Follow our journey building the future of AI-powered customer engagement.
Our newest feature lets you define rules for autonomous responses. The AI handles routine conversations while escalating complex queries to your team — with full transparency and control.
A deep dive into our Vertex AI context caching architecture. By reusing cached context across conversation turns, we dramatically cut token usage without sacrificing response quality.
How we designed EngageFlow to handle conversations from multiple platforms in a single unified workspace, and the technical challenges of keeping everything in sync in real-time.
EngageFlow now translates incoming and outgoing messages across 40+ languages in real-time. Powered by Google's Gemini models, your team can serve international customers without hiring translators.
Transparency is a core value at EngageFlow. We break down exactly how we handle user data, what we store, what we don't, and how our ephemeral AI processing works to protect your conversations.
The story behind EngageFlow — how a team of four from Kyiv went from managing hundreds of customer conversations manually to building an AI copilot that does it in seconds.
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