Sorilbran Stone

Sorilbran Stone is a Visibility Engineer and founder of Five-Talent Strategy House, a Detroit-based consultancy helping founders and teams become understandable – and recommendable – inside AI-driven search and decision systems.

She focuses on how AI systems shape decisions long before a human ever clicks a link. Visibility today depends on whether those systems can clearly place you in the right context, at the right time, for the right problem. Sorilbran helps organizations build the structural clarity those systems require, aligning entity identity, specialization, audience context, expertise, proof, and connections into a coherent, machine-readable narrative.

Sorilbran is an active contributor to Detroit’s tech ecosystem and a recurring workshop leader with Black Tech Saturdays, where she has led sessions including Engineering Visibility for Humans and Machines, AI Research Deep Dive, and Using AI to Find Winnable Markets. Her workshops focus on helping practitioners understand how AI systems evaluate credibility, relevance, and situational fit without relying on manipulation or short-term tactics.

She is also the creator of NORAH, a go-to-market intelligence platform designed to help match founder innovations to actual gaps in the market. NORAH was People’s Choice Award winner at the Venture 313 Tech the Halls Pitch Competition 2025, powered by Gilbert Family Foundation. Through NORAH, Sorilbran leads a founder cohort focused on identifying winnable markets, preserving institutional knowledge, and building durable visibility infrastructure that survives platform and algorithm shifts.

Before launching Five-Talent Strategy House, Sorilbran spent over a decade inside high-growth marketing environments, where she helped generate tens of millions of dollars in pipeline and witnessed the gradual breakdown of traditional performance signals. As AI systems began compressing discovery, evaluation, and recommendation into a single moment, her work shifted from content and demand generation to studying how large language models infer meaning, authority, and trust.

She is the author of UnInvisible: An AI Visibility Playbook, which introduces the concept of building a Minimum Viable Knowledge Graph – a practical methodology for making businesses legible and trustworthy to AI systems without chasing algorithms. Her work emphasizes ethical entity engineering, compensating signals, and long-term resilience over optimization theater.

Sorilbran is known for developing original frameworks that help organizations preserve and translate institutional knowledge in machine-mediated environments, including the Brand Intelligence Stack, the Translation Layer, and the Steganographic Layer – concepts designed to ensure that what a business knows, means, and stands for remains intact as systems evolve.

Sorilbran lives and works in the Detroit area, partnering with founders, consultants, and teams navigating visibility, credibility, and growth in a post-search world.