Socradata is the intelligence layer on top of your ERP and WMS — transforming operational data into real-time, predictive decisions. Not dashboards. Not POCs. Production-grade AI embedded in your workflows.
AI embedded in workflows — recommendations, scenario simulation, autonomous alerts
Forecasting, anomaly detection, predictive risk modeling, MLOps
Operational KPI monitoring, real-time alerts, governance dashboards
Organizations running Infor, SAP, and Oracle generate millions of operational data points every day. Most of that data is locked in dashboards that inform — but don't decide.
The gap between what your ERP knows and what your operations do is precisely where write-offs accumulate, forecasts fail, and efficiency erodes.
"KPIs before APIs." — Socradata's core operating principle
Production AI for the enterprise decisions that matter most.
Replace rules-based ERP forecasting with ML ensemble models that learn from demand signals, seasonality, external variables, and supplier history — deployed directly into your operational workflows.
AI-driven optimization across picking routes, labor forecasting, throughput prediction, and real-time anomaly detection — integrated with Infor WMS and comparable platforms without disrupting operations.
Control tower architecture with predictive risk scoring across suppliers, logistics nodes, and inventory positions. Real-time alerts replace retrospective reporting — so decisions happen before the disruption, not after.
Natural language query interfaces, embedded AI agents, and decision-support bots deployed on top of your ERP, WMS, and supply chain platforms. Beyond the chatbot — AI that reads operational state and acts.
Our operating model is built around one principle: every engagement ends in production deployment tied to measurable KPIs. No dashboards without decisions. No AI without accountability.
Operational visibility, KPI instrumentation, and governance foundations — the baseline for every AI initiative.
Production ML models built, validated, and deployed into your data environment — not your sandbox.
AI embedded directly in operational workflows — recommendations, copilots, and autonomous actions.
2-week data & process assessment. Gap analysis. KPI definition.
6-week scoped deployment tied to a measurable production KPI.
Full MLOps, integration, and workflow embedding. No POC theater.
Continuous model monitoring, retraining, and capability expansion.
Real results from production AI deployments. Engagement details available under NDA.
Deployed a predictive AI layer on top of an existing ERP, identifying at-risk SKUs 60 days in advance. The model flagged $50M+ in annual write-off exposure within 18 months of production deployment.
End-to-end AI optimization across picking, labor forecasting, and anomaly detection integrated with an Infor WMS environment. 35% efficiency gain measured over 12-month baseline comparison.
Replaced a rules-based ERP forecasting module with an ML ensemble incorporating external signals. Reduced MAPE by 15 percentage points, directly improving working capital and procurement efficiency.
Socradata is not a replacement for your ERP or WMS. It is the intelligence layer that makes them dramatically more powerful — working with your existing investment, not against it.
Deep expertise in Infor WMS, Infor Nexus, and Infor M3. Socradata is positioned as the AI extension layer for Infor's enterprise customer base — bridging data silos and adding ML capabilities the platform does not natively provide.
Production integrations with SAP S/4HANA, SAP EWM, and SAP IBP. ML models deployed alongside SAP's native forecasting engine, replacing or augmenting rules-based logic with data-driven alternatives.
Operational AI deployed on top of Oracle SCM Cloud and Oracle WMS — including demand sensing, inventory optimization, and supply chain control tower capabilities.
Socradata was founded on the thesis that AI for enterprise operations requires both deep technical capability and genuine domain knowledge. Most AI firms have one. We built an organization that has both.
Sergio has over 20 years of experience deploying AI and advanced analytics in enterprise environments across LATAM, North America, and the Middle East. He holds a PhD in AI and Sustainable Development from IAE Business School (Universidad Austral), an MBA from NYU Stern School of Business, and a Master's in Business Analytics from Stevens Institute of Technology.
Prior to founding Socradata, Sergio led data science and digital transformation initiatives across retail, pharma, logistics, and public sector organizations. He speaks and teaches globally — including as Adjunct Professor at New York University, where he teaches Intelligent Automation.
No deployment begins until success metrics are defined and baselined. Governance is not overhead — it is the precondition for ROI to exist.
We do not build proofs of concept that stall. Every engagement is scoped and governed for production deployment from day one.
AI that does not integrate into your ERP, WMS, and workflow stack is not operational AI — it is an expensive science project.
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The most common failure mode in enterprise AI is deploying before defining success. The framework that prevents it, with implementation templates.
Natural language interfaces on warehouse management systems are no longer theoretical. The architecture decisions that determine whether they reach production.
The NYU–IAE Summit brought together academia, government, and industry to address how AI and institutional design shape the future of work across Latin America. Socradata served as strategic orchestrator.
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Implementation stories, frameworks, and decision intelligence case studies.
Whether you are evaluating AI for your supply chain, building a business case for ERP intelligence, or looking for a strategic partner to close a client — let's start with a diagnostic.
2-week assessment of your data environment and AI opportunity map
Request a diagnostic →Infor, SAP, or Oracle channel partners — explore the subcontractor model
Explore partnership →Keynotes, executive workshops, and board-level AI strategy sessions
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