Primero provides an enterprise AI operating layer that connects legacy systems, structures business context, and powers auditable AI workflows, agents, and internal apps. The platform includes ontology management, natural language business intelligence, and configurable agents that escalate to human reviewers with full context. It is deployed across financial services, insurance, CPG, manufacturing, and retail, enabling traceable decisions with inputs, approvals, and sign-offs recorded for every run.
Funding
Funding not disclosed
Founders
Product
Problem
Enterprises struggle to apply AI across scattered legacy systems, spreadsheets, and internal APIs, leaving teams without a unified view or reliable context for decision-making. Without a coherent operational layer, AI workflows lack traceability and governance, making them difficult to deploy, audit, and improve at scale.
Solution
Primero provides an operating layer for enterprise AI that connects systems, structures business context, and powers apps, agents, and workflows in production. The platform maps business objects and relationships into an ontology, turns natural language questions into governed BI dashboards, and runs agents that read from systems of record, apply established rules, and escalate exceptions to human reviewers with attached context. Internal apps give teams queues, case views, and approval controls so they can work alongside agents. Every run logs inputs, approvals, and sign-offs, while model calls remain traceable to their prompts, responses, and token costs, making the entire system audit-ready.
Target Audience
Primero serves enterprises in financial services, insurance, consumer packaged goods, manufacturing, and retail that need auditable, AI-driven workflows integrated with their existing systems and subject to regulatory or internal oversight.
Features
- Ontology module with canonical definitions, identity resolution across systems, and governance rules for approved metrics and sensitive data
- Business Intelligence that compiles natural language queries into governed reports with every figure traceable to its source table
- Agents that read from systems of record, apply configured rules, and escalate to reviewers with full context attached
- Internal apps with queues, case views, approval controls, and audit records for team-in-the-loop workflows
- Auditable workflows that log every input, approval, and sign-off, as well as traceable model calls with prompt, response, and token cost details
- Industry-specific configurations for CPG deduction recovery, insurance claims evaluation, financial services credit review, manufacturing spare parts, and retail supplier payments