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TVARIT applies machine learning to foundry and metalworking operations, targeting scrap reduction and energy savings through real-time process optimization. The tech stack is cloud-native and data-heavy—Python, Spark, Flink, Kafka-adjacent tooling (Node-RED, Kepware), deployed across Azure, AWS, and GCP—reflecting a company built to ingest and process high-frequency sensor data from shop floors. Active hiring is concentrated in data and engineering (8 of 12 open roles), with senior-level dominance, suggesting they are scaling the core inference and ETL pipeline architecture rather than expanding sales.
Tech Stack 45 technologies
Core StackPython Terraform Apache Spark Apache Flink Hadoop AWS Azure Data Factory Databricks PySpark Docker Kubernetes SQL Server PostgreSQL InfluxDB MongoDB Cassandra JavaScript Azure SQL GCP Azure SQL Database Node-RED Kepware Excel DATEV SharePoint Tally Zoho Detectron2 MMDetection+15 more
What TVARIT Is Building
◆Challenges
- High-frequency industrial data
- Reducing manufacturing waste
- Scaling etl pipelines
- Real-time batch data processing
- Implementing ai in manufacturing
- Unreliable data acquisition
- Compliance with german tax requirements
- Internal and external audits
- Budget planning
- Eliminating waste and carbon emissions
▲Active Projects
- Real-time batch processing workflows
- Cloud data architecture design
- Industrial etl pipelines
- Zero waste manufacturing innovation
- Ai implementation in manufacturing
- Industry 4.0 shopfloor digitalization
- Shopfloor data acquisition and integration
- Iiot pipelines to edge and cloud
- Node-red flows for device onboarding
- Business case development for tia® platform
Hiring Activity
10 roles · 2 in 30d
Department
Seniority
Notable leadership hires: Engineering Head
Company intelligence
