Monitor, evaluate, and optimize large language model applications
LangWatch helps AI development teams ensure quality and accelerate deployment of LLM-powered applications. It automates the tedious process of prompt engineering and model optimization while providing enterprise-grade monitoring tools. The platform acts like a quality control system for AI, helping teams track performance metrics and collaborate effectively across technical and non-technical roles.
Automatically finds best prompts/models using DSPy framework
Collaborative workspace to set quality standards
Track performance across pipeline changes
30+ prebuilt or create your own quality checks
GDPR compliance & self-hosted deployment options
Combines automated prompt optimization with enterprise monitoring using Stanford's DSPy framework
Yes, drag-and-drop interface allows collaboration with domain experts
Offers self-hosted deployment and GDPR compliance with EU-based servers
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Recent data shows that LangWatch has 23.1K monthly visits (-17.1% decrease from the previous month), 42.0% bounce rate, and average 2.81 pages per visit.
Traffic is primarily driven by 6 different sources, with users from 5 countries worldwide, led by India contributing 17% of total traffic. SEO performance is shown by 5 tracked keywords, with "langwatch" being the top-performing keyword with 950 monthly searches. See below for more info.
Monthly Visits
23.1K
Pages per Visit
2.81
Bounce Rate
42.0%
Average Time on Site
37s
| SEO Keyword | Volume | CPC |
|---|---|---|
| langwatch | 950 | - |
| conversation simulation and evaluation tools | 160 | - |
| langwatch multi turn evaluation | 160 | - |
| multi turn conversations simulation tool | 160 | - |
| langwatch vs langfuse | 90 | - |
| Source | Traffic Share |
|---|---|
| Direct | 44% |
| Search | 36% |
| Social | 5% |
| Referrals | 13% |
| Paid Referrals | 1% |
| Country Name | Traffic Share |
|---|---|
 | 17% |
 | 15% |
 | 11% |
 | 7% |
 | 5% |
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