SparkBeyond/agentune

Tune your AI Agent to best meet its KPI with a cyclic process of analyze, improve and simulate

49
/ 100
Emerging

Agentune helps product, operations, and ML teams improve customer-facing AI agents like chatbots or virtual assistants. It takes real conversation data and business metrics (like sales conversion or customer satisfaction scores) and identifies what patterns in the conversations lead to better or worse outcomes. You get concrete recommendations to refine your agent's prompts, policies, or logic, leading to measurable KPI improvements.

Available on PyPI.

Use this if you are responsible for an AI agent's performance and want to move beyond guesswork to data-driven, continuous improvement based on actual customer interactions.

Not ideal if you are looking for a tool to build AI agents from scratch, as Agentune focuses on optimizing existing deployed agents.

AI Agent Optimization Customer Service Automation Conversational AI Product Management Business Analytics
Maintenance 10 / 25
Adoption 7 / 25
Maturity 24 / 25
Community 8 / 25

How are scores calculated?

Stars

36

Forks

3

Language

Python

License

Apache-2.0

Last pushed

Jan 14, 2026

Commits (30d)

0

Dependencies

16

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