Built for manufacturing. Not adapted from IT.

ROI tracking, value narratives, and executive dashboards that translate AI outputs into the language of business. Counterfactual analysis answers: "What would have happened if we hadn't intervened?"

The interface layer where AI meets human judgment. ARIA, our natural-language copilot, lets operators and executives query the entire platform conversationally. No SQL. No clicks. Just questions.

35+ AI agents operating in autonomous loops. Each agent owns a domain (RUL prediction, anomaly detection, quality control) and runs independently while coordinating through the multi-agent orchestrator.

47 capabilities spanning knowledge representation, learning, context retrieval, and entity resolution. The knowledge graph captures relationships between equipment, failure modes, and interventions, learning from every event.

28+ trained ML models with a dynamic model registry that automatically selects the best-performing model for each prediction task. Cross-validated, hyperparameter-tuned, with quality gates that reject underperforming models.

Kafka-powered event streaming with JSON Schema validation for every message type. REST APIs with JWT authentication, rate limiting, and role-based access control. Enterprise connectors for MES, ERP, and CMMS systems.

TimescaleDB for time-series sensor data at 1-minute resolution. PostgreSQL for operational tables. Neo4j for the knowledge graph. Redis for caching with sub-millisecond response. pgvector for semantic search embeddings.

Native protocol support for OPC-UA, MQTT, and Modbus: the languages your equipment already speaks. Edge gateway handles protocol translation, buffering, and local inference for latency-sensitive decisions.