CrewAI is one of the most popular ways to build multi-agent AI systems in Python — role-based "crews" of agents that collaborate on a task, plus event-driven "Flows" for more deterministic control. With 55,000+ GitHub stars, it's often the first framework developers reach for. But it's not the only option, and depending on what you're building — a TypeScript app, a production-grade agent runtime, or a genuinely parallel multi-agent system — one of its alternatives might fit better. Here's an honest look at four real ones.
The short version
| Tool | Language | Best for | Pricing |
|---|---|---|---|
| CrewAI | Python | Fast multi-agent prototyping | Free framework, paid AMP Suite on request |
| Mastra | TypeScript | Node.js/TS teams wanting memory+RAG+evals built in | Free core, paid cloud tiers |
| Agno | Python | Running agents in production across multiple frameworks | Free core, $150/mo hosted |
| Timbal AI | N/A (platform) | Enterprise agents needing governance + reliability | Free solo, ~€25/mo/seat teams |
| Mozaik | Node.js | Truly parallel, event-driven agent coordination | Free, open source |
CrewAI, for context
CrewAI is a Python framework for role-based multi-agent teams: Crews plus event-driven Flows, available from an MIT-licensed open-source core up to an enterprise suite. It's the fastest way to prototype a multi-agent system in Python, backed by a huge community.
Pricing: The framework itself and the control plane are free; the AMP enterprise suite is priced on request.
Where people look elsewhere: Its high-level abstractions can hide what agents are actually doing under the hood, and it carries a fairly heavy dependency footprint.
Mastra — if your stack is TypeScript
Mastra is a TypeScript framework for AI agents and workflows: typed tools, graph orchestration, memory, RAG, and 90+ model providers, all built in. If your team lives in Node.js and doesn't want to bring Python into the stack just for agents, this is the most complete option.
Pricing: Apache 2.0 core is free; the cloud has a free Starter tier with paid Teams tiers, and some enterprise features are separately licensed for production use.
Where it falls short: The API has seen churn between releases, and the dual-licensing model is worth checking carefully before you ship to production.
Agno — for running agents in production, not just building them
Agno is an open-source Python framework and runtime that gives agents memory, tools, and access to 30+ model providers through one API, plus a control panel called AgentOS to actually run them in production. Notably, AgentOS can run agents built on Agno itself, Claude Agent SDK, LangGraph, or DSPy on a single runtime — it's less about replacing your framework choice and more about operating whatever you already picked.
Pricing: The open-source framework and local control plane are free. Pro is $150/month (1 connection, 4 seats, plus $30/mo per extra seat and $95/mo per extra connection), with custom Enterprise pricing for SSO/RBAC/self-hosting.
Where it falls short: It's Python-only, so JS/TS teams will need to look elsewhere, the space is crowded and fast-moving, and the managed AgentOS jumps straight to $150/month.
Timbal AI — for enterprise reliability and governance
Timbal AI is a toolkit for building AI "employees" that actually finish a job reliably, instead of a chatbot that just talks — helping companies wire up agents that look things up, take real actions in other systems, and behave consistently every time. Its Action Control Engine (ACE) is built specifically for consistent agent behavior in production, and it ships 100+ native integrations (SAP, Salesforce, Slack, Teams, Stripe) with flexible deployment — cloud, VPC, or fully on-premises.
Pricing: Free for individual use; team plans start around €25/month per seat, with quote-based enterprise pricing for sovereign hosting, SLAs, and high volume.
Where it falls short: It's a proprietary hosted platform — only parts of the framework are open source — the "100+ integrations" figure isn't independently verified, and enterprise pricing being quote-based makes it harder to budget for upfront.
Mozaik — for genuinely parallel agent coordination
Mozaik is a free, open-source toolkit for making several AI agents work together at the same time on a shared task, reacting to each other's progress in real time instead of waiting in a rigid, one-at-a-time pipeline. That's a real architectural difference from CrewAI's more sequential crew model — Mozaik is event-driven and built for concurrent, emergent teamwork, works with OpenAI, Anthropic, Gemini, and DeepSeek, and is MIT-licensed with no paid tier at all.
Pricing: Completely free, MIT license, self-hosted on Node.js.
Where it falls short: Community and documentation are still limited (114 GitHub stars), an event-driven architecture is harder to debug than an explicit graph, and it's less proven in production than CrewAI or LangGraph.
Which one should you actually pick?
Stick with CrewAI if you're prototyping in Python and want the biggest community to lean on. Switch to Mastra if your team is TypeScript-first. Reach for Agno if you want a runtime that can operate agents built on several different frameworks, not just its own. Pick Timbal AI if governance, reliability, and enterprise integrations matter more than raw framework popularity. And try Mozaik specifically if your agents genuinely need to work in parallel rather than take turns — just go in knowing it's the least battle-tested option here.