[2023- 2026] AI Document Assistants and LLM Applications (LLM + Retrieval Augmented Generation)

Organizations frequently accumulate large volumes of internal documentation — PDFs, reports, manuals, and research papers. While this information is valuable, it can be difficult for teams to quickly locate the specific knowledge they need. Retrieval Augmented Generation (RAG) systems combine modern large language models with document retrieval techniques to enable conversational interaction with large collections of documents.

In a RAG architecture, uploaded documents are processed and converted into vector embeddings that represent their semantic meaning. These embeddings are stored in a vector database and used to retrieve the most relevant passages when a user asks a question. The language model then generates a response grounded in those retrieved documents. This approach allows users to ask natural language questions and receive accurate answers derived directly from their own knowledge base rather than generic model knowledge.

Our team implemented a lightweight AI document assistant integrated directly into a WordPress site. Stakeholders could upload PDF documents through the site interface and then interact with the system by asking questions about the content, enabling faster knowledge discovery and improved collaboration across teams.

[2021-2023] GIS Tracking & Map-Based Data Visualization

Modern organizations often collect large amounts of geospatial data, but without the right tools, this information can be difficult to interpret. Geographic Information Systems (GIS) combined with modern web technologies allow organizations to visualize events, detections, and movement patterns directly on interactive maps. By combining spatial databases, map tile providers, and web-based visualization frameworks, GIS applications transform raw location data into actionable insights that can be explored in real time.

These systems are particularly valuable in operational environments where situational awareness matters. Interactive mapping dashboards can display tracks, events, sensor detections, and historical trends across geographic regions. Users can zoom, filter, and analyze patterns in ways that would be impossible when reviewing raw log files or spreadsheets. GIS-based tools are widely used in industries such as logistics, defense, environmental monitoring, and infrastructure management because they help teams quickly understand where events are happening and how they evolve over time.

Our team helped a client begin understanding their complex system log data by developing a visualization platform that mapped and displayed track detections in an interactive GIS web application.

[2021-2022] Graph Database Visualization Platform

Many modern datasets contain relationships that are difficult to model using traditional relational databases. Graph databases are designed specifically to store and query connected data by representing entities as nodes and relationships as edges. This structure makes them particularly effective for analyzing networks such as social relationships, recommendation systems, supply chains, and professional networks. Graph technologies allow organizations to explore patterns, clusters, and connections that might otherwise remain hidden in traditional tabular data.

When combined with interactive visualization tools, graph databases become powerful platforms for discovery and exploration. Network visualizations allow users to visually explore how individuals or entities are connected, identify influential nodes within a network, and uncover communities or clusters. Modern JavaScript graphing libraries enable real-time exploration where users can zoom into portions of the network, filter relationships, and dynamically query the underlying database.

We provided consultation and developed a custom network visualization platform for a client in the film industry using a graph database powered by Neo4j and interactive graph visualization libraries in JavaScript.