Frame AI is a streaming generative artificial intelligence platform that enables businesses to derive real-time insights from customer interactions. Founded in 2016 by George Davis, Robbie Mitchell, Jesse St. Charles, and Brandon Reiss, the company is headquartered in New York. It offers solutions based on natural language processing (NLP) and machine learning (ML) technologies. The platform is recognized as a pioneering implementation of the Stream-Trigger Augmented Generation (STAG) architecture, which interprets natural language data from unstructured sources to support operational efficiency, personalization, and regulatory compliance.
STAG Architecture and Technological Infrastructure
STAG, the foundation of Frame AI’s platform, goes beyond traditional response-based AI systems by continuously monitoring unstructured natural language data, identifying patterns, and initiating automated actions through triggers. The architecture analyzes large volumes of emails, calls, chats, and surveys to automate internal workflows and inform data-driven operational decisions.
Frame AI employs an adaptive AI framework that runs broad, low-cost analysis models alongside advanced models for deriving critical insights. To facilitate the integration of structured and unstructured data, the platform features a customizable API infrastructure compatible with SaaS systems such as Salesforce, Zendesk, and Snowflake. Additionally, the platform can be deployed within customers’ own cloud environments.
Application Areas
Frame AI offers solutions for customer experience management, risk monitoring, operational efficiency, and regulatory compliance across a range of sectors. The platform is adaptable to the specific business needs of industries such as telecommunications, finance, healthcare, technology, and customer service.
In the telecommunications sector, it helps improve customer satisfaction and reduce costs by delivering instant insights from customer communications. In financial services, it enables the early detection of compliance risks to help prevent regulatory penalties. In healthcare, it supports real-time monitoring of patient interactions and processes data in compliance with HIPAA (Health Insurance Portability and Accountability Act).
Functional Modules and Usage Features
The platform includes features such as generative enrichment, contextual analysis, proactive triggers, and automated quality assurance to identify “critical moments” in customer interactions and drive continuous user experience improvement. It supports functions such as cost attribution, agent effort analysis, customer satisfaction (CSAT) prediction, campaign performance measurement, profile enrichment, and anomaly detection—enabling integration with marketing, product development, sales, and customer support functions.
Compliance and Security Solutions
To support regulatory compliance, Frame AI offers tools for automatic complaint detection, classification, and prioritization. The platform integrates NLP and ML techniques to comply with regulations such as KYC (Know Your Customer), AML (Anti-Money Laundering), BSA (Bank Secrecy Act), Dodd-Frank, and UDAAP (Unfair, Deceptive, or Abusive Acts or Practices).
Corporate Development and Investments
Frame AI has raised a total of $17.9 million in funding from investment firms including FirstMark Capital, Greycroft Partners, G20 Ventures, and Velvet Sea Ventures. In December 2024, it was acquired by HubSpot, a company operating in the customer relationship management (CRM) domain. Following the acquisition, Frame AI’s technology was integrated into HubSpot’s portfolio of AI-powered tools.
Future Outlook
Trends in processing and analyzing unstructured data are expanding the applicability of Frame AI’s STAG-based approach. The company’s strategy focuses on unifying disparate data sources across business units to deliver a more predictive and adaptive customer experience. Due to its customizable models, workflow-triggering capabilities, and compliance modules, the platform is expected to grow in sectors where regulatory scrutiny and data-driven decision-making are increasingly prioritized.
