How KPI Partners accelerates your journey from proof-of-concept to enterprise-scale AI - with proven IP, deep expertise, and zero wasted cycles.
Every enterprise is running a GenAI pilot right now. The demo works. Leadership is excited. Then silence. Months later, that promising prototype is still in a sandbox - nowhere near real users, real data, or real ROI. This isn't a data science problem. It's an infrastructure, integration, and expertise problem.
Most AI teams spend 70–80% of their time assembling plumbing: stitching together vector databases, model registries, governance layers, and monitoring systems. That's before a single business user sees any value.
"The bottleneck in enterprise AI isn't the model. It's everything that needs to happen before and after the model - and the combination of Databricks' platform and KPI Partners' accelerators is purpose-built to eliminate that bottleneck."
KPI Partners closes this gap by combining Databricks' unified Data Intelligence Platform with proven implementation methodology, proprietary IP, and embedded engineering teams that have done this before - across Oracle migrations, GenAI deployments, and everything in between.
KPI Partners' Databricks practice is structured around five core capability areas. Each maps directly to a Databricks platform capability, and each is backed by proprietary KPI IP that compresses delivery timelines:
Retire legacy EDW platforms - Oracle, Teradata, SQL Server, Snowflake - and migrate to a unified Lakehouse. Lower costs, faster analytics, and a single architecture for all workloads.
Cloud-native data engineering with Spark and Delta Lake. Metadata-driven ingestion, automated quality validation, and BI modernization - with less code and fewer manual handoffs.
From advanced analytics to production ML and GenAI - KPI delivers Mosaic/DBRX-based architectures, AI-assisted data engineering, and full MLOps operationalization.
End-to-end Unity Catalog implementation - RBAC, lineage, access policies, and secure data sharing across domains. Compliance becomes a configuration, not a project.
The highest-value pillar - where Databricks serves as the execution, intelligence, and orchestration layer for enterprise AI. KPI brings LLM + ML + structured/unstructured data fusion, DBRX/Mosaic architectures, and event-driven agentic workflows. This is where models think, reason, and act inside your enterprise.
KPI Partners compresses the standard 6–12 month infrastructure build to weeks - because the platform is already assembled and the accelerators are already built. Each phase delivers tangible value, not just groundwork.
KPI evaluates your existing data estate - Oracle, EDW, Informatica pipelines, or Snowflake workloads - and produces a Lakehouse migration blueprint using the Data Platform Accelerator, BI Platform Migration Accelerator, and GenAI Migrator.
🏗️ Modernize Data Platforms pillarDeploy metadata-driven ingestion and transformation frameworks. Activate the Data Quality Validator for Databricks. Your data is flowing, validated, and fresh - ready for AI workloads.
⚙️ Scale Data Engineering pillarUnity Catalog enablement across all data and AI assets - automated lineage, RBAC, AI Gateway configuration for PII filtering and cost controls. Compliance is built in, not bolted on.
🛡️ Govern & Share Data pillarBuild and evaluate RAG pipelines, ML models, or GenAI applications using Mosaic AI. KPI's CodeGPT and DataGPT accelerators embed AI productivity into your engineering and analytics teams immediately.
🧠 Enable AI & ML at Scale pillarDeploy intelligent agents - Conversational Analytics Engines, Intelligent Data Quality Agents - into enterprise workflows. Activate Lakehouse Monitoring. Go from prototype to production AI that generates measurable business impact.
🤖 Build Intelligent AI Experiences pillarTraditional integrators start by building the platform from scratch. KPI Partners arrives with battle-tested accelerators - GenAI Migrator, Data Platform Accelerator, BI Platform Migration Accelerator, Data Products Accelerator, and Unity Catalog Enablement - that eliminate 60–70% of the build time. You're not paying for KPI to figure it out. You're paying for what they've already figured out.
KPI Partners measures success by business outcomes, not delivery milestones. Here's what organizations typically achieve across each capability area:
| Capability Area | Customer Outcomes |
|---|---|
| Lakehouse Modernization | ✓ Legacy EDW retired ✓ Lower license costs ✓ Faster analytics at scale ✓ Simplified architecture |
| Data Engineering | ✓ Faster pipeline development ✓ Improved data freshness ✓ Higher analytics adoption ✓ Reduced maintenance |
| AI & ML at Scale | ✓ Faster AI to production ✓ Scalable ML pipelines ✓ Increased team productivity ✓ Reduced time-to-value |
| Data Governance | ✓ Improved data trust ✓ Secure self-service access ✓ Reduced compliance risk |
| Intelligent AI Experiences | ✓ AI embedded in workflows ✓ Higher team productivity ✓ Measurable business impact ✓ Beyond dashboards |
Every platform and partner decision faces skepticism. Here are the objections KPI Partners hears most - and the direct answers:
The organizations winning with GenAI aren't those with the most sophisticated models - they're the ones who got to production first, learned from real users, and iterated. Every month spent in infrastructure purgatory is a month your competitors are generating insights, automating workflows, and embedding AI into decisions you're still making manually.
KPI Partners and Databricks together don't promise to make AI easy. What they deliver is a dramatically compressed path - from fragmented legacy stack to unified Lakehouse, from pilot to production GenAI, from static dashboards to intelligent agents that act. Proven IP. Real engineering depth. Measurable outcomes.
"The question for enterprise AI in 2026 isn't whether to build with GenAI. It's whether you can afford to keep building the plumbing yourself - and whether your implementation partner has already built it for you."