Last year, we embarked on a journey to understand the rise of AI and why it should matter to everyone at ERNI. After a thorough analysis, we concluded that to leverage AI fully, we needed a tool accessible to all employees. Thus, the idea of having an internal ChatGPT was born.
By Alberto Martín (ERNI Spain)
Why your company should have an internal ChatGPT:
1. Our use case
ERNI AIDA was launched for all ERNIans early this year. The application features a simple interface, so users do not need extensive technical knowledge. They can simply choose the model, adjust the so called “temperature”, and start using it. This ease of use has made it a popular tool among our employees.
2. Impact on productivity
AIDA represents the first step in ERNI’s journey to accelerate AI adoption. With the tool in place, we plan to provide training sessions to help employees maximise its potential. Additionally, we will organise a tournament to practise the knowledge acquired. This initiative aims to enhance productivity and foster a culture of continuous learning and innovation.
3. Security and compliance
ERNI AIDA is designed with security and compliance in mind. It adheres to ISO27001 standards, ensuring that we can use it for confidential information without the risk of the model being trained on the provided data or storing any of it. This level of security is crucial for maintaining the integrity and confidentiality of our business operations. Additionally, having an internal GPT reduces the risk of employees using external platforms, thereby preventing potential leaks of sensitive information.
4. Cost efficiency
We adopted a “pay-as-you-go” approach, which allows us to avoid being tied to a specific licence for a particular purpose. This flexibility ensures that we only pay for what we use, making it a cost-effective solution for our organisation.
5. Accessibility and updates
The tool is easily accessible and integrated with the latest models, such as GPT-4o, DALL-E 3, GPT4-Vision, and text-to-speech capabilities. This ensures that our employees always have access to the most advanced AI technologies, enabling them to perform their tasks more efficiently. It also incorporates the ability to upload documents and “ask questions” about them.
6. Innovation and future plans
We also aim to evolve the tool with new features in the field, such as a prompt marketplace, ensuring that we collaborate to share the best and most useful use cases for each area and technology. To date, nearly 400 ERNIans are using the tool for various purposes. This forward-thinking approach positions us as innovators in the industry and demonstrates our commitment to leveraging AI for business growth.
7. General solution with comprehensive capabilities
While ERNI AIDA is a general solution designed to enhance productivity and innovation, our capabilities extend across the entire spectrum of data and AI projects. We specialise in delivering custom solutions tailored to meet our customers’ unique needs. Whether it’s developing advanced machine learning models, implementing data analytics platforms, or creating bespoke AI-driven applications, our team has the expertise to handle it. This versatility ensures that we can provide comprehensive support to businesses looking to leverage AI for their specific requirements.
Conclusion
ERNI AIDA not only positions us as innovators but also helps us become more productive in our daily work. From a business perspective, the implementation of AIDA is a strategic move that can drive significant competitive advantage. By leveraging advanced AI capabilities, we can optimise operational efficiencies, reduce costs, and improve decision-making processes. Furthermore, the insights gained from AI-driven analytics can identify new market opportunities and enhance customer experiences, driving revenue growth. Investing in such forward-thinking solutions demonstrates our commitment to staying ahead of the industry and continuously delivering value to our stakeholders
To further explore how AI-driven solutions can enhance business operations, check out our article on agile requirements engineering in data and machine learning projects. Learn how structured, agile methodologies can streamline AI adoption and improve project outcomes.