Enhancing Enterprise Data Collection through Interactive Template-Filling Agents with Localized Language Models

Nilesh Shankarrao Khedkar , Sujin Suresh

Large language models, template filling, interactive data collection, enterprise systems, conversational AI, local deployment.

Structured user data gathering in enterprise environments is critical but sometimes error-prone and boring when using traditional static forms. We propose an innovative interactive template-filling agent solution based on localized compact language models (LLMs). These agents guide users through dynamic prompts, context recall, and instant feedback to complete filled-in data form templates. We show a proof-of-concept deployment of this system with a Django-based front end and a locally run LLM (e.g., Flan-T5 or LLaMA2). Comparative evaluation with static ones on an HR onboarding task revealed statistically significant gains in data completeness (95% vs. 75%), accuracy (6% vs. 18% error rate), and user satisfaction (4.4/5 vs. 3.2/5). Our solution facilitates effective, privacy-aware data gathering, applicable in HR, legal, and customer onboarding scenarios.

Published Paper   E-Certificate

"Enhancing Enterprise Data Collection through Interactive Template-Filling Agents with Localized Language Models", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.10, Issue 6, page no.b53-b57, June-2025, Available :https://ijsdr.org/papers/IJSDR2506103.pdf

Volume 10 Issue 6, June-2025

Pages : b53-b57

Paper Reg. ID: IJSDR_303543

Published Paper Id: IJSDR2506103

Downloads: 000437

Research Area: Other area not in list

Country: Nagpur, Maharashtra, India

Published Paper PDF: https://ijsdr.org/papers/IJSDR2506103

Published Paper URL: https://ijsdr.org/viewpaperforall?paper=IJSDR2506103

DOI: https://doi.org/10.56975/ijsdr.v10i6.303543

ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Publisher: IJSDR(IJ Publication) Janvi Wave

This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition