Feature Comparison Matrix

A comprehensive comparison of what you get with each framework and integration approach. The columns progress from standalone frameworks on the left to full Waxell native on the right.

Legend

Symbol	Meaning
Yes	Fully supported out of the box
Partial	Partially supported or requires significant custom work
No	Not available

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Core Agent Capabilities

Feature	LangChain	LangChain + Observe	CrewAI	CrewAI + Observe	Custom Python	Custom + Observe	Waxell Native
Declarative agent definitions	No	No	Partial	Partial	No	No	Yes
Tool abstraction	Yes	Yes	Yes	Yes	Manual	Manual	Yes
Workflow orchestration	Partial	Partial	Yes	Yes	Manual	Manual	Yes
Multi-agent coordination	Partial	Partial	Yes	Yes	Manual	Manual	Yes
LLM model routing	Manual	Manual	Manual	Manual	Manual	Manual	Yes

Notes on partial support

• LangChain declarative: LangChain Expression Language (LCEL) provides composable chains, but agent definitions remain imperative.
• CrewAI declarative: Agent/Task/Crew classes are semi-declarative, but orchestration logic is still code-level.
• LangChain workflow orchestration: LangGraph adds graph-based workflows, but lacks durability and governance.

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Observability

Feature	LangChain	LangChain + Observe	CrewAI	CrewAI + Observe	Custom Python	Custom + Observe	Waxell Native
Execution run tracking	No	Yes	No	Yes	No	Yes	Yes
LLM call tracking	No	Yes	No	Yes	No	Yes	Yes
Automatic token counting	No	Yes	No	Partial	No	Partial	Yes
Step-by-step execution trail	No	Yes	No	Yes	No	Yes	Yes
Input/output capture	No	Yes	No	Yes	No	Yes	Yes
Dashboard UI	No	Yes	No	Yes	No	Yes	Yes

Notes on automatic token counting

• LangChain + Observe: The WaxellLangChainHandler callback extracts token usage from LangChain's LLMResult automatically.
• CrewAI + Observe / Custom + Observe: Token counts must be passed to ctx.record_llm_call() manually or extracted from your LLM client's response.
• Waxell Native: The LLM router tracks all token usage automatically.

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Cost Management

Feature	LangChain	LangChain + Observe	CrewAI	CrewAI + Observe	Custom Python	Custom + Observe	Waxell Native
LLM cost estimation	No	Yes	No	Yes	No	Yes	Yes
Per-model pricing (20+ models)	No	Yes	No	Yes	No	Yes	Yes
Tenant-level cost overrides	No	Yes	No	Yes	No	Yes	Yes
Budget enforcement	No	Yes	No	Yes	No	Yes	Yes
Cost-per-run visibility	No	Yes	No	Yes	No	Yes	Yes

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Governance and Policy

Feature	LangChain	LangChain + Observe	CrewAI	CrewAI + Observe	Custom Python	Custom + Observe	Waxell Native
Pre-execution policy checks	No	Yes	No	Yes	No	Yes	Yes
Budget limit policies	No	Yes	No	Yes	No	Yes	Yes
Rate limiting / throttling	No	Yes	No	Yes	No	Yes	Yes
Content filtering	No	Partial	No	Partial	No	Partial	Yes
Approval workflows	No	No	No	No	No	No	Yes
Dynamic policy management	No	No	No	No	No	No	Yes
Full governance lifecycle	No	No	No	No	No	No	Yes

Notes on content filtering

• +Observe: Policy checks can block execution based on agent name, workflow, or budget. Content-level filtering (inspecting prompts/responses) requires custom policy rules in the control plane.
• Waxell Native: The DynamicPolicyManager evaluates policies at every governance hook point, including pre-execution, mid-workflow, and post-completion.

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Durability and Infrastructure

Feature	LangChain	LangChain + Observe	CrewAI	CrewAI + Observe	Custom Python	Custom + Observe	Waxell Native
Durable workflows	No	No	No	No	No	No	Yes
Checkpoint / resume	No	No	No	No	No	No	Yes
Pause / resume (human-in-the-loop)	No	No	No	No	No	No	Yes
Multi-tenancy	No	Partial	No	Partial	No	Partial	Yes
Signal-driven execution (webhooks)	No	No	No	No	No	No	Yes
Production backends (Redis, Celery)	No	No	No	No	No	No	Yes
Audit trail with agent_trace	No	No	No	No	No	No	Yes
Generation layer (RAG, prompt versioning)	No	No	No	No	No	No	Yes

Notes on multi-tenancy

• +Observe: Runs are scoped to a tenant via the control plane API key. Data isolation is at the API level.
• Waxell Native: Full tenant isolation at the database level, with per-tenant policies, model configurations, and billing.

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Summary

The progression from left to right represents increasing levels of governance and infrastructure:

1. Standalone frameworks (LangChain, CrewAI, custom) give you agent capabilities but no governance.
2. + Waxell Observe adds observability, cost tracking, and basic policy enforcement with minimal code changes.
3. Waxell Native provides the full stack: declarative definitions, durable workflows, signal-driven execution, full governance lifecycle, and production infrastructure.

Each level delivers standalone value. See the Progressive Migration guide for how to move between them at your own pace.