INTRODUCING FLOWOPS
Define, automate, and runfully or semi-agentic workflows
The open-source platform for creating and running
AI workflows using simple scripts
01
LLM-Native
Build workflows that leverage the full potential of language models. Enable your agents to understand context, make decisions, and take actions autonomously.
02
Unified Data & Integration Layer
Access knowledge bases, store data, and connect to external services through a simple, unified interface. No complex setup required.
03
Open Source & Developer-First
Built for developers who value flexibility and control. Fully open source, extensible, and powered by simple Python scripts.
Simple, Yet Powerful
screening_workflow.py
@trigger(integration="linkedin", event="resume", source="CompanyLinkedin")
def run(context):
# Extract key information
parsed = ai.extract(
prompt="Extract full name, phone, work experience, summary of resume",
input=context["resume"]
)
# Conduct automated interview
conversation_data = ai.call(
parsed["phone"],
script="perform a screen interview for 15 minutes for junior .net positions"
)
# Generate and send summary
summary = ai.summarize(conversation_data)
email.send("hr@company.com", summary)