Data Engineer at a energy/utilities company with 10,001+ employees
Real User
Top 20
Jan 7, 2026
I have been using C3 AI for five years. My main use case for C3 AI is predictive maintenance, which belongs to reliability asset in development. A specific example of how I use C3 AI for predictive maintenance is that we have different assets coming through as predictive maintenance related to pumps, compressors, and other equipment. C3 AI helps with those compressors and other equipment by spotting issues before they happen and reducing downtime, which is exactly what we used to have a use case for. When we use C3 AI for predictive maintenance, we raise a critical alert when we identify any exceptions, helping us to identify any preventive issues and reduce shutdowns.
Group Head of Data Strategy & Enterprise Governance at a consumer goods company with 10,001+ employees
Real User
Top 20
Jan 7, 2026
My main use case for C3 AI was as an implementation partner working for a technology consultancy firm, where we attempted to introduce C3 AI to our clients, primarily in the financial services sector. We wanted to introduce C3 AI for three reasons. First, it had been funded by Tom Siebel and his son, and given the reputation and legacy of the Siebel family, we believed they have strong connections in the corporate software world. Siebel and his legacy CRM solutions, along with his network, are important assets. Second, they wanted to bring enterprise-level engineering and software building to the world of AI, which was very attractive to us because in many cases, AI consists mostly of proof of concept and small experiments that never reach large-scale applications. If C3 AI could make that work and reach the enterprise level, that would be really good. Third, the main interface for developing anything with C3 AI is based on JavaScript, meaning that many traditional corporate IT professionals could also work on AI implementations without needing deep training in specific machine learning languages such as Python or R. This was the primary reason we wanted to work with C3 AI.
I have been using C3 AI for five years. My main use case for C3 AI is predictive maintenance, which belongs to reliability asset in development. A specific example of how I use C3 AI for predictive maintenance is that we have different assets coming through as predictive maintenance related to pumps, compressors, and other equipment. C3 AI helps with those compressors and other equipment by spotting issues before they happen and reducing downtime, which is exactly what we used to have a use case for. When we use C3 AI for predictive maintenance, we raise a critical alert when we identify any exceptions, helping us to identify any preventive issues and reduce shutdowns.
My main use case for C3 AI was as an implementation partner working for a technology consultancy firm, where we attempted to introduce C3 AI to our clients, primarily in the financial services sector. We wanted to introduce C3 AI for three reasons. First, it had been funded by Tom Siebel and his son, and given the reputation and legacy of the Siebel family, we believed they have strong connections in the corporate software world. Siebel and his legacy CRM solutions, along with his network, are important assets. Second, they wanted to bring enterprise-level engineering and software building to the world of AI, which was very attractive to us because in many cases, AI consists mostly of proof of concept and small experiments that never reach large-scale applications. If C3 AI could make that work and reach the enterprise level, that would be really good. Third, the main interface for developing anything with C3 AI is based on JavaScript, meaning that many traditional corporate IT professionals could also work on AI implementations without needing deep training in specific machine learning languages such as Python or R. This was the primary reason we wanted to work with C3 AI.