CrewAI
Multi-agent automation framework & studio to build and run AI crews
Open-Source Projects
Discover top open-source software, updated regularly with real-world adoption signals.
Discover top open-source software, updated regularly with real-world adoption signals.
Easily build, manage, and run autonomous AI agents
A developer‑first framework to provision, extend, and operate autonomous AI agents with GUI, toolkits, and multi‑vector DB support, deployable via cloud, Docker, or DigitalOcean.
SuperAGI is a developer‑first framework that lets you provision, spawn, and run autonomous AI agents at scale. With a web‑based GUI and an Action Console, teams can monitor, interact with, and fine‑tune agents in real time. It supports concurrent execution, allowing multiple agents to operate simultaneously without interference.
Agents can be extended through a marketplace of toolkits, connect to multiple vector databases, store memory, and operate with optimized token usage to control costs. You can configure token limits per step and enable persistent memory to let agents learn from past interactions. Built‑in performance telemetry provides insights for continuous improvement.
Deployments are flexible: use SuperAGI Cloud for instant access, run the Docker‑compose stack locally (including GPU‑enabled variants), or launch a one‑click DigitalOcean droplet. The framework supports custom fine‑tuned models and ReAct‑style workflows for complex automation. Extensive documentation, a YouTube channel, and an active Discord community help accelerate onboarding and troubleshooting.
When teams consider SuperAGI, these hosted platforms usually appear on the same shortlist.
Looking for a hosted option? These are the services engineering teams benchmark against before choosing open source.
Customer support ticket triage
Agents automatically classify, prioritize, and route tickets, reducing manual handling time.
Data enrichment pipeline
Agents fetch, summarize, and store external data into vector DBs for downstream analytics.
Automated report generation
Agents gather metrics, apply ReAct workflows, and produce formatted reports on schedule.
DevOps incident response
Agents monitor alerts, retrieve logs, and suggest remediation steps, accelerating resolution.
SuperAGI is written in Python and runs via Docker, so Python knowledge is sufficient for extending agents.
Yes, you can connect custom or fine‑tuned models through the configuration.
SuperAGI Cloud provides a quick‑start hosted environment; you can also self‑host locally or on DigitalOcean.
The framework includes controls to limit token consumption per step, helping manage API costs.
Multiple vector DBs are supported; you can configure the one that fits your stack.
Project at a glance
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