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    <title>DEV Community: Afreed Khan</title>
    <description>The latest articles on DEV Community by Afreed Khan (@afreed_khan_3cee45ddffaa5).</description>
    <link>https://dev.to/afreed_khan_3cee45ddffaa5</link>
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      <title>DEV Community: Afreed Khan</title>
      <link>https://dev.to/afreed_khan_3cee45ddffaa5</link>
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      <title>AI Meeting Memory Assistant</title>
      <dc:creator>Afreed Khan</dc:creator>
      <pubDate>Mon, 13 Apr 2026 18:25:16 +0000</pubDate>
      <link>https://dev.to/afreed_khan_3cee45ddffaa5/ai-meeting-memory-assistant-4mc6</link>
      <guid>https://dev.to/afreed_khan_3cee45ddffaa5/ai-meeting-memory-assistant-4mc6</guid>
      <description>&lt;p&gt;Introduction:&lt;br&gt;
Meetings are powerful — but remembering what was discussed is often a challenge. Important decisions, task assignments, and responsibilities often get lost in chats or notes.&lt;/p&gt;

&lt;p&gt;To solve this, I built an AI Meeting Memory Agent that can:&lt;/p&gt;

&lt;p&gt;Store meeting notes&lt;br&gt;
Remember past conversations&lt;br&gt;
Answer questions using memory&lt;br&gt;
Use a fast LLM (Groq) for intelligent responses&lt;br&gt;
This project demonstrates how AI agents with persistent memory can improve real-world productivity.&lt;/p&gt;

&lt;p&gt;Problem statement:&lt;br&gt;
In most teams:&lt;/p&gt;

&lt;p&gt;Meeting notes are scattered&lt;br&gt;
People repeatedly ask the same questions&lt;br&gt;
Tasks get forgotten&lt;br&gt;
Context is lost over time&lt;br&gt;
We needed a system that doesn’t just chat — but remembers.&lt;/p&gt;

&lt;p&gt;Solution:&lt;br&gt;
I built an AI agent that combines:&lt;/p&gt;

&lt;p&gt;🔹 Persistent Memory&lt;br&gt;
Stores all meeting notes in a local JSON file.&lt;/p&gt;

&lt;p&gt;🔹 Smart Retrieval&lt;br&gt;
When a user asks a question, the system retrieves relevant past notes.&lt;/p&gt;

&lt;p&gt;🔹 AI Reasoning (Groq LLM)&lt;br&gt;
Uses Groq’s ultra-fast LLM to generate intelligent answers based on memory.&lt;/p&gt;

&lt;p&gt;🔹 Streamlit UI&lt;br&gt;
A simple, interactive web interface for users.&lt;/p&gt;

&lt;p&gt;Tech Stack:&lt;/p&gt;

&lt;p&gt;Python&lt;br&gt;
Streamlit&lt;br&gt;
Grouq API&lt;br&gt;
JSON&lt;br&gt;
dotenv&lt;br&gt;
System Architecture:&lt;/p&gt;

&lt;p&gt;User enters meeting note or question&lt;br&gt;
System checks if input is a question&lt;br&gt;
If note → store in memory&lt;br&gt;
If question → fetch memory + send to Groq&lt;br&gt;
Groq generates contextual answer&lt;br&gt;
Response is displayed in UI&lt;br&gt;
Key Feature — Memory + Intelligence&lt;/p&gt;

&lt;p&gt;Unlike traditional chatbots, this system:&lt;br&gt;
✔ Remembers past inputs&lt;br&gt;
✔ Uses context to answer questions&lt;br&gt;
✔ Improves over time&lt;br&gt;
✔ Acts like a real AI assistant&lt;/p&gt;

&lt;p&gt;Example:&lt;/p&gt;

&lt;p&gt;Input:&lt;br&gt;
Shiv will attend the meeting&lt;br&gt;
Sri is doing backend&lt;/p&gt;

&lt;p&gt;Question:&lt;br&gt;
Who is doing backend?&lt;/p&gt;

&lt;p&gt;Output:&lt;br&gt;
Sri is doing backend&lt;/p&gt;

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      <category>agents</category>
      <category>ai</category>
      <category>productivity</category>
      <category>showdev</category>
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