Horizon — Common Operating Picture
Horizon is Scrydon's Common Operating Picture (COP) — a live, map-centric view of your entire operation, fusing your data spaces, analytics, and running process flows so operators and workflows can act instantly.
Horizon is Scrydon's Common Operating Picture (COP): a persistent, map-centric view of everything happening across your operation, right now. Detections appear as they arrive, tracks update live, and every dot on the map is backed by governed data — classified, masked, and clearance-filtered per viewer.
Feature-flagged. Horizon is an early-access product: its surfaces are disabled by default and enabled per deployment by your platform operator. Talk to your Scrydon contact to turn it on. Everything process flows depend on — including map actions inside a running flow — works regardless of the flag.
Execution vs. awareness
Horizon is a product; the rest of the platform is the engine underneath it.
| Agentic — the "Engine Room" | Horizon — the "Control Tower" | |
|---|---|---|
| Role | Workflow automation | Situational awareness |
| What it does | Runs the logic: state transitions, AI prompt chains, background system tasks | Displays the state of the world on a persistent visual interface |
| Question it answers | "How does the work get done, and who does it next?" | "What is happening across our entire operation right now?" |
| OODA phases | Act — plus the automated decisions you delegate to workflows | Observe, Orient, Decide — the human on the loop |
Analytics and the Ontology complete the engine: your data spaces feed governed managed tables, the ontology types them, and Horizon fuses them onto a single picture.
The OODA loop, compressed
Every operations doctrine since Boyd frames decision-making as the OODA loop — Observe, Orient, Decide, Act — and the organization that cycles it faster than the situation changes is the one that stays in control. Horizon and the engine underneath it are the platform's implementation of that loop, end to end and event-driven (no polling):
- Observe — a webhook or scheduled workflow receives telemetry, writes it to a governed managed table, and opens (or updates) a process-flow instance per track; duplicate detections collapse onto the existing instance automatically. A thin signal fans out instantly to every authorized operator watching the picture — it carries no sensitive payload, so clients re-read through governed endpoints at their own clearance.
- Orient — the picture gives the raw observation its meaning: the ontology types the track, Analytics joins it against everything already known, and AI assessments and advisories appear alongside the live map — fused, clearance-filtered context instead of a bare dot.
- Decide — the operator records a decision on the running process flow: classify the track, send it back for re-assessment, or approve the response. AI recommends; the human on the loop decides.
- Act — the decision writes through to the governed table and unlocks the downstream automation — distribution, tasking, reporting — back in the engine room. What the automation changes shows up on the picture, and the loop begins again.
The division of labor is the point: Horizon owns Observe → Orient → Decide (awareness and the human decision), Agentic owns Act (and any decision you explicitly automate). Compressing the loop from minutes to seconds is what a COP is for.
Everything on a Horizon picture respects the platform's governance stack: document clearance, column masking, and Rego authorisation apply to the map exactly as they do to tables and search. See Security.
Where a COP earns its keep
The COP pattern was born in defense and has spread to every industry that runs distributed physical operations. Horizon targets the same use cases:
Defense, intelligence & aerospace
The birthplace of the COP. Military operations fuse thousands of telemetry feeds — satellite imagery, drone video, blue-force (friendly) tracking, radar, weather — into a single, secure map interface. Use case: theater-wide situational awareness, mission planning, threat detection, and synchronized joint-force execution.
Emergency management & public safety
First responders, civil defense, and homeland security agencies rely on COPs to manage crises. Use case: during floods, wildfires, or industrial accidents, a COP bridges the communication gap between police, fire departments, medical teams, and NGOs — integrating dispatch (CAD) logs, field-agent GPS positions, traffic cameras, and real-time hazard mapping.
Energy, utilities & critical infrastructure
Managing large-scale physical networks requires an immediate understanding of system health and external risk. Use case: electrical grids, water networks, and oil & gas pipelines layer SCADA sensor alerts, asset health data, weather forecasts, and field-technician locations onto a single pane of glass to prevent — or rapidly respond to — outages and leaks.
Healthcare & hospital command centers
Modern hospital networks treat bed allocation and patient flow like air traffic control. Use case: fusing ER wait times, ICU bed availability, incoming ambulance telemetry, and staffing levels across regional facilities to optimize resources and handle surge or mass-casualty events.
Maritime, ports & supply-chain logistics
Ports and large logistics networks are inherently chaotic — dozens of moving parts, international data spaces, changing environments. Use case: managing container-ship arrivals, berth assignments, weather, AGV coordinates, and customs clearance in real time. Humanitarian logistics use the same pattern to coordinate cross-agency relief in disaster zones.
The common thread: data fusion
Across all of these, the value is interoperability and data fusion. A COP matters to an enterprise because it takes your data spaces (the siloed databases) and your analytics (the background crunching) and visualizes them on a single timeline or map — so that human operators and your Agentic workflows can act instantly.