Picominer® Edge
MLOps For Industrial Automation
Picominer aims to solve the software and process challenges in "AI/ML Model-To-Business Lifeclycle".

The MLOps Problem
Majority (some reports say nearly 60%) of the AI/ML projects do not cross PoC (proof of concept) stage event though the data models are promising in the lab environment.
Unlike software development lifecycle, the data lifecycle is quite different. Usually, the cost of deploying AI/ML models are not factored in the initial estimates.
Model-To-Business needs additional steps that adopt the models to target environment (application context) in the AI/ML project lifecycle. It is the motivation behind the design of Picominer.

Data applications
Managed MLOps
With Picominer Edge we build Model-To-Business data pipelines and offer managed services for to your target environment.
Integrations
Picominer Edge supports a variety of integrations and protocols with automation devices and shop floor MES/ERP applications.
Open source
Picominer Edge platform designs and reference implementation are released under open source licence. No vendor lock-in.
Team training
Our services include team training and support on MLOps, DevOps, Expert Systems etc. to suite your business environment.
MLOps at the Edge
Picominer provides hosting of AI/ML models at the IIoT gateways. Picominer extends the capabilities of IIoT gateways with Ring, Star and Mesh topology.

MOTIVATION
A lightweight AI/ML model serving platform for IoT edge, automation and web.
SOLUTION
Binding the data models and expert knowledge for the target context.BENEFITS
Customised MLOps. Incremental and continuous improvements.
Picominer aims to solve the software and process challenges in "AI/ML Model-To-Business Lifeclycle".
PROJECT STUDY
Firstly, we will schedule meetings with customer
teams to set the scope.
DATA FLOW DESIGN
Identifying various data touch points to align with
the business objectives.
EXPERT SYSTEM
Data models will be subjected to the target
contextualisation process.
MODEL REGISTRY
Models are verified against target environment and a
model registry is prepared.
INTEGRATIONS
Integration (API) with MES/ERP and other
information applications.
Benefits that come with our engagement
Reference design
In-depth reference design, reference implementation and support for MLOps.
Flexible
Customise the MLOps to suite to the business. No opinionated framework.
DevOps
Versatile yet simple platform to run models at scale. DevOps may be used if needed.
Open source
All our reference implementations are released under open source. No vendor lock-in.
AI R&D
Access to our ongoing R&D on AI/ML reference designs and sources.
Team training
Get a structured training to the team on MLOps (online / offline as needed).
Innovation
Our approach is to enable the teams to innovate for the business needs.
Standards based
Incremental and continuous process improvement.
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