Grounded Intelligence.

As agents redefine support, coding, sales, and thousands of other workflows, both inside companies and in the products they ship, the nature of engineering is fundamentally changing. Every team at a company, even in non-technical domains, is now building agents in production. But improving these systems involves reading through traces and logs, writing eval suites, and fixing prompts by hand. It doesn’t scale yet for a few reasons:

1. 01
   Agentharnessesarecomplicated.Improvinganagentrequiresnavigatingalargedesignspaceofprompts,tools,subagents,androuting,wheretherightcombinationdependsontheworkflowandenduser.
2. 02
   Thedataneededtoimproveagentsexists,butinsilos.TeamsinspectLLMtracestodiagnoseagentfailures,butothersignalslikeuserfeedback,clickstreams,andbillingpatternsrarelyfeedbackintotheagentimprovementloop.
3. 03
   Agentsdon'tlearnfromeachother.AscompaniesracetoadoptAI,theiragentshavebecomefragmentedacrossvendorsandframeworks,witheachsystemevolvingseparatelyratherthancontributingtoasharedlayerofinstitutionalmemory.

Today’s tooling is fragmented, leading to point solutions that leave AI engineering brittle and reactive at scale. That’s why we’re building Grounded Intelligence: a closed loop that intelligently turns your production signals into compounding improvements, so agent engineering becomes as disciplined as shipping software.