Thought Industries positions its Customer Learning & Intelligence Platform as a quote-based solution rather than a self-serve product with published rates. On the official pricing page, the company presents three named tiers—Starter, Professional, and Enterprise—and asks prospects to “Let’s talk” for each one. The page also makes clear that AI capabilities are included in every package, which means buyers are not paying extra just to access the platform’s core AI features. Beyond that, the public materials stop short of disclosing dollar amounts, billing cadence, or seat minimums, so any purchasing decision starts with a sales conversation.
The feature comparison helps buyers understand how the tiers differ before they request a quote. Starter includes foundational capabilities such as omnichannel learning, conversational AI learning, AI content creation, assessments, certification pathways, live and on-demand learning, custom learning portals, audience segmentation, analytics, Salesforce integration, webinar integrations, SSO, and unlimited administrator licenses. Professional adds capabilities such as multilingual support, expanded customization, advanced customer engagement, eCommerce analytics, advanced analytics, and BI tool connectivity. Enterprise layers on the most advanced options, including adaptive learning and AI content recommendations, SCORM content syndication, comprehensive customer learning portals and admin, gamification, comprehensive data integration, and workflows with webhooks, SFTP, and API access.
Because Thought Industries does not publish list prices, buyers should think in terms of scope-driven pricing rather than fixed packages. A smaller customer education program may use Starter as the baseline, while a team that needs multilingual delivery, custom styling, or analytics depth may land in Professional. Enterprises that need data orchestration, advanced automation, and content syndication will likely need the top tier and a tailored proposal. The result is a pricing model that is transparent about feature packaging but intentionally private about commercial terms, which is common for enterprise learning software.