Launching today

AI Feedback Flow

Launching today

Autonomous AI Customer Service Department with Deep Memory

1 follower

Autonomous AI Customer Service Department with Deep Memory

1 follower

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Email marketing

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Community management

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AI Workflow Automation

AI Feedback Flow by Naroka Automation Studios is a revolution in reputation management. This autonomous ecosystem uses Gemini AI and n8n to analyze feedback in real-time, recognize returning customers via Deep Memory Architecture, and reclaim up to 85% of your support team's time. It doesn't just monitor—it understands context, captures hidden sentiment, and provides ready-to-use response drafts instantly via Telegram.

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Launch tags:SaaS•Artificial Intelligence

Launch Team / Built With

Mintlify — Knowledge infrastructure for AI agents

Knowledge infrastructure for AI agents

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Maker

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Hello Product Hunt community! 👋 I’m the creator behind Naroka Automation Studios, and I’m thrilled to introduce AI Feedback Flow. Managing brand reputation shouldn't be a manual grind. I built this system to solve the 'information noise' problem that many support teams face. By combining n8n workflows with the analytical power of Gemini AI, we’ve created a system that doesn’t just forward messages—it understands them. What makes it different? Deep Memory Architecture: It remembers past interactions with customers by their email, providing context that standard bots miss. Zero Latency: You get instant alerts and professional response drafts in Telegram the second a review hits. Massive Time Savings: Our goal was to reclaim up to 85% of staff time spent on routine sorting and summarizing. I’m excited to hear your thoughts and answer any questions about the technical architecture or implementation! Let’s revolutionize customer experience together

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24h ago

Forum Threads

p/ai-feedback-flow

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24h ago

How are you handling customer feedback scale in 2026?

I ve spent the last few months building AI Feedback Flow at Naroka Automation Studios, focusing on a major pain point: the "information noise" of manual feedback management.

While working on this, I realized that simple automation isn't enough anymore systems need "institutional memory" to provide real value. Our architecture uses a Deep Memory Module to track interaction history via email, ensuring the AI behaves like a manager who actually knows the client.

I d love to hear from the community:

How do you currently balance speed and personalization in your support workflows?
What are the biggest challenges you face when integrating AI into your existing customer experience stack?
Do you prefer fully autonomous responses or a "Human-in-the-loop" approach like our Telegram toolkit?

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I ve spent the last few months building AI Feedback Flow at Naroka Automation Studios, focusing on a major pain point: the "information noise" of manual feedback management.

I d love to hear from the community:

How do you currently balance speed and personalization in your support workflows?
What are the biggest challenges you face when integrating AI into your existing customer experience stack?
Do you prefer fully autonomous responses or a "Human-in-the-loop" approach like our Telegram toolkit?