Deploy agents that execute bash commands, query knowledge bases by accessing RAG pipelines, integrate SaaS platforms via MCP or API, and edit code autonomously
Execute bash commands, access RAG knowledge bases, and connect via MCP to external services
Automatically write, test, and deploy production-ready code based on natural language instructions
Orchestrated multi-agent workflows with shared context for distributed task execution
import streamlit as st
def main():
# Setup
st.set_page_config(page_title="Hello", layout="centered")
# Navigation
tabs = st.tabs(["📄 1. Hello Tab"])
# Tab Text
with tabs[0]:
st.write("### ✨ Banner ✨")
st.header("👋 Hello!", divider="rainbow")
st.write("Hello! This is a simple test page.")
# Button Action
if st.button("Say Hello Again!", key="hello_btn"):
st.balloons()
st.success("Hello there! 🎉")
st.toast("Nice to see you again!")
if __name__ == "__main__":
main()Loading live app...
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Surface agent actions, generated content, and real-time updates through elegant Streamlit applications
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Built with agents, cloud infrastructure, and Streamlit interfaces
Analyzes tender documents, extracts requirements via RAG, checks compliance against company capabilities, and generates complete responses with supporting documentation automatically
Conducts outbound calls with natural conversation, qualifies leads through intelligent dialogue, schedules meetings based on availability, and updates CRM automatically via MCP integration