SwiftTune vs LangSmith
LangSmith is the best place to watch a LangChain application. SwiftTune is a different application.
If your agent is built on LangChain or LangGraph, nothing traces it as well as LangSmith does, and this page will not pretend otherwise. SwiftTune is the other choice: the flow is a validated graph on a canvas instead of a codebase, and it deploys to the Cloudflare account you already own.
LangSmith: LangChain’s tracing, evaluation and prompt platform, with LangGraph Platform deploying and running the agents it traces.
Free tier, no card. Bring your own Cloudflare account.
SwiftTune and LangSmith, question by question
The same nine questions asked of both products. Three of the answers in our column are not a yes, and they are not a yes on any of these pages.
| Capability | SwiftTune | LangSmith |
|---|---|---|
| Visual builder that produces the deployed application | Yes Blocks on a canvas. The graph the canvas validates is the graph the runtime versions and deploys. | Partly LangGraph Studio draws and debugs the graph, and the graph is still authored in code. The picture follows the repository. |
| Runs the application itself | Yes The platform runs the flow, so the thing reporting on a deployment is the thing that served it. | Yes LangGraph Platform deploys and runs agents, so the platform tracing the application can also be the one serving it. |
| Deploys into a Cloudflare account you own | Yes Flows deploy into the Cloudflare account you bring. Infrastructure stays billed to you at Cloudflare’s rates. | No Their cloud, or a self-hosted install you operate. Not a deployment into a Cloudflare account you already own. |
| Prompt management for people who do not deploy | Partly A prompt is a field on a block, versioned with the flow that ships it. There is no approval queue for the wording on its own. | Partly The prompt hub versions and shares prompts. Picking up an edit is still something the application has to do. |
| Evaluation of prompts and outputs | Yes Evals clusters production traffic, builds eval sets from it, and scores a version against the one before it. | Yes Datasets, evaluators, experiments and annotation queues, with tracing feeding them directly. |
| Retrieval quality monitoring | Yes Retrieval Monitor reports recall@K, precision, MRR and NDCG per query cluster, continuously. | Partly Retrieval is evaluated by writing an evaluator. Recall and drift over query clusters are not a standing view. |
| Cost attribution by feature, user and prompt | Yes Cost Attribution breaks spend down by feature, user, prompt template and provider. | Partly Token counts and cost land on traces. Attribution by feature or prompt template is a query over them. |
| Open source or self-hostable | No Not open source, and there is no build to run on your own hardware. Your flows run on your Cloudflare account; the control plane is ours. | Partly LangChain and LangGraph are open source, so the framework outlives the vendor. LangSmith itself is commercial, with a self-hosted tier. |
| General-purpose connectors beyond AI services | Partly Cloudflare services, any MCP server and plain HTTP. Not a catalogue of SaaS connectors. | Partly A very large integration ecosystem through LangChain, aimed at AI applications rather than at SaaS automation. |
The LangSmith column was read from their public documentation on 4 September 2026. Both products change. Check it against the source before you decide. LangSmith documentation.
Where LangSmith is better
Three things they do that we do not, or do not do as well. If one of them is the reason you are here, stay where you are.
Nothing traces a LangChain application better
Every chain, tool call and retry lands in the trace with the framework’s own vocabulary on it. If the application is already built on LangChain or LangGraph, that fit is not something a competitor argues away.
The framework is open source, so the choice is reversible
LangChain and LangGraph outlive any vendor decision, and the prompt hub and the ecosystem around them are larger than anything here. Leaving SwiftTune means rebuilding the flow somewhere else.
Code is the right medium for some teams
A graph is a constraint: it makes the wiring checkable and the branching explicit, and it is a worse fit than a repository for logic that wants to be a function. Choose the medium the work actually is.
Stay on LangSmith if the application is LangChain or LangGraph and you want the tracing that was built for it.
Where SwiftTune is better
The other half, held to the same standard: each one is a capability in the product today, not a line on a roadmap.
The flow is checkable before it runs
Unknown blocks, mismatched ports and cycles fail on the canvas rather than at run time, because the validator drawing the flow is the one the API versions it with.
Your Cloudflare account, your rates, your jurisdiction
Flows deploy into the account you bring, with D1 and R2 created under the EU jurisdiction. Infrastructure stays billed to you by Cloudflare rather than resold.
Retrieval and cost are surfaces, not evaluators you write
Recall@K, precision, MRR and NDCG per query cluster, and spend split by feature, user, prompt template and provider. Both are on from the tier that bundles them.
Come here if you would rather compose the flow than write it, and run it on Cloudflare’s edge under your own account.
Moving from LangSmith
This is the largest of the five moves, because the application itself changes medium. Do it on one flow, not on the whole system.
What does not come across: LangChain-specific code, custom evaluators written against their SDK, and anything in the prompt hub. A flow that depends on the framework’s abstractions is a rewrite, not an import.
Check both columns before you believe either
Everything this page claims about our side is stated somewhere it can be held against us.
Rebuild one flow and compare it on live traffic
The free tier runs one deployment indefinitely, which is exactly enough to answer whether the canvas suits the work.
Free tier, no card. Bring your own Cloudflare account.