Dhaani uses a 2-step approach: design first, then code.
Combine your innovative solutions with AI's speed and knowledge to build
modular software with human-in-the-loop control.
This work is an intersection of:
Your innovative solutions drive the development process. AI amplifies your ideas, not replaces them.
Leverage AI's vast knowledge and coding capabilities to build faster than ever before.
Change and enhance parts of your software without impacting other components.
No documentation overhead. Your workflow becomes living documentation tied to your code.
AI excels at working with incomplete requirements, just like experienced developers.
From low technical to high technical users - everyone can benefit from Dhaani.
The design phase focuses on creating a data flow diagram based on the user input specification.
The coding phase then codes each process of the workflow, solving the requirement and creating an end-to-end solution. AI's efficiency and knowledge work with human creativity to generate modular, maintainable code.
Human-AI Collaboration: Both the phase involve human-AI collaboration which implements interactions based on the intelligibility protocol. This approach combines human creativity with AI's efficiency and knowledge to create software that reflects your vision.
Streamline data analysis, experiment automation, and research pipeline development.
Build data processing pipelines, ML models, and analytical tools with ease.
Develop machine learning applications and AI-powered solutions efficiently.
Analyze datasets, generate insights, and create comprehensive data analysis workflows.
Tackle complex problems like the IPARC challenge with innovative approaches.
Reliable LLM software engineering requires structured decomposition and protocol-based human interaction.
iProg revisits structured inductive programming in the LLM era, using language models not as autonomous end-to-end programmers, but as proposal generators within a human-ratified decomposition-and-synthesis process.
The latest paper presents one of the cleanest structured approaches for building reliable LLM-assisted software systems from natural-language requirements.
CAiSE 2026
IPARC at IJCLR
From specifications to code: design your data flow diagram, then generate modular Python code. Keep control, accountability and transparency.
Note: Dhaani is free for everyone to use. Download and start building your next project today!
If you use this tool, please cite Engineering Systems for Data Analysis Using Interactive Structured Inductive Programming. View BibTeX.
Have questions or feedback? We'd love to hear from you.