How to validate your company's data readiness?
Use our Data Maturity Model to understand where your organization stands and what steps are needed to successfully implement AI-powered maintenance solutions.
7 levels of data maturity
Assess your current level and understand the path to AI-ready operations
Level 1 - You have systems and collect data
Your organization has basic systems in place and is actively collecting operational data from various sources.
Level 2 - You know what data means and work with it
Your team understands the collected data, its significance, and actively uses it in daily operations.
Level 3 - You use data in decision making
Data-driven insights inform your operational decisions and help optimize processes.
Level 4 - People in your team work with data and understand results
Your team members are data-literate, can interpret analytics, and apply insights to their work.
Level 5 - You can build additional services or systems on data
Your data infrastructure supports building new applications, services, and automated workflows.
Level 6 - You can automate processing and improve based on data
Automated data pipelines enable continuous improvement and self-optimizing processes.
Level 7 - You can integrate machine learning and LLM solutions
Your organization is ready to deploy advanced AI, machine learning models, and large language models (LLMs) for intelligent automation.
What we need from you if you want to integrate Pulsar to your factory
Five key steps to prepare for a successful AI implementation
Identify the most relevant areas in maintenance
Pinpoint the parts of your maintenance operations that face the most challenges—whether it's specific machines, production halls, or staff.
Choose an initial focus area for implementation
Select the first area to start with, such as a specific machine type (e.g., CNC machines) or a production hall.
Prepare relevant data for the use case
Gather all necessary data for the chosen area, including machine manuals, maintenance logs, revision history, and details of existing problems.
Assign a data validation and testing lead
Designate a person responsible for overseeing data validation, testing the solution, and coordinating with our team.
Set clear, measurable goals for the implementation
Define what you want to achieve with Pulsar Solutions, such as reducing downtime by a certain percentage or improving first-time fix rates within a set timeframe.
Ready to assess your AI readiness?
Let's work together to evaluate your current data maturity level and create a roadmap for successful AI implementation.