Agent turns conversations Into follow-ups In Any Language

Speak in your own language.This AI agent finds leads, translates meetings in real time, answers Q&A, and automatically executes follow-ups—turning conversations into action without manual work.

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Inspiration

Teams talk to prospects every day, but deals often stall after meetings—especially across languages. Notes get lost, follow-ups are delayed, and intent fades. We wanted an agent that listens, understands in any language, and acts, so conversations reliably turn into execution.

What it does

Agent turns conversations into follow-ups in any language is an AI execution agent that:

  • Discovers and prioritizes high-intent leads
  • Joins meetings, provides real-time translation (speak your native language), and captures context
  • Answers live Q&A from meeting knowledge
  • Automatically generates and sends context-aware follow-ups

It closes the gap between conversations and action—without manual work.

How we built it

  • Yutori scans public and web sources to identify and rank leads by intent and timing
  • Recall.ai captures meetings with transcription and speaker context
  • Tinyfish enables real-time translation so users can speak in their own language
  • A context-aware CRM orchestrates reasoning and actions
  • Auth0 handles authentication and access control
  • Retool for crm and management for followup
  • We used Tonic fabricated dummy data to safely demonstrate realistic workflows

Challenges we ran into

  • Preserving meaning across real-time translation while extracting accurate intent
  • Turning unstructured conversation into reliable, actionable steps
  • Designing autonomy without over-automation or hallucinated actions
  • Keeping latency low for live demos

Accomplishments that we’re proud of

  • End-to-end autonomous flow: lead → meeting → Q&A → follow-up
  • Real-time, multilingual meetings where users speak their native language
  • Follow-ups aligned to decision context—not generic emails
  • Successful integration of multiple tools into a single agentic loop

What we learned

  • Execution—not assistance—is where AI delivers real value
  • Language barriers disappear when translation is native to the workflow
  • Storing decision context beats storing notes
  • Autonomy works best with clear triggers and guardrails

What’s next for Agent turns conversations into follow-ups in any language

  • Learning from follow-up outcomes to improve prioritization
  • More channels (phone, in-person audio) and calendar-aware actions
  • Organization-specific playbooks and compliance modes
  • Analytics on conversion rates and decision velocity

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