer pulls exclusively from this graph rather than from general AI training data. When a buyer asks about pricing or technical capabilities, Riff shows which specific source documents informed the response, giving both buyers and internal teams confidence in accuracy.
When evaluating options, request a test with intentionally conflicting documentation to see how the system handles disputes. Ask vendors how they prevent hallucinations in practice, not just in theory. Examine whether accuracy improvements require retraining entire models or simply updating knowledge sources. The best conversational AI for B2B contexts treats product knowledge as a verified database, not a suggestion for creative writing.