Case Study: U.S. Air Force SEEK EAGLE Office reduces store certification research to minutes with Tamr Inc.

Air Force SEEK EAGLE Office and Tamr Expedite the Air Force's Mission Capabilities

The U.S. Air Force SEEK EAGLE Office (AFSEO) needed to speed certification of aircraft “stores” but was hampered by decades of siloed, structured and unstructured data — more than 13 TB without metadata — limited personnel and budget, and a time‑consuming, non‑scalable training process for new engineers. To address this, AFSEO worked with Tamr Inc., deploying Tamr’s machine‑learning data mastering and natural language processing capabilities to index, tag and surface historical test and technical documents.

Tamr Inc. mined technical content, applied NLP and ML to create 4.4 billion metadata tags across 22 information types, and fed organized tags into AFSEO’s Cloudera data lake for Solr/Banana search. The result: store‑certification research that once took hours or days is reduced to minutes, engineers’ workloads and onboarding time dropped, the Air Force expanded the range of approved stores, and substantial cost savings were achieved by keeping analysis in‑house.

U.S. Air Force