Abstract

OmniDoc-AI is a modular, production-ready assistant for research summarization, Legal Summarization, form analysis, and intelligent querying. Designed with a hybrid retrieval framework powered by multi-provider LLMs and vector databases, it enables structured extraction from legal, financial, and academic documents. With its Challenge Me Mode, auto-structuring, and smart summarizer, OmniDoc-AI bridges the gap between raw data and actionable insights.

Introduction

The exponential growth of unstructured textual data in research, legal, and finance sectors demands intelligent tools that go beyond generic summarization. OmniDoc-AI solves this by integrating Retrieval-Augmented Generation (RAG), prompt engineering, and modular design to build a scalable document intelligence pipeline.

Methodology

OmniDoc-AI utilizes LangChain for chaining tasks across LLM providers. A dual-retriever setup ensures semantic and keyword-based filtering of context. Challenge Me Mode simulates adversarial querying, while form parsing modules extract tabular and grouped logic from structured inputs. Embedding pipelines leverage FAISS and Chroma for fast and accurate vector retrieval.

Experiments

The assistant was tested on arXiv papers, legal filings, and startup onboarding forms. Benchmarks focused on summarization quality (ROUGE scores), response latency, and logical grouping accuracy. Ablation studies were conducted on vector database choice, prompt phrasing, and retriever configurations.

Results

OmniDoc-AI demonstrated significant gains in structured summarization and query accuracy. ROUGE-L improved 18% over baseline, and grouped form extraction reached over 90% accuracy across datasets. Challenge Mode introduced robustness under diverse questioning strategies. Latency optimization through caching and streaming reduced response times by 40%.

Conclusion

OmniDoc-AI sets a new benchmark in smart document processing. With its modular architecture, adaptive querying, and application-ready deployment, it supports a wide range of domains including LegalTech, FinTech, and EduTech. Open-sourced under Apache 2.0, it invites collaboration to shape the future of intelligent document workflows.