A comprehensive set of tools for rapidly aggregating, contextualizing data around a system representation, and deploying vision AI workflows for better decision-making.
The operating system for vision AI
Aether enables the digital, visual observation of physical systems, the processing and analysis of data streams through pre-built or customized models, and the generation of high-value insights leading to wiser business operations.
Combine internal and external data onto a single environment to aggregate, navigate and visualize a contextualized state representation of your system
- Fuse your data onto a single and contextualized system representation leveraging Aether data ingestion pipelines and contextualization algorithms
- Navigate and visualize your system representation (2D/3D view), and explore complex dependencies using our powerful visualization tools
- Reconcile data from your state representation with field observation using Aether mobile application, and acquire new data in just one click
Import seamlessly large quantities of unstructured data coming from different sources such as cloud object storage (ex AWS). The Data Fusion module allows to automatically transform and contextualize data streams into a unified state representation used for visualization, system state updates and AI model input.
Explore your data from different angles and filter a scope of interest. Thanks to the asset viewer you can explore, filter, aggregate, and export specific attributes of the system or its components, or compare them over time.
The mobile application enables users to integrate mobile workflows, such as visual data collection or field annotations. Experience effortless data collection in the field or ground truthing (available on iOS and Android).
Ingest, create and contextualize 3D models and other visual data (orthomosaics, DSM, DTM, etc.). Visually explore and assess complex data dependencies. Design better models faster.
Aether offers a variety of tools for accelerating the development of vision AI workflows
- Leverage time series to get historical information about your system that can be analyzed by AI algorithms to generate predictive models
- Use pre-built ML models or build upon them to reflect your unique business process
- Easily import and export your data from your preferred labeling tool to train or retrain your models
- Implement incremental learning workflows
- Compute and cross-analyse information using intuitive user interfaces
Time Series Management
The Aether environment supports time series data creation and management for AI applications enablement. Time series refers to a list of data points that qualify the system state representation evolution over time. Time series allows to efficiently address business monitoring needs such as inventory levels, equipment temperature or wear and tear. Time series data provides the historical information needed for analysis by Al and ML algorithms to generate and test predictive models.
Data Computation and Transformation Tools
Enable a variety of pre-built logic-based algorithms that can accelerate the understanding of your system. These tools do not just enable the calculation of distances, surfaces, and volumes but also the analysis of reflectance maps and other types of indexes. You can also choose to extend the pre-built tools to reflect your unique business process or develop custom new packages.
Pre-built ML Models
Make use of a variety of pre-built ML models to accelerate the development of vision AI workflows. These packages contain tools for anomaly or object detection, task segmentation, 3D reconstruction, and point cloud classification. Companies can also choose to extend these pre-built object models to reflect their unique business process or develop custom new object models.
Aether enables the deployment of workflows that seamlessly integrate with existing data storage, enterprise resource systems, tools, and underlying infrastructure. It is designed to connect to and work in harmony with major cloud infrastructure and service providers, and generate outputs that speak the language of your operations.
- Leverage our CLI, set of APls and SDK for easy integration into your existing software environment
- Get full control over who can access what
- Connect your data and decisions with your operations by leveraging a set of business intelligence tools
Command Line Interface
Use the Command Line Interface as a first level of integration, easy to handle, to deploy your own custom analytics on Aether and benefit the platform resources and features for visual and non-visual data management.
Software Development Kit and APIs
Quickly develop specific applications on top of Aether, using the provided Python SDK, to enrich the user experience and business workflows with advanced functionalities. Add custom analytics to your end-to-end workflows. Seamlessly integrate the Aether environment with other IT applications, send push notifications and data in and out to adapt with your operational constraints.
Accessibility and Role-Based Access
To ensure platform security and data integrity, the access to Aether is restricted according to user roles. The roles and rights at Aether are organized according to operational constraints. Create and configure custom roles that fit best your organization’s access needs.
Aether can be accessed using the single sign-on (SSO) authentication method allowing users to securely log in, by using your own enterprise identity provider.
Data Operations Management
Filter, extract and aggregate relevant data about your system. Build customized reports with actionable information that integrate seamlessly into your business workflows and generate optimized work orders. Define warnings to create and trigger operations, allocate them to specific teams and monitor activities.
Creating results that make a difference.
Building a “connected quarry” model to transform operations
- Manage, analyze, and share data from aerial surveys seamlessly with Alteia’s wholly integrated and easy-to-use platform
- Visualize a site in 2D or 3D on an intuitive platform with the capacity to provide orthophotography, slope maps, digital surface models, and 3D models
- Make measurements quickly with integrated tools to calculate length, determine an area size, and calculate stockpile and cut and fill volumes
- Forecast accurately with frequent updates of topographic data
Cemex has transitioned to a “connected quarry” model allowing for truck and machine efficiency optimization with the use of telematics data. Cemex has chosen Alteia to be the central hub of their topographic and machine data to achieve their ambitious transformational goals. In doing so, they can centralize their initiatives and strategic projects and leverage the platform’s extensive data analysis and AI capabilities.
Enabling digital phenotyping with vision AI
- Automate and optimize field data collection
- Accumulate real-time insights into how plants respond to environmental conditions
- Build digital twins of research crops
- Run AI models for crop characterization
Partnering with Alteia, BASF’s agricultural research stations use the Alteia platform to streamline and standardize sensor-based field studies data. This allows them to turn visual drone data into actionable insights and, ultimately, new sustainable solutions for the agricultural market.
Digitizing the world to increase projects efficiency
- Aggregate lidar point clouds into one single data image, easily shareable with clients and partners
- Improve the end-customer experience with user-friendly data visualizations and a collaboration portal
- Streamline workflows with easy drone, satellite, and ground sensor data processing
- Integration of pre-built ML models for feature extraction
Utilizing Alteia’s technology, Stantec platform can organize, centralize, and analyze vast amounts of unstructured data ranging from high resolution imagery to high density lidar point clouds, eliminating many of the data management and processing challenges that typical organizations face when managing projects of that scale.
Leveraging vision AI for power line lifecycle management
- Access data from anywhere, at all levels of the company
- Detect defects, hazards, and maintenance needs with a 90 +% accuracy with automated visual inspection leveraging our pre-built ML models
- Standardize, control, and optimize asset inspections
In 2020, Enedis has decided to deploy artificial intelligence across its organization by leveraging the Æther AI platform. This partnership allows Enedis to accelerate its digital transformation with the systemic use of visual data and AI to verify operations of its medium voltage overhead network.
Optimizing biogas production on waste management sites
- Reduce cycle times and vehicle wear by monitoring road grades
- Optimize traffic plans with up-to-date site maps
- Get a visual timeline of site changes to demonstrate regulatory conformance
- Calculate compaction rate and increase performance
By partnering with Alteia, Veolia has developed its digital process around landfill management to introduce greater safety, efficiency, and traceability into their already advanced and highly critical workflow.
Digitizing mining operations to increase operational performance
- Manage access for everyone, including subcontractors
- Oversee global operations in real-time
- Integrate truck data for haul road optimization and carbon emissions reduction
Eramet recognizes that digital twins, which enable monitoring and performance management, help improve safety and productivity on their sites. The first step towards creating digital twins is creating and maintaining digital records of the sites, leveraging different types of data sources. Utilizing Alteia’s platform, Eramet has placed visual intelligence at the core of its growth, operational performance, and competitive edge.