Скачать или смотреть How Apollo designed AI agents for adoption and ROI

Apollo.io didn't force their team to adapt to a new AI tool. They put the agent where people already work and designed it around existing workflows.

🔗 Watch the full conversation: https://tray.ai/resources/on-demand-w...

In this clip, the Apollo IT team explains the homework they did before building their first agent. They reviewed tickets, analyzed Slack conversations, and figured out exactly where the agent should live. The goal wasn't to introduce a new system—it was to enhance the tools people already used every day.

This approach required evaluating multiple platforms, including prebuilt tools that promised quick deployment. But those rigid solutions would have forced Apollo's team to change how they worked. Tray's flexibility let them build agent interactions that matched their existing processes, right inside the Slack channels where work was already happening.

You'll hear why this "meet people where they are" strategy was critical for adoption and how Tray's capability to customize interactions made it possible to create something that felt natural rather than disruptive. When you can build exactly what your business needs instead of adapting to what a tool offers, agent adoption becomes significantly easier.

If your team is evaluating AI agent platforms or trying to figure out how to get people to actually use the agents you build, this shows why flexibility and integration into existing workflows matter more than feature lists.

#AIAgents #TrayAI #AgentAdoption #WorkflowAutomation #SlackIntegration #UserAdoption #ITAutomation #ApolloAI #AgentBuilder #B2BAI

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