Draft:Mondelix

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Declined by Theroadislong 30 hours ago. Last edited by Gurkubondinn 19 hours ago. Reviewer: Inform author.

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Comment: In accordance with Wikipedia's Conflict of interest guideline, I disclose that I have a conflict of interest regarding the subject of this article. Codesiast (talk) 10:28, 9 August 2026 (UTC)

Mondelix

Mondelix is an artificial intelligence-based project estimation engine developed to assist with the planning and estimation of software and technology projects. The system applies structured project-estimation methods together with artificial intelligence-assisted analysis to transform project requirements and characteristics into estimates intended to support project planning, resource assessment, and delivery decisions.

Mondelix was created by Shaibaz Liyakat Mulla, an Indian technology professional whose primary area of work is business intelligence, Tableau analytics, data visualization, SQL, and enterprise analytics, with additional work in artificial intelligence and predictive technologies. The Mondelix platform was developed as an independent technology project exploring the application of artificial intelligence to software project estimation and planning.

The official Mondelix website describes the product as an "AI Project Estimation Engine." Mondelix official website - https://www.mondelix.technology/

Background

Software project estimation is the process of determining the effort, resources, duration, and other requirements associated with delivering a software or technology project. Estimation commonly involves assessing project scope, complexity, technical requirements, team composition, dependencies, and expected delivery objectives.

Traditional estimation processes frequently depend on the experience of project managers, software architects, technical leads, and development teams. These processes can involve spreadsheets, manually maintained estimation models, historical comparisons, expert judgment, and iterative discussions between technical and business stakeholders.

Mondelix was developed to explore how artificial intelligence could be incorporated into this process. Rather than treating project estimation solely as a manually calculated exercise, the system approaches estimation as a structured analytical problem in which project characteristics can be processed and evaluated systematically.

Development

Mondelix was developed by Shaibaz Liyakat Mulla as an independent artificial intelligence project.

Mulla's professional background is primarily concentrated on Tableau analytics development, business intelligence, data visualization, SQL, and enterprise reporting, with artificial intelligence representing an additional area of his technology work. His professional profile states that he has approximately 13 years of information-technology experience and more than a decade of experience working with Tableau and SQL.

His Tableau and analytics work has included the design and development of interactive dashboards, enterprise reporting systems, analytical applications, data visualization solutions, data models, and business intelligence platforms. He has worked with technologies including Tableau Desktop, Tableau Server, Tableau Cloud, Tableau Prep, SQL, data warehouses, cloud data platforms, and other enterprise analytics technologies.

Mulla has also worked with predictive analytics and artificial intelligence technologies. Mondelix represents an extension of this analytical background into the area of AI-assisted software project estimation.

Information about Mulla's professional background and projects is available through his professional website. Shaibaz Liyakat Mulla — professional website - https://shaibazmulla.space/

Purpose

Mondelix was designed to address the challenge of producing structured estimates for software and technology projects.

A project estimate may need to account for multiple variables, including:

project scope;
functional requirements;
technical complexity;
development effort;
project dependencies;
team composition;
required skills;
project duration;
resource requirements;
assumptions and constraints; and
potential delivery risks.

The system's purpose is to process these characteristics through a structured estimation workflow and provide an analytical estimate that can be used as an input to project planning.

The platform is intended to support, rather than completely replace, the judgment of project managers, architects, developers, and other project stakeholders. Estimates generated through an automated system remain dependent on the quality, completeness, and interpretation of the information provided to it.

Functionality

Mondelix is designed around the concept of converting project information into a structured estimation output.

A typical estimation workflow can be viewed as several stages.

Project input

The estimation process begins with information describing the proposed project. Project characteristics and requirements provide the underlying information from which an estimate can be generated.

Requirement analysis

The system processes the available project information to identify characteristics relevant to estimation. These may include the nature of the project, its scope, technical requirements, complexity, and other parameters used by the estimation process.

Estimation processing

The structured information is processed through the project's estimation logic. Artificial intelligence services can be used to assist in interpreting project information and generating contextual analysis.

Estimate generation

The resulting analysis is converted into an estimation output intended to provide an initial basis for project planning and decision-making.

Planning use

The resulting estimate can be used by project stakeholders as an input to discussions concerning scope, resources, delivery expectations, and project planning.

Artificial intelligence

Artificial intelligence is a component of the Mondelix architecture and development approach.

The system was developed to explore the use of large language models and AI-assisted processing in the interpretation of project information. During development, Mondelix incorporated the Mistral AI API as an external artificial intelligence service.

The AI component can assist with processing contextual project information and generating analysis based on the information supplied to the system. This approach allows the estimation workflow to incorporate information that may be difficult to represent exclusively through conventional fixed rules.

