Generative artificial intelligence has made it easier and cheaper for retailers to produce marketing copy, emails, social media posts and other customer communications. Calgary-based technology startup StoriBot.ai is betting that the next challenge will be determining whether all that content is actually connecting with customers.
The company operates a platform built around what it calls Narrative Intelligence™, a proprietary term StoriBot uses for its approach to analyzing the stories businesses are telling customers, identifying gaps and creating communications that remain consistent across different channels and stages of the customer relationship.
Founder and CEO Michael Harris argues that the proliferation of generative AI is creating an abundance of content without necessarily improving the effectiveness of business communications.
“Businesses already produce enormous amounts of content, but much of it is generic, disconnected and quickly forgotten,” Harris told Retail Insider. “StoriBot helps organizations understand the story they are currently telling, identify what is missing and create communications that connect more meaningfully with customers.”
Retail is emerging as one of the company’s areas of focus, particularly automotive dealerships and, increasingly, grocery and consumer packaged goods. StoriBot is already generating contracted enterprise revenue and has secured outside investment, although its retail strategy—particularly automotive—is still at an earlier stage of deployment.
Moving Beyond AI Content Generation
StoriBot began development in Calgary in 2024. Harris brings roughly three decades of experience in media, entertainment and brand storytelling to the venture and has also participated in the Founder Institute startup program.
Rather than positioning StoriBot as another AI writing tool, Harris describes it as a system for bringing greater structure to an organization’s communications. Businesses can provide existing content, company information and other material, which the platform analyzes using storytelling frameworks and brand context before producing material for different formats and channels.
The broader proposition is to measure how those communications perform and use the results to inform subsequent activity. Harris argues that general-purpose AI can create individual pieces of content, while StoriBot is intended to provide an additional layer of intelligence, governance and measurement connecting those communications to a company’s broader narrative, customer journey and business objectives.
“ChatGPT can give someone an answer,” Harris said. “StoriBot is designed to help an organization build, govern, distribute and continually improve a consistent narrative across its operations.”
The platform is designed to work alongside technology businesses already use. Harris said its roadmap includes additional connections with systems such as HubSpot and Salesforce, while integrations with specialized retail and dealership systems would depend on the technology, security and privacy requirements of individual organizations.
Automotive Becomes an Early Retail Focus
Automotive is currently StoriBot’s most developed retail use-case vertical, based on the maturity of its applications, market development and pipeline. The company is also pursuing opportunities in grocery and CPG, multi-location businesses, hospitality and service-oriented retail.
The automotive sector presents an opportunity because the relationship between a dealership and customer can extend well beyond an initial vehicle inquiry. Communications can continue through shopping, financing and delivery, and later into maintenance, service, retention and eventually another vehicle purchase.
StoriBot’s automotive applications are designed to support those interactions. Potential uses include vehicle and inventory marketing, personalized lead follow-up, CRM-based communications, email and text campaigns, social media and advertising, sales materials and service-retention programs. Harris sees an opportunity to connect those activities instead of treating each interaction as a separate marketing exercise.
A dealership could provide StoriBot with inventory information, brand standards, current offers, customer profiles, CRM stages, reviews and previous marketing campaigns. The system could then identify gaps in how vehicles or the dealership are being presented.
One example would be marketing a vehicle almost exclusively around specifications and price without addressing how it fits a particular customer’s needs or priorities. The platform could use that information to produce vehicle stories, salesperson follow-ups, emails, advertising concepts and social content adapted for different channels.
Harris ultimately wants those communications assessed against business measures including response rates, appointments, qualified leads, conversion, gross profit, service retention and referrals.
Grocery and CPG Offer Another Retail Opportunity
Grocery and consumer packaged goods represent another potential market because retailers in the sector already possess large amounts of customer and transactional information.
Loyalty programs can give grocers insight into purchasing behaviour, basket composition, promotions and product preferences. The challenge is turning that first-party information into relevant communications without overwhelming customers or compromising privacy and trust.
Harris believes StoriBot could add another layer to that personalization, using customer information to shape communications around different needs and behaviours instead of relying predominantly on broadly distributed promotional messages.
The company also sees applications across specialty retail, hospitality, home improvement and other multi-location businesses. Harris said its strongest opportunities tend to involve categories where purchasing decisions are influenced by trust, emotion or personal identity in addition to price.
Building the Business
StoriBot is generating contracted enterprise revenue while building out its leadership team. Harris said the company currently has approximately US$60,000 in contracted annual recurring revenue across two enterprise customers. He emphasized that not all of that revenue comes from retailers. The financial figures were provided by the company and have not been independently verified.
The leadership group includes Harris as founder and CEO; Tamara Rosenblum, chief marketing officer; Dawit Netere, chief technology officer; Joe Colangelo, partner and chief operating officer; and Nathalia Servetnyk, chief financial and risk officer.
Colangelo brings a lengthy retail operating background to the company. He said he led the launch of Petro-Points in 1994 as part of his senior retail-downstream leadership responsibilities at Petro-Canada, which operated an approximately 3,500-location national retail network at the time. His background also includes senior downstream leadership with Gulf Oil and 14 years as owner and president of Contemporary Office Interiors.
Servetnyk is a Ukrainian-Canadian legal, financial-services and business professional who leads StoriBot’s financial, governance and risk-management functions.
Harris said StoriBot has received its first outside investment through a SAFE agreement and is undertaking a US$2-million SAFE financing round. The company plans to use additional capital for platform development and integrations, customer acquisition and repeatable enterprise implementations.
StoriBot has set an internal objective of reaching approximately US$2 million in annual recurring revenue within 18 months as it converts more of its enterprise pipeline and expands adoption. Harris emphasized that the figure represents an operating target, not a forecast or guaranteed result.
Can Narrative Become the Differentiator?
Underlying StoriBot’s business model is a broader argument about where generative AI is heading. As retailers and other businesses gain access to increasingly capable tools for producing text, imagery and marketing material, Harris believes simply generating additional content will offer diminishing competitive advantage. StoriBot instead focuses on identifying the difference between what an organization believes it is communicating and what customers are actually receiving.
In practice, that means examining which messages are connecting, which are being ignored or misunderstood, what information or emotional elements may be missing and whether changes to those communications improve business results.
“As AI-generated content becomes commonplace, simply producing more material will not create differentiation,” Harris said. “The competitive advantage will come from meaning, authenticity, consistency and the ability to connect a narrative to measurable behaviour.”
StoriBot uses Narrative Intelligence™ as the proprietary term for its methodology and platform. Harris describes the concept as a systematic approach to analyzing, governing and measuring the narratives organizations use in customer communications. The company is seeking to establish it more broadly as a recognized business discipline.
StoriBot has also received external recognition for its technology. The company was named Specialist AI Platform of the Year, 2026–2027 through the Corporate LiveWire Global Awards and received a Global Recognition Award for Innovation, 2026 from Global Recognition Awards. Harris said external recognition has helped open conversations with prospective enterprise customers, partners, employees and investors, while acknowledging that longer-term success will ultimately depend on customer results.
Retail Case Studies Are the Next Test
Over the next 12 to 24 months, StoriBot plans to convert more of its pipeline into paying customers while expanding its CRM and data integrations. Within retail, Harris wants to establish automotive and grocery case studies demonstrating measurable changes in customer engagement, conversion, retention and operating productivity.
That will be an important measure of StoriBot’s retail proposition. Generative AI has already demonstrated that retailers can create considerably more content with fewer resources. StoriBot’s next objective is to demonstrate that applying greater structure, relevance and consistency to those communications can produce measurable commercial results.
