We Make Your Most Complex
Process Intelligent.
We understand the problem. Design the solution. Build it on ARPIA — fast, because the platform is already built. You run it. Then you scale.
Organizations Have AI. Almost None Have AI That Runs in Production.
Most enterprises have experimented with AI. A predictive model here. A generative tool there. A chatbot for customer service. Each initiative solves a local problem — but none connect, build on each other, or produce governed outputs.
The result is perpetual pilot mode. Smart teams. Real investment. No production.
The bottleneck is not AI capability. It is architecture. Organizations lack the orchestration infrastructure to coordinate different AI types, manage data flows, maintain quality at each step, and produce auditable, governed results.
That infrastructure is ARPIA. And we build your use case on top of it.
Four Steps from Problem
to Production
Not a framework. Not a methodology deck. What actually happens when we work together.
We Diagnose the Real Problem
Not "how do you use AI" — but "what is the most complex process in your organization that depends on human judgment, has fragmented data, and would create measurable value if automated?" We map your data landscape, your current bottlenecks, and the actual decision flow. This takes one to two weeks.
We Design the Intelligence Pipeline
Which data sources need to reflect into ARPIA? What does the knowledge ontology look like for your domain? Which AI types — ML, Generative AI, Agentic — handle which steps? What does governance need to produce for your regulatory context? We design the pipeline before writing a line of code.
We Build It. Fast.
The platform is already built — seven years of production development. We are not starting from scratch. You get a governed intelligence pipeline built on proven orchestration infrastructure in 30 to 90 days. Not six to twelve months. The infrastructure exists. We build your use case on it.
You Run It. Then You Scale.
You own the production system. Then you scale it. The platform is horizontal — the same infrastructure that runs your first use case runs your next ten. Each new pipeline is faster to build because the data layer and ontology already exist. The platform's value compounds with every use case you add.
Built Once. Runs Everything.
Every use case we build sits on ARPIA's four-layer intelligence infrastructure. This is why we can go from problem to production in 30-90 days — the foundation is already there.
Data Reflection
We create an AI-optimized mirror of your production data — a faithful digital twin that gives AI workers full access to your operational reality without exposing or loading your live systems. Every data element carries provenance, lineage, and governance metadata from the moment it enters ARPIA.
Knowledge Ontology
We build a living knowledge graph that maps how your data entities relate to each other in business context — not just rows and columns, but meaning. Customers, products, transactions, contracts, policies — structured so AI workers can reason about relationships, not just process records.
Reasoning Flows
The pipeline design layer. We compose ML workers, Generative AI workers, and Agentic AI workers into governed, sequential pipelines — each step receiving validated inputs and producing structured outputs. Every pipeline is reproducible, composable, and auditable by design.
Governance & Traceability
Every variable analyzed, model selected, agent decision made, and action activated is logged in an immutable audit trail. Governance is structural — a natural byproduct of how pipelines operate, not documentation added afterward. Aligned with ISO 42001 and SOC 2 Type 2.
From Raw Data to Activated Strategy
in 13 Minutes.
A production deployment for a financial services organization. A portfolio collections challenge that previously required days of analyst work and produced strategies that were outdated before they were activated. Here is what ARPIA built.
Intelligent Scoring
ML workers perform comprehensive statistical analysis across portfolio variables. Generative AI designs multiple competing scoring methodologies, executes each against production data, and selects the optimal approach through objective quantitative evaluation — no human intervention.
Autonomous Strategy Design
Five concurrent autonomous agents decompose the strategy problem into sub-tasks, reason through trade-offs, and produce a complete operational strategy: customer segmentation, channel assignments, contact schedules, and escalation rules.
Executive Reporting
Two reports generated in parallel. A business stakeholder report with interactive visualizations. A governance and traceability report documenting the complete decision chain for compliance — every model evaluated, every agent decision made, every variable analyzed.
Operational Activation
The strategy is persisted directly into the enterprise ERP. Execution workflows are activated. All artifacts are associated with the decision record. The gap between AI intelligence and operational action is measured in seconds, not days.
This is not a demonstration. This is a production pipeline processing real enterprise data for a real organization. The same architecture — Data Reflection, Knowledge Ontology, Reasoning Flows, Governance — applies to any complex enterprise process.
Read the Full Technical Whitepaper →One Intelligence Layer.
Unlimited Use Cases.
ARPIA is not a collections platform. Not a risk engine. Not a pricing tool. It is the intelligence layer that makes any complex enterprise process autonomous, governed, and measurably better.
The same data layer. The same ontology. The same orchestration engine. Each new use case is faster to build than the last.
Seven Years Built.
Level 6 of 7 Deployed.
ARPIA operates at Level 6 of 7 on established AI maturity frameworks published by McKinsey, Gartner, and the OECD — combining ML, Generative AI, Agentic AI, and formal governance in production. Industry research indicates fewer than 10% of organizations have deployed AI at this maturity level.
Deployed in production enterprise environments across Latin America. Bootstrap funded. Revenue backed. Built to solve real problems, not to raise valuations.
What Is Your Most Complex Process?
Start with one conversation. We will tell you honestly whether ARPIA can solve it, what the pipeline would look like, and what production deployment would actually require.