back_office_ops · ecommerce · workflow
Karrot builds a centralized GenAI platform with LLM Router, Prompt Studio, and KarrotChat
Teams at Karrot were independently provisioning AI API accounts and keys, creating management overhead, uneven rate-limit availability, and fragmented cost visibility. Every AI feature iteration also required engineering support, preventing rapid experimentation.
How it works
Common implementation structure
How this type of workflow is generally built, generalized across documented cases — not tied to any one vendor's stack. Click any stage to read what happens there. Specific products that implement these stages appear in “Tools commonly seen” below.
Stage 1 · Route all AI calls via gateway
Karrot built LLM Router to funnel all AI API calls through a single gateway, with API keys and accounts managed centrally.
Tools used
LLM RouterPrompt StudioKarrotChatOpenAIAnthropicGooglevLLMOpenAI SDKBigQuery
Outcome
Karrot eliminated provisioning overhead, unified cost visibility, and enabled non-engineers to build AI features independently. Internal Agents like DANA now let any team member perform sophisticated data analysis without SQL expertise, measurably boosting productivity across teams.
Results
Volumehundreds of GenAI use cases
Grounding & classification
Source type: technical build writeup
30 fields verified against source quotes, 1 dropped as unverifiable.
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