Aviation & Logistics · Employee Productivity AI
Employee Productivity AI: Content Generation and Intelligent Retrieval at Scale
Building retrieval and generation tools that help employees find, create, and reuse knowledge
The Client · A major US airline
Overview
A major US airline engaged Taller through a staffing partner in March 2023, with work spanning applied AI and core modernization. Taller ran six pods across AI/data and .NET/Angular rebuilds, with multi-year extensions confirmed.
The Problem
The airline’s productivity bottleneck was content generation and information retrieval. Knowledge that lived in manual workflows took hours of skilled time to find, package, and put in front of a decision-maker, and that delay compounded across a large workforce. What the airline needed was a knowledge base that responded at the speed operations required, grounded in its own trusted documents.
The Solution
Taller’s senior AI engineers built the productivity tool by combining large language models (the AI systems behind tools like ChatGPT) with retrieval-augmented generation (RAG), a technique that grounds the AI’s answers in the company’s own trusted documents rather than letting it invent them. What made it accurate at production scale was the blend of three retrieval strategies into one response path: hybrid search (matching both exact keywords and meaning, to handle specialized terminology), multi-query retrieval (rephrasing a question several ways to catch different wordings), and re-ranking (surfacing the most relevant passages before they reach the model). LangChain coordinated the process, LangGraph managed the multi-step workflows that needed more than one lookup, an automated evaluation pipeline (RAGAS) checked every answer before it was delivered, and a React interface streamed responses to the user as they generated.
The Impact
The tool cut content-generation and data-retrieval time from hours to seconds, with a measurable lift in employee engagement on the affected workflows and improved operational efficiency across the airline’s content-and-retrieval work.
