Process Experts Are the Hub of Success for AI and Advanced Analytics
In today’s fast-paced, digital landscape, there is no better space for Generative AI (GenAI) to impact operational excellence than in a collaborative environment with instantaneous connection to time series data at the hands of thousands of process experts. In short, Seeq.
In Part One of our GenAI blog series, we discussed how Seeq plans to leverage new GenAI capabilities to empower users to improve manufacturing processes. In Part Two, we will explore how Seeq is building a foundation for success with GenAI and advanced analytics by integrating the core elements—reliable enterprise data, advanced analytics, and Generative AI—within a workflow that places domain experts at the center of the process.
Enhancing Collaboration Across the Enterprise
From experts in first-principles models and data science, to operational and high-level business decision-makers, Seeq users span the entire enterprise. Within one private Seeq instance, this wide variety of users can access and impact their process data, analytics, and insights while continuously improving their results and efforts to enhance their operations.
With the Seeq AI Assistant, we are embedding AI into this collaborative environment to bridge the knowledge gap between these domain-specific experts and their individual tasks by facilitating communication, understanding, and results. The AI Assistant leverages GenAI models alongside specific questions, calculations, tasks, views and actions that are part of the advanced analytics workflows in Seeq. This combination streamlines the ability to elevate analytical results, provide business and operational insights, and offer recommendations for action within the Seeq advanced analytics platform.
Domain experts belong at the core of workflows
At Seeq, we prioritize the importance of human users and their central role in manufacturing analytics, including and especially where AI is assisting. Seeq is purpose-built to meet users where they are in their need and ability to generate insights from time series process data.
After working with our customers and observing our new AI capabilities in the field, it’s obvious that GenAI reduces the time required to get valuable decisions and can even offer suggestions for analytical methodologies and code. This means individuals without specific analytics, data science or coding skills can turn their hardest questions and ideas into insights, making impactful action more accessible to a broader audience within organizations.
For example, a significant aspect of any learning curve is the verbiage, terms, acronyms and language. In time series analytics and the Seeq platform, AI can be curated and tuned with these terms, such as “capsules” and “signals” or “scatterplot,” to reduce or eliminate any language-based barriers to success.
Additionally, if users need assistance understanding analytics approaches and/or results in a specific native natural language, embedded AI can give impeccable guidance for their analytics and workflow questions
Repetitive data analysis tasks can be automated away, freeing up valuable time for process experts to focus on more strategic and complex aspects of their roles. As users benefit from AI conversations, those persist as curated and targeted insights for quick and consistent reference and assistance.
Early Impact
For our early AI Assistant users, we see impactful analytical approaches and automated workflows proliferating and scaling with ease. This includes data asset structures being conceptualized in minutes rather than days (and what used to take months or years), optimized calculations, and reports and dashboards being scaled across organizations. Automation of tasks like scheduled monitoring calculations and affiliated notifications are also perfectly suited for this capability. These are things that previously only code-savvy users could do, and it took them much longer to do it.
These efficiencies reduce analytics ideation, iteration and workflow implementation administration load, enabling teams to increase efficiency between five and 50-fold using the Seeq AI Assistant. This, in parallel with our scaled calculation engine and cloud-native infrastructure, unleashes an organization’s full capacity to generate enterprise insights from their manufacturing data. These are the tasks our early users and soon all users will be able to do with the new integrated AI Assistant.
Data privacy is essential
In manufacturing analytics, private AI assistance within a dedicated SaaS platform is crucial. Leveraging AI’s potential to assist data analysis, process optimization, and critical decision-making can be challenging due to the sensitivity of the data that is associated with these critical systems. Seeq recognizes the importance of bridging knowledge between AI, time series data, and subject matter experts and that data privacy is equally vital.
You own your data. Any data used by a manufacturing analytics platform or its AI models must remain private and isolated. Customer information cannot be used for training public or general models with AI integrated in Seeq. This strict commitment to data privacy ensures a secure AI assistance environment, enabling process experts to explore insights confidently.
A New Era of Analytics
We encourage users to explore these exciting developments by contacting their Seeq Customer Success representative and signing up for our Seeq Preview Program. The collaborative program enables users to test these new capabilities as we develop them and provide feedback, ideas, and more.
Not a current customer or ecosystem partner? Please contact us here for more info.