Artificial intelligence for your data
Leverage your data with Softia’s AI. By combining AI and custom development, we strengthen your information systems with solutions that harness the potential of your data to better automate your processes, optimize your decision-making and foster your innovation.At Softia, the development of artificial intelligence (AI) solutions is based on a structured methodology that ensures a precise response to customer needs, while guaranteeing flexibility and performance. Our AI solutions, integrated with information systems, transform data into strategic insights, enabling faster, better-informed decision-making. Our solutions are designed to be as scalable as they are adaptable, guaranteeing the evolution and transformation of your information systems in line with business needs and market developments.
Our methodology to leverage your data with Softia's AI
First and foremost, it is essential to have a clear understanding of the customer’s objectives and the operational context in which the solution will be integrated:
- Business needs analysis : We identify the issues and business processes where AI can bring value, such as automation, prediction or pattern recognition.
- Definition of the objectives of the AI solution : We clarify the expected results and define the performance indicators (KPIs) to measure the success of the solution.
Data is the fuel of any AI solution. This stage is crucial for guaranteeing the quality of the information on which the solution will be based:
- Identifying data sources : The Softia team identifies relevant internal and external data sources.
- Cleaning and structuring : We check the quality of the data by eliminating inconsistencies and structuring the information.
- Dataset preparation : We create the training and validation datasets for the AI model.
Depending on the objectives and available data, we design the AI model best suited to the customer’s needs:
- Algorithm selection : Softia selects the appropriate algorithms (machine learning, deep learning, natural language processing, etc.).
- Model training : We train the model using the training datasets, adjusting the parameters to obtain optimum accuracy.
- Evaluation and optimisation : Finally, our team tests the model on validation data and makes the necessary adjustments to maximise its reliability.
Once the AI model has been validated, it is integrated into the customer’s infrastructure:
- Development of a user interface : We create an intuitive interface so that end users can interact easily with the solution.
- Integration of the AI model : Our team connects the model to existing systems (ERP, CRM, etc.) and data flows for complete automation.
- API configuration : We set up the programming interfaces needed to enable seamless communication between the AI solution and the customer’s systems.
Before deployment, the solution is tested to ensure that it meets expectations and is robust.
- Performance and security testing : We assess the responsiveness, security and stability of the solution in the customer’s environment.
- Functional validation : We involve end-users to ensure that the solution meets operational requirements and delivers an optimal experience.
- User acceptance : We then carry out tests in real-life situations to gather final adjustments before official deployment.
Once the solution has been validated, it is put into production and users are trained to make full use of it.
- Secure deployment : We ensure that production is rolled out progressively or in big-bang mode, depending on the customer’s requirements.
- Team training : We train users to get to grips with the solution and learn the best practices for getting the most out of it.
AI requires continuous attention to maintain its effectiveness and adapt to changes in the business.
- Corrective maintenance : Our team corrects any bugs and ensures that the solution works properly.
- Evolutionary maintenance : We add new functionalities or adapt the model to new data and requirements.
- Performance monitoring and adjustments : Finally, we monitor the AI’s performance to ensure that it is in line with the initial objectives and to optimise its performance on a regular basis.
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“With twenty years’ experience in all sectors of activity, from industry and government to SMEs and SMIs, we have been confronted with the greatest diversity of data models and the challenges of optimizing their use. The transition to AI has become an obvious part of our service offering to our customers, while remaining attentive to the simplicity of implementing solutions in the field.”