Product · Built by Asteres Technologies
An AI-native operating system. DAEGON stands up, runs, and tracks complete AI systems from declarative workflow definitions, on infrastructure you own.
01What it is
One system, end to end
DAEGON replaces hand-wired glue between models, data, and services with a declarative spec. Its first use is sovereign enterprise AI; it grew out of our work in autonomous and space systems, which is where it is headed next.
Declarative workflows
Define multi-step AI pipelines, models, data sources, and external APIs in a readable DSL instead of glue code.
Every workflow is an API
Deploying a workflow spec automatically provisions production-ready microservices, REST APIs, and WebSockets.
Runs and tracks the whole system
DAEGON stands up the services a system needs, orchestrates them, and keeps track of everything they do.
Retrieval & memory
Vector search, embeddings, and document ingestion for retrieval-augmented generation, bound declaratively.
Multimodal ingestion
Native pipelines for documents, code, audio, images, and live streaming feeds.
Event-driven core
Built on Kafka streaming for real-time messaging, schema validation, and horizontal scaling.
02Declarative by design
Code what you want
A DAEGON workflow describes inputs, steps, and outputs. This example runs anomaly detection on camera frames through an Intel OpenVINO inference service, entirely on local hardware, and is deployed as its own API.
workflow edge_intel_vision {
external {
intel_openvino_node: "http://localhost:9001/openapi.json"
}
inputs {
camera_id: string
frame_bytes: string
}
steps {
run_intel_inference: call intel_openvino_node.inspect_frame with {
"cameraId": input::camera_id,
"frameData": input::frame_bytes,
"model": "openvino-anomaly-v2"
}
}
output {
anomaly_detected: bool = gt(step::run_intel_inference.result.confidence, 0.85)
inference_metrics: object = step::run_intel_inference.result
}
}03Deployment
Three ways to run DAEGON
Enterprise
Turnkey, in-house AI on your own infrastructure: secure RAG and search, private chat agents, document ingestion, and data workflow automation.
Solution partners
Consultants and integrators license DAEGON to build, brand, and deploy domain-specific AI workflows for their clients while keeping their IP.
Hardware & OEM
Pre-installed DAEGON appliances for edge and on-premise AI, co-built with hardware partners and optimized for Intel platforms.
04Intel Partner Alliance
Why Intel
DAEGON's inference layer is built in Python, and Intel has invested heavily in optimizing the Python AI stack, including OpenVINO, for standard CPUs and edge hardware.
Hardware you own
Run sovereign, on-premise AI on x86 hardware organizations already own or can readily buy, without depending on scarce GPU supply.
Data center to edge
Accelerated inference on Intel platforms, from servers to edge appliances.
Partner network
As a member of the Intel Partner Alliance, we work with Intel and its partners to deliver DAEGON appliances and services.
05Get started
Bring AI in-house
DAEGON 1.0 is open for early access. Join the waitlist, or talk to us about a partner, enterprise, or OEM deployment.