Clay reconciles 99.5% of its AI spend with LangSmith observability
LangChain · x · 2026-08-31
LangChain shares a customer case: Clay, a sales/marketing automation company, reconciles 99.5% of its AI spend using LangSmith. Head of AI Jeff Barg explains why cost observability only clicked once LangSmith was in place, and how the tool finally brought clarity to AI expenditure.
Related event: Clay Reconciles 99.5% of AI Spend with LangSmith Trace-Level Cost Tracking(3 posts)→
More from coding & agent
- DIY visual diff tool using GitHub Artifacts and pure JavaScript to save costs — zeeg · 2026-09-01
- Dev shares a dirt-cheap approach to visual diffs — zeeg · 2026-09-01
- Grok Bot automates Shopify updates and supplier coordination — billyjhowell · 2026-09-01
- Grok Bot automates lost deal analysis by mining call and email threads — lennysan · 2026-09-01
- Design pattern: immutable agent artifact revisions behind a stable review URL — RocketSeven · 2026-09-01
- Building a long-term memory benchmark for agents: what to add? — True_Mongoose_7073 · 2026-09-01