The Ten Most Promising Artificial Intelligence Companies of 2017

In this overview of RapportBoost.AI, the central argument is that data alone does not create results. Real business impact comes from continuously monitoring, interpreting, and optimizing customer engagement. Analytics only drive profit when they are translated into better decisions and better interactions.

RapportBoost is an artificial intelligence platform designed to help large brands communicate more effectively with customers through live chat and messaging. Its core objective is to reduce churn, increase conversion rates, improve average order size, and build durable customer relationships by understanding how front-line agents engage customers—and, over time, how bots should do the same.

The platform is built around three core services that move organizations from insight to execution.

RapportRoadMap serves as the diagnostic foundation. By ingesting chat transcripts and key performance indicators, the platform reverse-engineers what a successful conversation looks like. It identifies actionable behavioral insights, simulates how conversations would improve if agents adopted those behaviors, and quantifies how much revenue has been left unrealized.

RapportCoach operationalizes these insights. Delivered on a daily, weekly, or monthly cadence, it breaks feedback down to the individual agent level and functions as a coaching and training system. Agents receive clear guidance on how to improve their engagement style to drive better outcomes.

RapportMentor provides real-time support. This live widget monitors ongoing conversations and offers suggestions based on the customer’s linguistic cues. It is described as a “real-time spell-check” for emotion, tone, and friendliness, helping agents adapt in the moment rather than after the fact.

The evolution of RapportBoost is rooted in the belief that digital communication is uniquely difficult. Chat and messaging lack non-verbal cues and rely heavily on informal language such as emojis, slang, abbreviations, and GIFs. These features make misunderstandings common and relationship-building harder than in face-to-face interactions.

RapportBoost addresses this challenge by leveraging advances in artificial intelligence to surface deeper insight into how people communicate in messy, real-world digital conversations. After several years of development and real-world deployment, the platform is now expanding to larger brands and more emotionally complex sales environments, with future plans extending to bots, email, and voice-based interactions.

Despite being relatively young, RapportBoost has achieved notable recognition. Customers are referenceable and report strong gains in customer experience and revenue. One e-commerce CEO noted that the platform helped them “stay ahead of the curve” and unlock the full potential of their chat channel.

The company’s technology has also attracted industry attention. NVIDIA selected RapportBoost for its Deep Learning and AI Inception Program in 2017. Tech in Motion recognized the company for workplace diversity and named it a finalist for Best Tech Management in Los Angeles.

The leadership team plays a central role in the platform’s credibility. Michael Housman, co-founder and chief data science officer, brings over 15 years of experience building AI platforms and personally architected RapportBoost from the ground up. Tony Medrano, CEO and co-founder, contributes deep experience in scaling technology companies and leading high-performing sales teams.

Client outcomes reinforce the platform’s value. Organizations using RapportBoost report double-digit percentage improvements in acquisition, retention, and lifetime value, along with higher net promoter scores driven by better-trained and more emotionally intelligent agents.

A key differentiator is RapportBoost’s approach to language. Unlike traditional sentiment tools trained on structured data such as movie reviews, the platform is built to handle the unstructured, evolving nature of chat and messaging—where slang, misspellings, emojis, and colloquialisms are the norm.

The article highlights two major technical challenges the company had to overcome. First, language complexity. RapportBoost built deep linguistic libraries that evolve as new words, symbols, and emojis emerge.

Second, causality. Because chat is a two-way interaction, determining what actually causes a positive or negative outcome is difficult. RapportBoost combines retrospective analysis with experimentation to identify true causal effects over time.

Looking ahead, the company sees conversational commerce—via chat today and voice tomorrow—as inevitable. While bots will play a major role, they remain immature. RapportBoost’s strategy is to first perfect human communication and then use those insights to train emotionally intelligent automated systems.

The overarching conclusion is clear: customer engagement is not just a technology problem. It is a behavioral one—and artificial intelligence is most powerful when it is used to understand, guide, and amplify the human side of communication.