Machine Learning · head to head
JMP vs Langwatch

JMP
Machine Learning
Desktop statistical and design of experiments software from a SAS subsidiary
- From
- Free
- Rated
- -

Langwatch
Machine Learning
LLM engineering platform for testing and evaluating AI agents in production
- From
- Free
- Rated
- -
The short version
- Each has a real cost: JMP it is a desktop application holding the working table in memory, so a data set that outgrows the workstation has no in-place upgrade path, only a move to a different tool and a different skill set.; Langwatch free plan limited to 50k events per month, restricting larger deployments
- They diverge on capability: JMP covers Custom design of experiments, Langwatch covers Agent simulation testing.
- Prices and features above were last checked on 30 August 2026.
Where they differ
Only the attributes on which JMP and Langwatch actually diverge.
Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated), category (Machine Learning).
What each one covers
Drawn from each product's published feature list. An absence here means we hold no record of it - not that the product lacks it.
Only in JMP
- Custom design of experiments
- Linked interactive graphics
- Analysis platforms
- Quality and process tools
- Graph Builder
- JSL scripting
- Scoring code export
- Predictive modelling in JMP Pro
Only in Langwatch
- Agent simulation testing
- LLM evaluation
- OpenTelemetry tracing
- Langy AI Engineer
- Governance controls
- Multiple deployment options
- Framework support
What people use each for
The jobs each tool is most often brought in to do.
JMP
- Planning a physical experiment where each run is expensive, and the question is which twelve runs to perform rather than how to model data you already havenot Langwatch
- Process capability and control chart work in a manufacturing quality function that has to produce evidence for a customer or regulatornot Langwatch
- Exploratory analysis by an engineer or scientist who will not write code but needs more than a spreadsheetnot Langwatch
- Semiconductor, chemical and pharmaceutical development groups where JMP is already the shared language for reporting resultsnot Langwatch
Langwatch
- Continuous testing of AI agents before production deploymentnot JMP
- Automated test creation from product requirementsnot JMP
- LLM response quality evaluation and scoringnot JMP
- Production agent monitoring and cost trackingnot JMP
- Governance and access control for AI systemsnot JMP
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
JMP
- It is a desktop application holding the working table in memory, so a data set that outgrows the workstation has no in-place upgrade path, only a move to a different tool and a different skill set.
- There is no Linux build and no server edition for running analyses, so JMP cannot sit in a scheduled pipeline the way an R or Python script can, and recurring reports depend on a named person running them on a laptop.
- The predictive modelling capability most buyers mean when they call this machine learning software is in JMP Pro, a separate and more expensive licence, so the base product's price is not the price of the thing being evaluated.
- JSL is proprietary to JMP, so the scripts, add-ins and automation a group accumulates over a decade do not port anywhere and become sunk cost the moment anyone questions the renewal.
- Deployment ends at exported scoring code with no registry, monitoring or retraining, so a model that runs in production is maintained by another team in another language and steadily diverges from the version the analyst still has open.
Langwatch
- Free plan limited to 50k events per month, restricting larger deployments
- Pricing in EUR may complicate budgeting for US-based teams
- Usage-based overage model can create unpredictable costs
- Self-hosted option requires DevOps expertise
Pricing, plan by plan
JMP
Free- TrialFree
- 30-day trial
- Full features
- JMP$1785/year
- Core JMP
- Standard features
Langwatch
Free- DeveloperFree
- 50k events per month
- 14-day data access
- 2 users
- Growth$29/month
- 200k events per month included
- 5 EUR per 100k additional events
- 30-day data retention
- Enterprise$undefined/custom
- Custom event limits
- Hybrid, self-hosted or on-premises deployment
- Custom SSO and RBAC
Which should you pick?
Choose JMP if
- You need custom design of experiments.
- You want to start without paying.
- You work on Mac, Windows.
- You also want linked interactive graphics.
Choose Langwatch if
- You need agent simulation testing.
- You want to start without paying.
- You work on Web, Docker, Kubernetes.
- You also want llm evaluation.
Questions people ask
- Is JMP or Langwatch better?
- Neither clearly leads. JMP starts at Free and Langwatch at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, JMP or Langwatch?
- JMP starts at Free and Langwatch at Free.
- Does JMP or Langwatch run on more platforms?
- JMP runs on Mac, Windows. Langwatch runs on Web, Docker, Kubernetes.
- Can I use JMP for free?
- Both have a free tier, so you can try either at no cost before committing.
- What is JMP best used for?
- JMP is most often used for planning a physical experiment where each run is expensive, and the question is which twelve runs to perform rather than how to model data you already have, process capability and control chart work in a manufacturing quality function that has to produce evidence for a customer or regulator, exploratory analysis by an engineer or scientist who will not write code but needs more than a spreadsheet, semiconductor, chemical and pharmaceutical development groups where jmp is already the shared language for reporting results. Of those, planning a physical experiment where each run is expensive, and the question is which twelve runs to perform rather than how to model data you already have and process capability and control chart work in a manufacturing quality function that has to produce evidence for a customer or regulator are not what Langwatch is typically brought in for.
- What can JMP do that Langwatch cannot?
- JMP covers Custom design of experiments, Linked interactive graphics, Analysis platforms, Quality and process tools. Langwatch covers Agent simulation testing, LLM evaluation, OpenTelemetry tracing, Langy AI Engineer.
Answered from the vendors’ own pages
JMP: Is JMP the same thing as SAS?
No. JMP is a separate desktop product from a SAS subsidiary, with its own interface, its own scripting language and its own licence. Knowing SAS does not transfer to it beyond the statistics.
Langwatch: Is there a permanent free tier?
Yes, Langwatch's Developer plan is free forever with 50k events per month, 14-day data access, 2 users, and no credit card required. It is specifically designed for individual developers prototyping AI applications.
SourceJMP: Do I need JMP Pro?
If you want cross validation, penalised regression, boosted trees or neural networks, yes. The base edition covers classical statistics, graphics and design of experiments well and stops short of predictive modelling.
Langwatch: What is Langy and how does it save time?
Langy is an AI-powered tool that automates test creation. It converts product requirements into test scenarios, runs simulations, scores results, and generates pull requests with fixes in a median of 14 minutes.
SourceJMP: Does it run on Linux?
No. Windows and macOS only, as an installed application.
Langwatch: What frameworks does Langwatch support?
Langwatch works with LangGraph, LangChain, CrewAI, OpenAI Agents, AWS Bedrock, Azure OpenAI, Vertex AI, and other major LLM frameworks and platforms.
SourceJMP: Can I put a JMP model into production?
Only by exporting the scoring formula as SQL, C, Python or similar and running it in another system. JMP itself does not serve, monitor or retrain models.
JMP: Who actually uses it?
Process and quality engineers, and scientists in R&D, particularly in semiconductor, chemicals, pharmaceutical and medical device work. It is not usually chosen by data engineering or platform teams.
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