Quanterha presented its new functionality of improvement of requirements with generative artificial intelligence (IAG). This innovation allows optimizing the quality and precision of estimates from the initial phase of the project, complementing the already existing intelligent estimation of Quanter, which integrates a LLM model (Large Language Model) to obtain faster and more precise estimates.
The improvement of requirements takes advantage of AI capabilities to perform a complete analysis of user requirements or stories before proceeding to estimate. Once the requirements in natural language are introduced, Quanter proposes a new version with improvements based on best practices and standards of the industry, or following the own client defined rules. This ensures that the requirements are clear, complete and aligned with the client’s work methodology.
“The quality of an estimate depends largely on the clarity of the requirements. With this new functionality, we make the equipment work with better defined requirements without additional effort, which directly impacts the precision of their estimates and the efficiency of their projects, ”explains Dacil Castelo, CEO of Quanter and LEDAMC.
The necessary change in project planning
For years, the software industry has dealt with descriptions of ambiguous, incomplete or poorly structured requirements, which negatively affected estimates. These problems resulted in erroneous calculations, endless revision rounds and unnecessary costs. With the improvement of requirements, Quanter ends a problem that has affected software development for too long. Quanter AI not only reformulates the text, but also explains how each requirement has interpreted, raises relevant questions and justifies each suggested improvement. This offers a valuable context for the teams to understand why the changes benefit the project and how they impact the final estimate.
This innovation eliminates uncertainty in project planning, facilitating equipment working with more precise information from the first moment. In addition, improved requirements can be exported to other tools such as Gira, which are synchronized with Quanter, or downloaded in a file for use in different environments, ensuring that the project documentation is precise and reusable.
Less errors and more confidence in each estimate
“We saw that there was a great gap between how the teams expressed their requirements and how they translated into estimates. With the artificial intelligence integrated in Quanter we have managed to close it, obtaining better requirements than the intelligent quanter estimate also processes with greater precision, ”says Dacil Castelo. Thanks to these advances, development managers and development teams can optimize times, minimize errors and ensure that their estimates reflect more fidelity the necessary real effort.
The functionality is now available for Quanter users and is natively integrated into its platform, without the need for additional configuration. With this new tool, Quanter reaffirms its commitment to innovation and continuous improvement, offering solutions that generate a real impact on productivity and software quality.
