Austin Historical Council Meeting Search Platform
How Steeped AI transformed thousands of image-based PDF scans into a searchable database of Austin's civic history, dating back to 1869.
Steeped AI partnered with Curt Yowell to expand the AustinCouncil.app concept into a comprehensive archive of Austin City Council meetings dating back to 1869, just three decades after the city's incorporation. The historical record was trapped in thousands of image-based PDF scans, ranging from nearly indecipherable handwritten manuscripts from the 1800s to degraded typewritten documents from the 1940s. Using a combination of AI-powered OCR, machine learning pipelines, and modern web technologies, the team transformed these inaccessible archives into a searchable database of more than 10,000 historical city council meetings.
Next Level OCR
A multi-layered pipeline of AI vision models and machine learning OCR systems was developed to extract and preserve text from historical documents. Because many records contained handwritten passages, faded type, and low-quality scans, the extracted text required multiple stages of NLP validation and cross-checking using Steeped AI's data preparation service to improve accuracy and preserve the integrity of the historical record.
Searchable Transcripts + Summaries
The transcripts were transformed into accessible summaries using advanced AI models, including Claude and Gemini. These summaries, alongside the original meeting transcripts, were integrated into the AustinCouncil.app platform, creating a searchable historical archive where users can explore, search, and browse Austin's civic history across more than a century of city council records.
Topic Mapping Connecting History
Looking ahead, Steeped AI will continue partnering with Curt Yowell to enrich the archive with AI-powered topic mapping. Rather than limiting discovery to keyword searches, users will be able to explore the evolution of nuanced themes and concepts across nearly 160 years of Austin's history. From livestock, transportation, and sustainability to race relations, food culture, landmarks, street names, and prominent local figures, AI topic mapping will connect related discussions across decades revealing how the city's priorities, challenges, and identity have changed over time.
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