Products
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 + NAVIS
Collect PLC signals and MES, ERP and QMS records
Store and query by product, lot and time
Combine machine condition with production and inspection results
Route approved equipment control through NAZARE
NAZARE
NAZARE collects selected fields from existing systems and stores them with equipment data. Query by product, lot and production time to examine process conditions alongside inspection results.
Explore the product capability
NAVIS
NAVIS uses NAZARE signals and site knowledge together with connected operational records to propose likely causes and response steps. Use existing systems for production and quality decisions, with approval before execution.
Explore the product capability
Details
NAZARE collects and stores equipment signals and existing production and quality records, making them searchable by product, lot and time. NAVIS uses those records and site knowledge to propose likely causes and response steps.
For example, follow a failed inspection back to machine pressure, current and production conditions at the same time. The operator reviews the evidence and approves the response. When equipment control is required, NAVIS sends the approved request to NAZARE, which issues the command to the connected PLC.
OT: collect PLC, CNC and sensor data. Supported source families include FANUC, MELSEC, Modbus, OPC-UA, MQTT and Socket, with equipment-specific models, options and access checked before connection.
IT: connect MES, ERP, APS and QMS through JDBC, REST APIs or MCP. Agree order, product and inspection identifiers and time conventions.
Unstructured: collect images, audio, video, drawings and instructions, with event-linked datasets. Collection and AI interpretation are separate scopes.
| Interface | Use |
|---|---|
| REST API | External applications and services |
| JDBC / ODBC | BI and existing IT tools |
| FlightSQL / ADBC | Large query-result transfer |
| MCP server | Agent data and business context |
| CSV | Review and further analysis |
Apply consistent authorization and audit scope across interfaces.
Agree read methods, frequency, authentication, data contracts and failure behavior with source owners. Changes need separate approval criteria. Prepare samples, test access, network zones and test windows.
AAS integration concerns digital asset representation. AAS, ontology and MCP address asset representation, semantic relationships and tool connectivity respectively.
Start together
Tell us about your equipment, data and priorities to review a path from connection to operations.
