Flexible image-centric AI/ML
engineering platform
compliant with Industry 4.0 standards
with strong
data management capabilities.
BeeYard supports ML/AI engineers and data scientists throughout the entire MLOps workflow and enables collaboration of all stakeholders within enterprises.
An ultimate solution addressing industrial-grade applications, BeeYard was designed to utilize the maximum amount of variable data from production, including images from industrial optic systems, to build robust ML/AI modules quickly and reliably.
BUILD ROBUST ML/AI MODELS FASTER
DESIGNED FOR INDUSTRIAL-GRADE
MACHINE VISION APPLICATIONS
END-TO-END ML/DS Platform
BeeYard covers the entire MLOps workflow:
-
data collection and organization
-
data preparation and pre-processing (annotations, labeling)
-
model training
-
deployment
-
maintenance
1.
2.
3.
4.
5.
Feasibility
Study / POC
Prototype
Deployment & Commissioning
Production
Maintenance
COVER THE ENTIRE MLOps WITH ONE
POWERFUL PLATFORM
Data cell
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A set of all object - related data
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Basic database unit
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Context - driven data storage
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bound to each object
-
Created time
-
Modified time
-
Description
-
Tags
-
Properties
DESIGNED FOR MACHINE VISION
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large data volumes processing;
-
data collection and storage optimized for ML/AI tasks;
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contextual data storage - DATA CELL APPROACH
images are tight with context metadata from other sources; -
hive database storage local or cloud.
INDUSTRIAL MACHINE VISION REQUIRES SPECIFIC
APPROACH TO DATA PROCESSING AND MANAGEMENT
SDKs
AUTOMATED
BeeYard leverages automation features to
accelerate ML/AI systems development:
-
AI-assisted labeling.
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Data cleanups
-
Data preparations
-
Pretrained models for principal DL tasks,
facilitate finetuning of these models.
ACCELERATE THE MLOps WORKFLOW AND
GET RID OF TIME-CONSUMING MANUAL TASKS
BeeYard is designed to be embedded into CI/CD pipeline.
Polygon selections
AI assisted
labeling
Label classes
Key
points
Bounding boxes
Semantic
segmentation
DATA PREPARATION
Annotation jobs
-
all types of annotations required in industrial field
-
coordination between annotators
-
can be distributed to annotators anywhere with
access rights management.
Image preprocessing
Image augmentation
-
images and annotations are already in the
correct format to be feed to whatever computer
vision algorithm or deep learning model,
Batch operations on images:
-
eliminate repetitive annotations by applying it to
a batch of images in one shot.
THE QUALITY OF MACHINE VISION ALGORITHMS STARTS WITH VALID AND CONSISTENT DATASETS
COMPOSITE AI CAPABILITY
BeeYard supports deep learning as well as other AI
techniques (traditional machine learning, image
processing, or even a combination):
-
A combination of conventional machine learning
and deep learning achieves the highest possible
performance.
-
Deep learning is not transparent enough to be
applied to all industrial applications (not possible to
explain the outcomes and comply with e.g. quality
regulations).
-
Teams can test both in parallel or use hybrid
combinations (machine learning + deep learning).
DEEP LEARNING IS NOT A SILVER BULLET,
ESPECIALLY IN MANUFACTURING
BeeYard local storage
Public Cloud
Private Cloud
HYBRID CLOUD SOLUTION
BeeYard supports hybrid scenarios
of data collection and storage
-
Edge *
-
On premise
-
Public or private Cloud
-
Or a combination.
BE COMPLIANT WITH INTERNAL CONSTRAINTS AND
POLICIES ON DATA GOVERNANCE AND SECURITY
COLLABORATIVE CAPABILITIES
Collaboration of all involved parties, team members,
3rd parties at all stages of machine vision projects:
-
audit logs
-
versioning
-
access rights
Collaborative annotations
BeeYard serves as a communication tool for the dialogue between domain experts (in-house teams) and data scientists (in-house or 3rd party), typically quality managers who can label or annotate pictures directly in the platform.
INVOLVE DIFFERENT USERS TO PARTICIPATE
ON THE MACHINE VISION PROJECTS
SINGLE POINT OF TRUTH
ONE DATABASE ~ MANY USERS
SCALABLE ARCHITECTURE
Deploy BeeYard from the local edge up
to enterprise level utilizing cloud storage:
-
EDGE level
-
FACTORY level
-
ENTERPRISE level
* Optional BeeYard EDGE device for the
collection of data from the edge devices
as part of the BeeYard product family.
SCALABLE ARCHITECTURE ENABLES TO PROPAGATE DATA
FROM THE EDGE UP TO THE ENTERPRISE LEVEL FOR FURTHER
PROCESSING OR ANALYSIS
DATA MANAGEMENT & SECURITY
BeeYard supports deep learning as well as other AI
techniques (traditional machine learning, image
processing, or even a combination):
-
ACCESS RIGHTS
-
USER MANAGEMENT
-
AUDIT LOGS
-
VERSIONS
-
Protection against the loss of data,
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Automated backups,
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Synchronization between multiple devices,
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Easy data transfer,
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Restore capabilities,
-
Security compliance.
SECURITY:
MANAGE WHO CAN MANIPULATE WITH YOUR DATA AND IN WHAT WAY, ESPECIALLY WHEN A WIDE THE AUDIENCE HAS ACCESS RIGHTS
DATA MINING
Easy access to the correct and specific data:
-
easy aggregations,
-
queries management,
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insights on data,
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tools to output statistics of the data,
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automated tests on specific batches of data,
-
possibility to add properties to data such as sensor
measurements, date and time, dimensions etc.
EASY ACCESS TO RELEVANT PRODUCTION DATA FROM VARIOUS SOURCES
Proposed BeeYard Architecture
OPEN-SOURCE EXAMPLE
