Tags: Manufacturing, Databricks, Enterprise AI, Unity AI Gateway, model routing, agentic ai transformation, GenAI Automation, AI Agent Evaluation, Databricks MLflow Evaluate, Synthetic Evaluation Dataset, LLM as a Judge, LLM Cost Optimization, RAG Evaluation, Agentic AI Observability

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Manufacturing Databricks Enterprise AI

AI Model Trust and Economics for Enterprise Agents: Measured Quality, Controlled Cost on Databricks

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Independently judged agent answers

Traceable cost per answer

41 %

Lower model spend in testing

See the eight measures, both routing designs and the full test results inside

CUSTOMER CONTEXT

The Client

A global food and beverage enterprise scaling agentic AI on Databricks asked two questions: can it trust agent answers, and can it keep their cost sustainable. KPI Partners built its AI Model Trust and Economics framework to answer both, through answer quality evaluation, cost-aware model routing and spend observability. The full case study walks through how every interaction can deliver the required quality, with the right model, at the lowest sustainable cost.

TECHNOLOGY STACK

Tools & platforms powering the solution

KPI Partners AI Model Trust and Economics framework Databricks Unity Catalog (evaluation dataset, lineage, audit logs) Unity AI Gateway Databricks AI Search (vector and hybrid search) Databricks RAG Service (REST API, Unity Catalog Functions, Model Serving Endpoints) Delta and UC Volumes ai_classify MLflow Evaluate and MLflow Tracking DeepEval scorers (via MLflow) Lakebase (PostgreSQL cache and query log) LiteLLM OpenRouter n8n workflow and action layer Azure App Service Azure AI Evaluation SDK Azure Monitor GPT-4o (judge, Architecture 2) Models in the routing pool: Llama 3.3 70B, Qwen 122B, GPT-OSS-120B, Claude Sonnet 4.5, Llama 4 Maverick

KPI Partners scores question quality, the layer almost nobody reports, so unanswerable test questions are caught before they distort the result.

Ready to Make Every AI Agent Answer Accountable?

Measure answer quality, control model costs, and trace every interaction with KPI Partners on Databricks.

Schedule a Consultation View more Case Studies

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AI Model Trust and Economics for Enterprise Agents: Measured Quality, Controlled Cost on Databricks

See the eight measures, both routing designs and the full test results inside

The Client

Tools & platforms powering the solution

Ready to Make Every AI Agent Answer Accountable?

Share this story
with your network: