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Platform

The Miradoris Platform

A purpose-built software stack that integrates data intelligence, workflow automation, and real-time operational control into a unified system for physical environments.

Data
Ingestion, ontology, transformation
Automation
Flow editor, scheduling, triggers
Control
Policies, permissions, enforcement
Architecture

Four integrated layers. One platform.

Data flows up from sensors and devices, gets structured into a unified model, passes through the intelligence layer for decisions, and surfaces in a single operational view.

OperationsLAYER 4
Geo & Floor Maps
Natural Language Commands
Task & Schedule Interface
Real-time Dashboards
IntelligenceLAYER 3
Visual Workflow Builder
Policy & Safety Rules
AI Task Assignment
Anomaly Detection
Unified Data ModelLAYER 2
Typed Entity Schemas
Relationship Mapping
Graph Synchronization
Vendor-neutral Model
Data & IntegrationLAYER 1
Sensor Data Polling
Device Commands
Location Monitoring
Third-party Integrations
Commands flow down
Data flows up
Spatial Ontology

Structured representation
of operational reality

The spatial ontology is a typed, vendor-neutral data model that represents every asset, location, task, and rule as connected entities in a semantic graph. It is the foundation that every other platform capability builds on.

Typed entity definitions
Assets, locations, tasks, and policies with enforced schemas and property validation.
Property inheritance and versioning
Schema evolution with migration support. Namespace isolation per deployment for multi-tenant operations.
Real-time graph synchronization
Live data feeds keep the ontology current. Every sensor reading and location change reflects instantly.
Explore the ontology
ENTITY Asset ENTITY Location ENTITY Task ENTITY Policy located_at assigned_to governs depends_on constrains
type Asset { id: UUID, name: String, location: Location, status: Enum }
type Location { id: UUID, name: String, coordinates: GeoPoint, zone: Zone }
type Task { id: UUID, assignee: Asset, policy: Policy, status: Enum }
edge located_at { from: Asset, to: Location, since: Timestamp }
Data Layer

Data ingestion &
unified ontology

Connect any data source into a single operational model. Miradoris ingests, normalizes, and transforms raw data into a structured ontology that maps every relationship between your assets, locations, and operations.

Ontology model
Assets
Drones, robots, vehicles, workers
Locations
Sites, zones, floors, coordinates
Tasks
Operations, assignments, schedules
Rules
Policies, constraints, permissions
Data flow
πŸ“‘
Sensors & IoT
🏭
SCADA Systems
πŸ”—
APIs & Webhooks
πŸ“Š
Telemetry Feeds
πŸ—ΊοΈ
GIS & Maps
Transform & Normalize
Schema mapping, validation, enrichment
Unified Ontology
Assets β†’ Locations β†’ Tasks β†’ Rules
Visual Flow Editor
Trigger
Sensor alert
Condition
Wind < 25kn?
Dispatch
Assign drone
Notify
Alert team
Inspect
Run scan
Complete
Log result
Automation

Visual flow editor

Build automation workflows with a drag-and-drop visual editor. Define task sequences, branching logic, and conditional triggers -- operational workflows become clear, auditable diagrams.

Drag-and-drop workflow builder
No code required. Build, test, and deploy workflows visually.
Conditional branching
React to sensor data, weather, asset status, and external events.
Dependency resolution
Automatically parallelizes tasks and reschedules on failure.
Governance

Policy & permissions
engine

Define operational rules, safety zones, access permissions, and compliance requirements. Every action is validated against your policies in real time -- nothing executes without clearance.

Real-time enforcement
Policies checked before every command is executed.
Role-based access control
Granular permissions per user, team, and asset type.
Audit trail
Complete log of every decision, override, and policy evaluation.
Safety Zone Critical

No drone flights above 120m within 2km of airport perimeter

Certification Required

Only Level-3 certified operators can control heavy machinery

Permission Enforced

Contractor teams restricted to assigned work zones only

Operational Active

Maximum 4 drones per sector during active maintenance windows

Trigger Rules
4 active rules
If: Temperature > 85Β°C on any motor
Armed
Then: Reduce RPM to 60%, notify maintenance lead
If: Humanoid enters restricted zone without clearance
Armed
Then: Halt movement, lock zone perimeter, alert supervisor
If: Conveyor idle > 15 min during active shift
Armed
Then: Log downtime event, reassign pending tasks
If: Air quality index drops below threshold
Testing
Then: Activate ventilation protocol, evacuate zone if critical
Automation

Custom triggers
and actions

Define rules that bind specific conditions to automated responses. When a trigger fires, whether from a sensor reading, a geofence breach, or an access anomaly, the platform executes the associated action sequence without manual intervention.

Condition-based trigger definitions
Combine sensor data, entity state, time windows, and logical operators.
Composable action chains
Sequence multiple actions with conditional branching and fallbacks.
Full audit trail
Every trigger activation and action execution logged with timestamps.
Monitoring

Behaviour monitoring,
alerts and warnings

Continuous monitoring of every operator, device, and autonomous agent in your environment. The platform evaluates behavioural patterns in real time, surfaces alerts when thresholds are breached, and escalates warnings through configurable notification channels.

Real-time pattern evaluation
Behavioural patterns tracked across operators, devices, and agents.
Configurable alert thresholds
Define severity levels and escalation rules per entity type.
Multi-channel notifications
Route alerts to dashboards, email, webhooks, or SMS based on severity.
Live Alert Feed
Monitoring
Warning Forklift FL-09
14:32:07

Operating outside designated zone for 4m 12s

Critical Conveyor C-03
14:28:41

Throughput 62% below hourly baseline

Info Operator J. Ramos
14:15:03

Access pattern deviation detected in Sector 7

Channels:
DashboardEmailWebhookSMS
Intelligence

Automatic deviance
monitoring

AI models trained on operational baselines continuously evaluate system behaviour and flag deviations. When an entity acts outside its established norms, the platform generates a deviance report with severity classification, probable cause analysis, and recommended remediation. No manual rule writing required.

Baseline learning
AI builds behavioural profiles per entity, process, and environment.
Anomaly scoring
Every deviation scored by severity with confidence intervals.
Probable cause analysis
AI correlates deviations with system state to identify root causes.
Deviance Reports
AI analysis
Robot Arm RA-02 High
Metric
Cycle time
Baseline
4.2s avg
Current
6.8s avg
Probable: servo motor degradation in joint 3
Warehouse Zone B Medium
Metric
Pick rate
Baseline
142/hr
Current
89/hr
Probable: routing congestion from reslotting
Reporting

Operational reporting

Transform raw operational data into structured, actionable intelligence. Generate scheduled or on-demand reports covering incidents, compliance, trends, and deviance patterns. Designed for both technical teams and executive stakeholders.

Incident Summary

Weekly

Consolidated view of all incidents, alerts, and resolutions with trend analysis.

Compliance Posture

Monthly

Policy adherence rates, violation trends, and certification readiness metrics.

Operational Trends

Daily

Entity performance, throughput metrics, and behavioural pattern shifts over time.

Deviance Report

On-demand

AI-generated analysis of anomalous behaviour with root cause and remediation.

Export formats:
PDFCSVAPI
Natural Language Interface

Operational control
through natural language

Express operational intent in plain language. Miradoris resolves entity references, validates against active policies, and translates input into precise, executable commands.

  • Automatic resolution of entity names and spatial references
  • Policy validation prior to command execution
  • Batch operations across multiple assets and locations
  • Complementary to direct manipulation and map-based controls
Command Interface
>
Indoor β€” Floor Plan
Outdoor β€” Geo Map
Seamless handoff between indoor and outdoor
Spatial

Unified indoor and outdoor spatial awareness

Manage floor plans and geographic maps in one interface. Assets moving between indoor facilities and outdoor sites are tracked continuously without manual handoff -- across locations, buildings, and floors.

Floor plan import
Upload building plans and overlay them on the map.
Multi-location tracking
Move robots between buildings and outdoor zones without losing context.
Automatic coordinate mapping
Indoor and outdoor coordinate systems are unified automatically.
Compatibility

Hardware-agnostic by design

Humanoid robots, drones, AR glasses -- Miradoris integrates with any hardware through a vendor-agnostic adapter layer. No lock-in, ever.

Robots
Humanoid robots
AMRs & AGVs
Inspection robots
Collaborative arms
Aerial
Survey drones
Inspection drones
Delivery drones
Fixed-wing UAVs
Wearables
AR glasses
Smart helmets
Body-worn sensors
Handheld devices

No vendor lock-in

Connect any hardware from any manufacturer. Miradoris uses open protocols and a vendor-agnostic adapter layer.

Easy reassignment

Reassign any asset to any task in seconds. Mixed human-robot teams collaborate with unified task management.

Relationship modeling

Define which tools work with which robots, which payloads fit which drones, and which certifications are required. Prevent incompatible assignments automatically.

Be among the first

We are looking for partners willing to test Miradoris in real operational environments. Early adopters get priority access to the platform at significantly reduced rates.

We'll review your request and follow up. No unsolicited contact.