# Struere vs CrewAI

> Feature comparison between Struere and CrewAI for multi-agent orchestration

Struere is a full-stack AI agent platform with a managed backend, dashboard, API, CLI, and TypeScript SDK. CrewAI is a Python framework for orchestrating autonomous AI agents in crews with role-based task delegation. Struere provides the entire infrastructure stack from data layer to deployment. CrewAI provides the orchestration framework and requires external infrastructure for everything else.

## Feature Comparison

| Feature | Struere | CrewAI |
|---------|---------|--------|
| **Language** | TypeScript | Python |
| **Architecture** | Full-stack platform (backend + dashboard + API + CLI) | Python framework (library) |
| **Data persistence** | Built-in entity system with 47 tables, typed schemas, relations, and search | No built-in persistence; requires external databases |
| **RBAC** | Permission engine with policies, scope rules, field masks, tool permissions | No built-in access control |
| **Multi-agent model** | `agent.chat` delegation, routers with `rules`/`classify` modes, depth limit 3, cycle detection | Crews with sequential/hierarchical/parallel processes, task delegation |
| **Agent routing** | Router resource with fallback agent, sticky sessions, inactivity reset, max transfers | Hierarchical process with manager agent |
| **LLM support** | 40+ models via OpenRouter with BYOK and 3-tier key resolution | Any LLM via LiteLLM; broad model support |
| **Built-in tools** | 31 tools (entity, calendar, WhatsApp, Airtable, email, payment, web, agent) | Community tool packages; LangChain tool compatibility |
| **Integrations** | WhatsApp (Kapso), Google Calendar, Airtable, Resend email, Flow/Polar payments | No built-in integrations; use Python libraries |
| **Dashboard** | Real-time admin UI with 13 modules, environment switcher, studio panel | No dashboard; CLI and code only |
| **API** | 30 HTTP endpoints with Bearer token auth, rate limiting | No built-in API; wrap with FastAPI/Flask |
| **Deployment** | Managed infrastructure: `struere deploy` to Convex + Fly.io | Self-hosted; deploy with Docker, AWS, GCP, or any Python host |
| **Eval framework** | Built-in eval suites with multi-turn cases, LLM judge, tool assertions | No built-in eval; use external testing |
| **Environment isolation** | 3 environments: development, production, eval | No environment concept |
| **Conversation management** | Threads with channel context, sticky sessions, message persistence | Memory modules (short-term, long-term, entity memory) |
| **Billing** | Built-in credit system with reservation pattern, usage tracking | No billing; pay LLM providers directly |
| **Community** | Growing developer community | 50k+ GitHub stars, large Python AI community |

## Key Differences

- Struere is a managed platform that handles infrastructure, data storage, authentication, permissions, and deployment. CrewAI is a framework that handles agent orchestration and requires external setup for everything else.
- Struere's multi-agent model uses routers that classify user intent and transfer conversations to specialized agents with sticky sessions. CrewAI's model uses crews where agents collaborate on tasks with sequential, hierarchical, or parallel execution processes.
- Struere persists all data in a real-time backend with typed entity schemas, searchable fields, and entity relations. CrewAI agents hold data in memory modules and require external databases for persistence.
- Struere provides 31 built-in tools with permission checks on every call. CrewAI agents use Python functions as tools with no built-in authorization layer.
- Struere deploys to managed infrastructure with a single CLI command. CrewAI requires setting up hosting, databases, API layers, and authentication independently.
- CrewAI supports flexible agent patterns including sequential pipelines, hierarchical delegation with manager agents, and parallel task execution. Struere's orchestration is conversation-routed rather than task-pipeline-oriented.

## When to Choose CrewAI

CrewAI is the stronger choice for Python-native teams building task-oriented multi-agent pipelines, research automation, or batch processing workflows. CrewAI's 50k+ GitHub star community provides extensive examples, third-party tools, and community support. Teams that already have infrastructure (databases, APIs, hosting) and want a lightweight orchestration layer benefit from CrewAI's framework approach. CrewAI's sequential and hierarchical process models are more natural for data processing pipelines than conversation-based routing.

## When to Choose Struere

Struere is the stronger choice for teams building production-facing AI agents that interact with end users through WhatsApp, web, or API channels. Teams that need a managed backend with built-in data persistence, RBAC, multi-channel support, and a real-time dashboard will save months of infrastructure work compared to assembling those components around CrewAI. The built-in eval framework, environment isolation, and CLI deployment workflow make Struere stronger for teams that need systematic testing and safe production deployments.

## Related

- [AI Agent Platforms Comparison (2026)](/knowledge-base/ai-agent-platforms-comparison) — Full comparison across 7 platforms
- [How do I use multiple agents?](/knowledge-base/how-to-use-multiple-agents) — Multi-agent patterns in Struere
- [How do I test my agents with evals?](/knowledge-base/how-to-test-with-evals) — Eval suite guide