Build your own applications on the same infrastructure.
Atlas, Socius and Chronos are modules — built on an SDK that is open to your team as well. Custom applications inherit sovereignty, ontology, audit trail and explainability automatically. No fork, no parallel infrastructure.
Five primitives that let you build anything.
The same building blocks we used to build Atlas, Socius and Chronos — documented, versioned, ready for your teams.
Connect any source
Adapter patterns for REST, gRPC, S3, OPC-UA, GIS, databases. Your connectors are first-class — no special treatment compared to built-ins.
Pipelines, declaratively
Source → inference → ontology → output, as code. Versioned, testable, reproducible — from notebook to operations.
Plug in your own models
Register your ML models in the Cortex registry — with confidence tracking, versioning and audit trail like built-in models.
Extend your domain
Add your own concepts (actor subtypes, events, relationships) to the shared ontology — compatible with Atlas/Socius/Chronos.
Interfaces that fit Makor
Components for maps, graphs, time series, audit views. You build interfaces for your workflows, not for ours.
Same infrastructure
Custom applications run on the same on-prem/private-cloud infrastructure as the modules. No second stack, no second audit pipeline.
// Custom connector — bind any source to Axis from makor.sdk import Connector, Flux, Cortex class RadarFeed(Connector): schema = "axis://radar.v1" def stream(self): yield from self.poll(interval="5s") // Compose pipeline → Kontinuum pipeline = (Flux("radar.lagebild") .source(RadarFeed()) .infer(Cortex.model("anomaly.v3")) .annotate(ontology="verkehr") .publish("lagebild.verkehr.tiles")) pipeline.deploy(env="on-prem", audit=True)
One connector, one pipeline, one model — and you have a custom application with audit trail and explainability. Schematic.
Five primitives that let you build anything.
The same building blocks we used to build Atlas, Socius and Chronos — documented, versioned, ready for your teams.
Your domain has concepts no standard module knows. You model them in the ontology and build the interface your team actually needs.
Your research team has a model nobody else has. You plug it in as a Cortex model — with the same audit pipeline as built-ins.
Map recurring analysis and approval processes as Flux pipelines — versioned, testable, with an audit trail per run.
Build data products for other teams without demanding a data warehouse — results as API, tile service or notebook output.
Your team builds. We deliver the backbone.
In the pilot, your engineers get SDK access, training, and pairing sessions with our team. You keep code, data and audit logs.