On-premises server software
Collect vast volumes of factory data with NAZARE. Turn it into analysis and action with NAVIS. Start manufacturing AI with two software platforms installed on your premises.
Explore deployment
NAZARE
Collect, store and query equipment, business-system and document data. Structure operating knowledge with ontology for analytics and AI, and send approved control commands to equipment PLCs.
NAVIS
An Agentic AI platform that answers using live machine data, operating records and knowledge. NAVIS presents a response and its evidence, then requests execution from NAZARE through MCP after manager approval.
Start with a specific need, such as identifying defect causes or detecting equipment anomalies. Build collection, storage and query capabilities for the required equipment, production and quality data while applying and validating AI. Reuse the data infrastructure across more machines and factories.
NAZARE
NAVIS
Use AI before every machine is connected. Validate analysis and responses on the first connected equipment, then expand.
Explore the details you need
Manage shared terms and relationships so different tag names do not force you to restart each analysis. AAS and MDR organize the meaning of equipment assets and their data.
Define each production cycle and compare its signals with a reference run. Find changed segments in repetitive production to prioritize quality checks and equipment inspection.
Compare pressure, temperature, current and other signals around an event. Inspect a short interval in detail or aggregate a longer period to narrow down possible causes.
Connect PLC and CNC signals with records from existing production and quality systems. Choose the fields, verify incoming values, and reuse the same data for monitoring and analysis.
Manage connected sources, storage capacity and processing status together. Use common screens and policies as the number of machines and operating tasks grows.
A pressure reading is useful when you know which machine and measurement point it belongs to. Link plants, equipment, products and signals so people can understand them and AI can reference them.
Distinguish missing, late and out-of-range values. Manage original records alongside processing criteria to improve confidence in data used by engineers and AI.
Clean values by condition and create calculated signals. Prepare equipment readings and existing system records for their intended use, reducing repetitive work before analysis.
Record why a machine stopped, not just how long. Review recurring downtime reasons and parts replacement history to identify opportunities to reduce production losses.
Operate on premises when factory data cannot leave the site. Assign equipment and functions by responsibility and separate data access from control permissions.
High-resolution signals from hundreds of machines quickly become a large history. NAZARE keeps that data on site and queries the equipment, time windows and fields needed for live use and long-term analysis.
Process-specific ML needs precise data at the moment of inference. NAZARE prepares historical training data and live signals; NAVIS combines results with site knowledge to explain findings and plan responses.
What is abnormal, what should be checked first, and what action is appropriate? Ingkle specialists capture this knowledge through interviews and tools, linking equipment, parts, signals, criteria and actions. This is manufacturing ontology.
Move from plant-wide operating states to individual machine signals. See running, waiting, stopped and alarm conditions together to reduce time spent checking machines in person.
What is abnormal, what should be checked first, and what action is appropriate? Ingkle specialists capture this knowledge through interviews and tools, linking equipment, parts, signals, criteria and actions. This is NAZARE ontology.
Explore the details you need
Connect data access, business context and model inference as tools for agent workflows.
Review and approve the target and evidence in NAVIS. NAVIS requests execution through MCP; NAZARE sends commands to connected PLCs. Track request status separately from actual outcomes.
Connect relevant material and work context as the starting point for operational agents.
Review equipment state, AI evidence, work for approval and execution results together. Five equipment demos show how data and operating knowledge connect to responses.
Explore the details you need
NAZARE connects equipment, MES, ERP and QMS data. NAVIS uses the same evidence for analysis and response. Explore how the products work with existing systems.
NAZARE separates data access by site and user. NAVIS connects the sources, tools and approvers required for each role. Explore separated operation and execution permissions across sites.
Start together
Tell us about your equipment, data and priorities to review a path from connection to operations.
