Spotlight Interview: Josh Rose on How Zagger.ai Turns Unstructured Business Data Into Productive AI Workflows

In this Technology Executives Club® Spotlight Interview, Alex Jarett sits down with Josh Rose, Co-Founder and CEO of Zagger.ai, to discuss how his team is helping companies turn messy, unstructured business data into productive AI workflows.

Zagger.ai focuses on one of the biggest challenges in enterprise AI: the gap between what AI models can do and what companies need in order to make AI useful. Much of the most valuable business knowledge lives outside structured systems. It is found in emails, chats, Jira tickets, documents, spreadsheets, conversations, and the experience of the people doing the work every day.

Turning Tribal Knowledge Into a Business Asset
A consistent theme throughout the conversation is the value of tribal knowledge. Josh explains that companies often have years of lessons learned, internal decisions, customer history, and process knowledge scattered across different systems and people.

Zagger.ai helps bring that messy, real-world data together so AI can support better decisions, more repeatable workflows, and faster execution.

Improving Key Workflows with AI
One example Josh shares is a grant writing workflow for a California nonprofit. The organization had a 16-year archive of grant materials that was highly valuable and could not simply be shared with public AI tools.

Zagger.ai turned that archive into a knowledge partner for the grant writing team. The system did not replace the grant writers, but it helped reduce the time required to complete grants by approximately 30%. It also helped reduce onboarding time for new grant writers from three months to one month.

Scaling What Top Performers Do
Josh also discusses how Zagger.ai is being used in lead generation and outreach. In these cases, the value comes from capturing the logic, research process, and decision-making approach of high-performing people and turning that into a repeatable workflow.

In one example, a team reduced the time required for highly customized outreach from roughly 60 minutes per response to about eight minutes per response.

Josh emphasizes that this is not about removing people from the process. The AI helps with research, first drafts, follow-up logic, and workflow support, while the human still reviews, refines, and decides what gets sent.

Supporting Project Management and Team Communication
Another use case discussed is software development and project management. While much of the AI conversation focuses on code generation, Josh points out that a large part of the software development lifecycle involves the work around the code.

Plans, customer meetings, team discussions, Jira tickets, and emails all contain important context. By bringing that information together, Zagger.ai can help teams onboard new people faster, improve communication, and support better execution.

Protecting Sensitive Data and Private Business Knowledge
A major part of Zagger.ai’s approach is privacy and control. Josh explains that Zagger.ai can be deployed in ways that allow organizations to keep their data private, including private LLM and on-premise options.

This makes the platform especially relevant for companies with valuable intellectual property, privacy concerns, legal requirements, or compliance restrictions that prevent them from using public AI systems with sensitive business data.

➡️ Watch the full Spotlight Interview with Josh Rose to hear how Zagger.ai is helping companies turn unstructured business data into productive AI workflows.

*️⃣ Guest: Josh Rose, Co-Founder and CEO, Zagger.ai
*️⃣ Host: ALEX JARETT, Founder, Technology Executives Club®