First-person views from the world of industrial IoT, data, and digital solutions.
OP Financial Group, one of Finland's largest financial services companies, teamed up with Brightly to scale up their data and analytics capabilities, fostering a robust data community within the organization. The project demonstrated that fostering a culture of data literacy and innovation requires the right tools, infrastructure and a data-oriented, problem-solving mindset.
Brightly created a PoC of an AI-powered tool that enables Normet personnel to make natural language queries into IoT data, making data more accessible and valuable throughout the organization.
Software testing is the unsung hero of the various development disciplines. Often the testing is seen as ‘Complex!’ ‘Time-consuming!’ and ‘Tedious!’ But as a systematic part of your development processes, it makes developers’ work smoother, easier, and cost-effective while making your product solid, bug-free and future-proof. Here are some ways to leverage testing to improve your product and help your developers do their best work.
The hype is strong with AI. As we're bombarded with AI-related topics, it might seem imperative to move quickly, but it's equally important to ensure that we're solving the right problems. Read more to learn how use a problem-solving mindset to make your AI project successful.
Modern data solution development has surprisingly many similarities with the innovation process. In this blog, I describe how to recognize innovation phases when developing data and analytics cases.
This blog post delves into the application of modern AI for extracting meaningful insights from the turmoil of social media discourse. We showcase this technique by examining the social media conversations about the ongoing labor market reforms and political strikes in Finland.
This article will address the impact of unit testing on projects, define testable units, explore the benefits of disciplined practices, and provide guidance on getting started.
This article distills Brightly’s hands-on experience into essential dos and don'ts when developing GenAI applications for production use.
Data monetization is a process of converting organizations’ raw data into sellable data products. This article covers two real-life examples of data monetization, explains the key benefits of data monetization, and describes how to monetize your data in practice.
Generative AI has the potential to contribute $2.6 trillion to $4.4 trillion annually to the global economy, making this the right moment to seize market share. The question is, how can you determine GenAI's real value for your business?
This case study explains the solution we built in partnership with a prominent car dealer to enhance their business efficiency by leveraging a predictive model to estimate used car sales cycles.
Explore the essential guide to streamline Git workflows for efficient software development and quality assurance. From understanding core Git workflows to implementing release management, Semantic Versioning, and embracing automation, this article offers practical strategies to enhance collaboration, code quality, and overall development efficiency.