Every AI ambition, engineered to run the business.
Agents, generative AI, data science and the platforms, foundations and operations beneath them, delivered as one practice on the data platform you already run.
Overview
Most enterprise AI stalls between the pilot and production, and it stalls for an engineering reason, not a modeling one. AI Engineering is the KPI Partners practice that closes that gap: It brings agentic AI, generative AI, data science and machine learning together with the foundations, quality, security and operations that production demands.
Most journeys start with one of these. Select one to see where it lands first and which parts of the practice it draws on, a practice that covers far more than any single one of them.
Agents plan and carry out multi-step work across enterprise resource planning (ERP), customer relationship management (CRM) and data platforms. A supervisor coordinates specialist agents, and a person approves every consequential action.
Explore Agentic AIAssistants answer from contracts, policies and documents, cite their sources and respect who is asking, through retrieval-augmented generation (RAG) and document intelligence.
Explore Generative AIModels forecast demand, price, risk and failure, explain their reasoning and stay monitored in production as governed services.
Explore Data Science and MLThe Practice
Behind every agent, assistant and model sit four disciplines. Choose one, then select any capability to see what it includes.
The agents, knowledge assistants, analytics, predictive models and applications your people actually use.
The agent platform, business semantics, integrations and model engineering that every use case shares.
Measured quality, your security rules enforced inside every agent, and production operations.
AI-assisted modernization of the business intelligence (BI) and data estate that AI runs on.
Delivered natively on Databricks, Snowflake, Microsoft, AWS and Google Cloud.
See it on your platformAgents that answer questions, recommend decisions and carry out multi-step business processes. A supervisor agent coordinates role-specific specialists, and a person approves every consequential action.
Explore Agentic AIAssistants that answer from documents, policies and contracts, cite the source behind every answer and respect who is asking, through retrieval-augmented generation (RAG).
Explore Generative AIScanned contracts, invoices, forms, images and tables turned into structured, governed data, with low-confidence results routed to a reviewer instead of passing silently.
Business users ask questions in plain language across governed metrics. Accuracy is reported honestly as coverage, correctness and safe failure.
Models that forecast demand, price, risk and failure, explain their reasoning and run as monitored production services.
Explore Data Science and MLCustom AI applications, and intelligence embedded in the portals and collaboration tools people already use, with single sign-on and role-based access.
One reusable foundation for orchestration, memory, tools, identity and guardrails, so the tenth agent costs a fraction of the first.
Metrics, semantic models and ontologies that teach AI what your data means. Auto-generated context is not governed context, so we verify it.
Enterprise Context EngineSalesforce, SAP, Oracle, ServiceNow and Workday exposed to agents as governed tools through the Model Context Protocol (MCP) and agent-to-agent patterns. The agent drafts, a person approves, then the action is written back.
The right model for each task, routed for quality, latency and cost, and interchangeable across Claude, Llama, Mistral, GPT and Gemini.
Golden datasets built with your experts, automated scoring for groundedness, accuracy and hallucination, and a readiness score that gates every release.
AI run like production software: Continuous integration and delivery for prompts, agents and models, tracing of every step, cost and quality monitoring, and feedback loops that keep improving the system. Large language model operations (LLMOps) and ML operations (MLOps) included.
Every agent honors the same access rules as the data it reads: Identity through your provider, row-level and object-level security, personally identifiable information (PII) controls, guardrails and a full audit trail.
Tableau, Qlik, Oracle Analytics and Business Objects estates converted to Power BI with AI-assisted conversion and automated quality checks.
GenAI-Based BI ModernizationInformatica, Oracle, SQL Server and legacy warehouses carried to Databricks, Snowflake, Fabric or BigQuery with AI-assisted code conversion.
Data Platform MigrationGenerated documentation and automated validation of migrated outputs, so teams trust the new estate from day one.
Once modernized, the estate becomes conversational, so people ask questions in plain language instead of waiting for the next dashboard.
Why KPI Partners
No new platform to buy. We engineer with the native services of your platform, and we are plain about what we have shipped where.
SalesIQ and ProcurementIQ are available now on Databricks, and SupplyChainIQ and HRIQ follow the same reference architecture.
Our partnershipRebateIQ runs in production across more than 600 contracts, SalesIQ is delivered at two clients, and SupplyChainIQ is built on Cortex Agents.
HRIQ is being re-platformed onto Foundry and Fabric as a portable framework, and our Power BI and Fabric migration accelerators have shipped at enterprise clients.
Our partnershipRebateIQ runs on Amazon Bedrock and Amazon Textract for a North American foodservice provider, and our Databricks and Snowflake accelerators run on AWS-hosted instances.
Our Oracle to BigQuery, Snowflake to BigQuery and marketing analytics accelerators are delivered on Google Cloud.
Models sit behind one gateway, so model choice stays a business decision.
Every platform claim reflects delivered work, so plans rest on facts.
Domain-expert agents from DomainIQ Agents and governed context from the Enterprise Context Engine.
Advice, build and managed operations under one team, so accountability never changes hands.
See the Impact
Figures from KPI Partners accelerators built on this practice and running in the business.
A global specialty retail brand moved from reactive manual ordering to autonomous inventory orchestration, with a reasoning agent and stockout prediction models working across its partner store network.
A North American commercial and retail bank combined real-time ML scoring with GenAI behavioral detection and an explainable AI layer for audit and compliance.
A North American foodservice equipment and supplies provider used RebateIQ to turn unstructured rebate contracts into analytics-ready data, with real-time visibility of earned rebate revenue.
A global insurance and risk management organization replaced legacy sentiment models with large language models on Databricks, simplifying the model lifecycle for its sales teams.
A leading U.S. beverage producer gave teams a conversational assistant in Microsoft Teams for Oracle ERP inventory and supplier questions, with workflows that automate work orders.
Next Steps
Tell us the outcome you need and the platform you run. We will show you the path to production.
Talk To Our AI ExpertsGoverned, domain-expert AI agents for supply chain, procurement, finance, HR and sales, deployable on the data platform you already run.
Explore DomainIQ AgentsAssess readiness, prioritize use cases and set an architecture that fits your platform.
Enterprise AI AdvisoryMost journeys start in the KPI Partners Enterprise AI Lab, which takes a first use case from pilot to production in 90 days.
