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Title
FiscalNote streamlines ML and NLP legislative-analytics model deployment on Databricks, tripling release cadence
…ployment directly correlates with a reduction in time to market for new models, FiscalNote can now deploy 3x the number of models annually, compared to their output before Databricks. Because of these substantial gains, the software company’s data science team fe…
Description
FiscalNote, a legislative and regulatory data analytics company, used Databricks MLflow and Model Serving to automate tracking, deployment and no-disruption updates of its machine learning and NLP models, which perform tasks like legislative outcome sentiment analysis and binary classification of how a congressperson will vote. The change let FiscalNote deploy ML models 3x faster and increased the number of models it ships annually compared to before Databricks.
…xtract, transform and load (ETL) pipelines to ingest data from various sources, perform NLP tasks (e.g., summarizing and sentiment analysis) and execute binary classification workflows (e.g., analyzing whether a congressperson will/will not vote on a particular bill). Eidelman elaborated on the progress FiscalNote has seen thus far, “We’ve only…
Company
FiscalNote
…increasing analyst productivity. Facing major hurdles in AI/ML model deployment FiscalNote is a software company at the forefront of analyzing government data and legislative processes. Leveraging data science and machine learning, FiscalNote provides actionable in…
Industry
Financial Services
…cal resource in the legislative and regulatory domains. Share this post Details Industry : Digital and AI-Native Business , Financial Services Use Case : Artificial Intelligence Cloud : AWS Product : Agent Bricks Ready to…
Problem
FiscalNote's data teams were hampered by cumbersome, fragmented processes to stitch together components essential for AI model deployment such as tracking artifacts and builds, which limited their cadence for deploying and updating AI models to around once a year, required extensive custom coding to avoid disrupting existing models, and suffered from a lack of discoverability of essential data assets.
…mponents essential for model deployment, such as tracking artifacts and builds. This extensive, fragmented process limited the team’s cadence for deploying and updating certain AI models to around once a year. Vlad Eidelman, Chief Technology Officer at FiscalNote, explained, “We’re primar…
Solution
FiscalNote adopted Databricks MLflow to manage and deploy ML models, reducing time spent tracking artifacts, model versions and notebooks, and layered on Databricks Model Serving to deploy, manage and monitor models without needing to build APIs or plan no-disruption deployments manually, supporting ETL pipelines, NLP summarization and sentiment analysis, and binary classification workflows.
…rket and scaled up their model deployments to an as-needed basis. Additionally, FiscalNote leveraged Databricks Model Serving , a comprehensive service used for deploying, managing and monitoring machine learning models, whether they are developed by Databricks or sourced from other providers. Mode…
Business value
FiscalNote reduced bottlenecks with their data platform teams and can now deploy 3x the number of models annually compared to their output before Databricks, reducing time to market and allowing employees to be more productive and effective.
…fits, stated, “Databricks allows our team to build and deploy ML models faster, reducing time to market and allowing our employees to be more productive and effective.” With increased speed in their processes and greater productivity from their e…
Technology
MLflow, Databricks Model Serving, Agent Bricks
…ve Business , Financial Services Use Case : Artificial Intelligence Cloud : AWS Product : Agent Bricks Ready to get started? Try Databricks for free Learn more about our product Talk…
AI capabilities
Natural Language Processing, Machine Learning
…data — whether at the local, state or federal level — FiscalNote has developed machine learning (ML) and natural language processing (NLP) technologies to give customers access to policy and geopolitical insights. The software comp…
Use case type
Predictive operations
…rious sources, perform NLP tasks (e.g., summarizing and sentiment analysis) and execute binary classification workflows (e.g., analyzing whether a congressperson will/will not vote on a particular bill). Eidelman elaborated on the progress FiscalNote has seen thus far, “We’ve only…
Headline outcome
…ote CUSTOMER STORY Scaling global policy and intelligence for a better tomorrow 3x Faster ML model deployment Established in 2013 to transform access to legislative and regulatory data — wh…
Deployment model
cloud
…and AI-Native Business , Financial Services Use Case : Artificial Intelligence Cloud : AWS Product : Agent Bricks Ready to get started? Try Databricks for free Learn more…
Deployment options
cloud
…and AI-Native Business , Financial Services Use Case : Artificial Intelligence Cloud : AWS Product : Agent Bricks Ready to get started? Try Databricks for free Learn more…