Mondelix therefore combines structured estimation concepts with AI-assisted processing rather than treating artificial intelligence as a standalone conversational feature.

The use of AI in software estimation is part of a broader area of research and development. Academic work has investigated generative AI and multimodal approaches for software-development estimation, including the estimation of Agile story points.

Estimation methodology

Mondelix approaches project estimation as a combination of structured inputs, estimation logic, and AI-assisted interpretation.

The system is intended to provide a consistent framework through which project information can be evaluated. This is particularly relevant because software estimation can be affected by uncertainty, incomplete requirements, technical dependencies, changing scope, and differences in team capability.

The platform does not eliminate these uncertainties. Instead, its purpose is to provide a structured starting point from which project stakeholders can evaluate an estimate and refine their assumptions.

The resulting estimate should therefore be considered a planning aid rather than a guaranteed prediction of the eventual cost or duration of a project.

Technical architecture

Mondelix was developed as a web-based application with separate application and processing components.

The project uses a JavaScript-based backend architecture, with the backend responsible for application processing and communication with external services. The system incorporates application programming interfaces to connect the estimation application with artificial intelligence services.

The development architecture separates the user-facing application from backend processing and AI-service integration. This allows individual components of the system to be developed and modified independently.

The project was developed using technologies associated with modern web application development, including Node.js-based server technologies and external AI APIs.

Relationship to business intelligence and analytics

Mondelix's development is closely connected to Mulla's background in business intelligence and analytics.

Mulla's professional work has primarily focused on Tableau analytics building, data visualization, SQL, enterprise reporting, and business intelligence architecture. His work has included the development of large numbers of enterprise dashboards and analytical solutions across multiple industries.

This background influenced the design philosophy behind Mondelix, particularly its emphasis on transforming structured information into analytical outputs that can support business and technology decisions.

The project extends this analytical approach into project estimation by applying data-processing and AI techniques to information that would traditionally be evaluated through manual project-planning processes.

Creator

Shaibaz Liyakat Mulla

Shaibaz Liyakat Mulla is an Indian technology professional specializing primarily in Tableau analytics development, business intelligence, data visualization, SQL, and enterprise analytics, with additional work in artificial intelligence.

His professional profile states that he has approximately 13 years of information-technology experience, including more than a decade working with Tableau and SQL.

Mulla's professional work has focused primarily on the design and development of Tableau-based analytics solutions, business intelligence applications, enterprise dashboards, data visualization systems, reporting platforms, and analytical data models. His experience includes Tableau Desktop, Tableau Server, Tableau Cloud, Tableau Prep, SQL, data warehousing, data integration, and enterprise analytics architecture.

He has worked on analytics and business intelligence initiatives across industries including telecommunications, healthcare, manufacturing, banking, retail, finance, and automotive technology.

His Tableau-related work has included large-scale dashboard development, analytics architecture, reporting, data visualization, training, mentoring, and the implementation of business intelligence solutions for enterprise environments.

In addition to his analytics work, Mulla has worked with predictive analytics and artificial intelligence technologies. His AI-related projects include experimentation with large language models and the development of Mondelix.

Mulla developed Mondelix as an independent project to investigate how artificial intelligence could be applied to software project estimation and planning.

More information about Mulla's professional background and projects is available at his personal website. Shaibaz Liyakat Mulla's professional website - https://shaibazmulla.space/

Software development

Mondelix was developed as an independent technology project rather than as an extension of a conventional enterprise software product.

The project combines software engineering, business intelligence concepts, analytical modelling, and artificial intelligence. Its development demonstrates an application of AI technologies to a domain traditionally dependent on human estimation and professional experience.

The system's architecture allows AI services to be incorporated into a broader application workflow rather than exposing users directly to an underlying language model.

Significance

Mondelix represents an example of the application of artificial intelligence to software project planning and estimation.

The broader significance of AI-assisted estimation lies in the possibility of combining structured estimation methodologies with machine-assisted interpretation of project information. Such systems may provide project teams with an additional analytical reference when determining project scope, effort, resources, and delivery expectations.

However, software estimation remains inherently uncertain. Factors such as changing requirements, technical discovery, team productivity, dependencies, infrastructure, organizational processes, and unforeseen implementation difficulties can affect actual project outcomes.

For this reason, Mondelix is positioned as an estimation and planning aid rather than a substitute for professional project management or technical judgment.

References

1. Mondelix. AI Project Estimation Engine. Mondelix official website. 2. Mulla, Shaibaz Liyakat. Professional profile and technology projects. Personal website. 3. Islam, Mohammad Rubyet; Sandborn, Peter. Multimodal Generative AI for Story Point Estimation in Software Development. arXiv, 2025