Reflexio

The moat for AI agents isn't the model — it's what your agent learns from every interaction it handles.

Reflexio is an agent self-improvement platform. It turns every conversation your AI agent has into a learning opportunity — automatically extracting user preferences and behavioral playbook entries so your agent continuously improves itself without manual tuning.

GitHub · reflexio-client on PyPI · reflexio-ai on PyPI

Install

Pick the package that matches how you want to run Reflexio:

Managed Reflexio Enterprise (recommended for most users) — lightweight client that talks to the hosted cloud at https://www.reflexio.ai. No local server, no extra dependencies.

pip install reflexio-client

Self-hosted (open source) — full package containing the client, the FastAPI server, and the reflexio CLI. Use this when you want to run the entire Reflexio stack on your own machine.

pip install reflexio-ai

Both packages expose the same import:

from reflexio import ReflexioClient

client = ReflexioClient()  # uses REFLEXIO_API_KEY env var (managed)
# or: client = ReflexioClient(url_endpoint="http://localhost:8081")  # self-hosted

Key Features

• Never Repeat the Same Mistake — Transforms user corrections and interaction signals into improved decision-making processes — so agents adapt their behavior and avoid repeating the same mistakes.
• Lock In What Works — Persists successful strategies and workflows so your agent reuses proven paths instead of starting from scratch.
• Correct in Real Time — Retrieves personalization and operational signals to fix agent behavior live — no retraining required.
• Learn from Human Experts — Publish expert-provided ideal responses alongside agent responses — Reflexio automatically extracts actionable playbook entries from the differences.
• Personal & Global Improvements — Separates individual user preferences from system-wide agent improvements.
• AI First Self-Optimization — Agents autonomously reflect, learn, and improve — less human-in-the-loop, more compounding gains.

How It Works

Publish conversations from your agent, and Reflexio closes the self-improvement loop. Interactions flow through the pipeline to produce User Profiles (per-user preferences), Playbooks (actionable improvement signals), and Evaluation Results (success/failure assessments). Everything is organized via Requests and Sessions.

Self-Hosted (Open-Source) vs Managed Enterprise

Documentation