Try Tami’s platform promises to cut the cost and time of upskilling software engineers, accelerating AI tool adoption and giving mid‑size tech firms a competitive edge in a $30 billion market that remains fragmented and inefficient.
The interview on The SaaS CFO introduces Try Tami, a nascent ed‑tech startup founded by Kelby Zorg Drager and Dave Murphy, which aims to streamline corporate instructor‑led training for software engineers. Leveraging 25 years of experience delivering live training to Fortune‑100 firms, the founders identified the logistical bottlenecks of traditional training marketplaces and built a platform that lets engineering leaders design, book, and deliver custom courses directly with vetted experts, cutting out multiple intermediaries.
Try Tami targets the $30 billion live‑learning market, focusing first on technical training for software teams of 20‑200 engineers—an underserved segment as many large enterprises decentralize learning functions. The beta platform already supports AI‑driven automation of scheduling, evaluation, and content customization, and has secured early paying customers. The company raised $400 K in pre‑seed capital from friends‑and‑family and angel investors, using functional wireframes and a working demo to validate demand before seeking additional funding.
Key differentiators highlighted include the use of AI agents to accelerate course creation, real‑time matching with world‑class instructors, and a community‑first go‑to‑market strategy that delivers short, targeted live sessions (2‑4 hours) rather than lengthy e‑learning modules. The founders stress that while self‑paced content remains valuable, enterprises now crave rapid, hands‑on learning to keep pace with AI‑assisted coding tools such as Claude Code and GitHub Copilot, which many senior engineers are hesitant to adopt.
If Try Tami can scale its platform and expand beyond technical training into sales and leadership development, it could reshape the corporate training landscape by reducing friction, shortening time‑to‑skill, and enabling faster AI adoption across engineering teams. The company’s early traction and founder pedigree suggest a credible path to capturing a slice of the fragmented market, though continued product iteration and broader enterprise adoption will be critical.
Comments
Want to join the conversation?
Loading comments...