Advanced RAG Engineering for real estate due diligence AI Agent

What does Mapline do?

Mapline.AI is a US-based startup on a mission to transform how real estate developers conduct due diligence. By utilizing the power of artificial intelligence, the tool drastically reduces the time and costs associated with traditional due diligence processes. Instead of weeks of research and site visits, Mapline.AI enables remote, comprehensive evaluations of potential developments in a matter of minutes. This innovation not only accelerates decision-making but also lowers the barrier to entry, making professional due diligence more accessible to developers of all sizes—without requiring them to be on-site or deeply familiar with local legal complexities.

How does Vstorm cooperate with Mapline?

The overarching goal was to create an AI Agent capable of conducting in-depth due diligence for real estate development projects across various U.S. municipalities. This required integrating multiple high-volume data streams – geospatial, environmental, municipal, legal, and infrastructural – while ensuring the accuracy of insight-based reports. Percel-specific variables include land use, zoning class, total acres, proposed land use, proposed zoning class, open space, greenways, wetlands, surface water, watersheds, adjacent roads, transportation plans, major roads, local roads, conservation elements, greenways & trails and access easements. Off-the-shelf AI tools were prone to the limitation of adjusting to specific workflows and technical environments and, as a result, “hallucination” when faced with the sheer complexity and variability of these data sets. Further, the differences in municipal regulations added another layer of difficulty, necessitating a custom AI solution

Vstorm’s mission was to build a robust AI Agent that seamlessly integrates these disparate data sources, automates labor-intensive analyses, and delivers actionable insights in near real-time. By focusing on tailor-made AI solutions instead of a generic platform, Vstorm enabled Mapline.AI to provide real estate developers with a highly efficient, cost-saving approach. We took care of full process of AI Agent engineering, including the engineering consulting part to design the appropriate solution.

1. Diagnose the engineering challenge. Conducted a detailed analysis of the real estate due diligence process and the constraints posed by diverse data types and municipal regulations.
2. Feasibility study. Assessed the project’s technical viability to identify realistic goals and milestones, balancing complexity, time, and budget.
3. Solution design. Designed a system architecture and infrastructure plans.
   • Chose an optimal large language model and advanced RAG methodologies.
   • Determined observability, compliance, and security features for post-deployment.
   • Selected technology components – such as a self-hosted vector database and an AI orchestration framework.
4. Defining business-focused metrics. Established clear performance indicators, including reduced due diligence time, cost savings, and improved decision-making accuracy.

“Once we understood the challenge, we chose to implement a more robust OCR solution. Standard text extraction tools struggled with the complexity of real estate documents, particularly those with intricate tables. By adopting a specialized OCR setup, we achieved more accurate parsing of these challenging documents, ensuring that LLMs receive clean, reliable text for analysis.”
AI Lead Engineer – Wojciech Achtelik 

One of the most important elements of the project was to design a tailored RAG (Retrieval-Augmented Generation) suitable for the process workflow of analysis of legal, environmental, and planning documents and automatically generate reports. We’ve moved beyond basic RAG by implementing several custom, advanced features for higher accuracy and relevance:

1. Parsing complex documents with specialized OCR. Real estate documents, especially PDFs, can be challenging with complex tables, images, and varied layouts. Standard text extraction often fails. While Mistral OCR demonstrated impressive performance on standard benchmarks, it consistently underperformed when applied to our most challenging documents. In contrast, LlamaParse Premium delivered superior results, accurately parsing complex tables where others faltered. Choosing the right OCR tool ensures our AI gets a clean, precise text to work with, which is critical for reliable analysis.
2. Metadata filtering. Finding the exact documents needed for a specific property and report section is key. We chose the Milvus vector database because it allows for advanced metadata filtering. We tag documents with metadata like municipality and document type. Milvus lets us instantly query only documents matching the correct location and type, ensuring the AI receives highly relevant information, not just generally similar content.
3. Custom re-ranking. Not all relevant documents are equally important. Our system includes a custom re-ranking step. After finding potentially relevant documents, it intelligently boosts the score of documents coming from sources we know are most critical or authoritative for certain tasks.
4. Dynamic data extraction. To make the AI’s analysis truly specific to the property, we automatically extract key details from related geospatial data – things like zoning codes, land use designations, adjacent roads, or nearby wetlands. This specific, structured data is fed directly into the AI’s prompt along with the document text, giving it rich context beyond just the documents themselves, leading to more insightful and tailored report sections.

These advanced techniques – specialized OCR, precise filtering with Milvus, custom re-ranking, and dynamic data injection – are what allow our system to generate detailed, accurate, and highly relevant due diligence reports far more efficiently than traditional methods.

Results

“We are performing due diligence on a 90-acre land, which includes creating a detailed sketch plan and meeting with multiple consultants. By leveraging Mapline’s insights, we can streamline this process, potentially saving $2,000–$3,000 while significantly boosting efficiency.”  — Mapline.ai end-user

The work between Vstorm and Mapline.AI resulted in an AI Agent built specifically for real estate due diligence, designed to fit business goals and workflow. This tool takes what used to be weeks of due diligence and gets it done in minutes, saving developers thousands of dollars per project while keeping the accuracy spot-on. For anyone using it, that means quicker decisions and lower costs, whether you’re a small developer or a bigger player.

A big part of why this works so well is how Vstorm set it up to be reliable and secure. We added observability tools like LangSmith to keep an eye on how the AI Agent runs in real-time and to track and refine the AI Agent’s behavior, ensuring consistent performance. Strict encryption and compliance steps protect all the sensitive data, meeting the real estate world’s strict rules. Built with a future-ready architecture, the AI Agent handles increasing data volumes without compromising performance, ensuring it won’t falter as Mapline.AI grows or as real estate datasets expand.

We also made sure Mapline.AI’s team could run things on their own. The system lets them update stuff like zoning rules or property details without needing us to step in, giving them full control to manage the AI Agent however they need. On top of that, we kept improving it by listening to feedback from their team and users. Regular updates based on what they said helped us fine-tune the system, making it more accurate and dependable over time, ready for whatever changes come up in real estate.

And it’s not just about speed—this tool catches things manual reviews often skip, like small zoning quirks or environmental details that could matter later. That gives developers clearer, more useful info to work with, so they can decide with confidence. With Vstorm’s help, Mapline.AI now has a system that’s secure, grows with them, and makes due diligence a lot easier and smarter than it used to be.