CUI Marking Tool

Detection, identification and protection of sensitive and confidential information

AI-Enhanced Facility Finder

Many facilities are required to register for industrial stormwater permits but do not do so. To find unpermitted facilities, EPA personnel use approaches that are time-consuming,…

Living Literature Review: Semi-automated Literature Screening

The Agency conducts reviews of scientific literature in many contexts, including periodic revision of NAAQS as mandated by the Clean Air Act, other standards, but also one-time as…

Using machine learning methods to analyze drivers of water quality

To increase our understanding of drivers of water quality.

RCRA PA

Risk scoring of Large Quantity Generators (LQGs) to support RCRA inspections

CWA PA

Reducing staff time and better identification of potential violators

Budget Area Topic Classification Tool

The Budget Area Topic Classification Tool uses a pre-trained Bidirectional Encoder Representations from Transformers (BERT) model ('bert-base-uncased') to classify proposals into…

CAA PA

Reducing staff time and better identification of potential violators

RMP Risk Modeling

To identify facilities with Risk Management Plans (RMP) under the Clean Air Act (CAA) that have an elevated risk of accidents

AI voice over

The AI system generates temporary synthetic voice-over using text-to-speech services (e.g., Eleven Labs, WellSaid Labs) to convert scripts into placeholder audio for video drafts.…

Regulation Statutory and Common Name Indexing

Compliance OCC staff frequently need to reference regulations by both their alphabetical identifiers (e.g., Regulation Z) and their full statutory names. Manually searching for th…

AskBEP AI ChatBot

The AskBEP chatbot addresses the challenge of quickly and consistently accessing policy information within the BEP community. Employees often need clear, accurate answers without…

Sub-Asset Maintenance Model

This model helps reduce downtime by forecasting when sub-asset machines will need maintenance, enabling proactive servicing and improved asset reliability.

Ink and Paper Consumption Forecast (IPCF)

The Ink and Paper Consumption Forecast (IPCF) AI model is intended to predict: 1. Ink mileage predictions based on ink type and associated denom; 2. Ink consumption predictions ba…

Inventory Replenishment Forecast

This model helps reduce supply chain disruptions by forecasting vendor performance and item stockouts. It enables proactive sourcing decisions, improves inventory planning, and st…

IDV Model

This model helps forecast long-term inventory turnover to improve IDV utilization and support proactive funding requests.

Anomaly Detection for Data Quality

Anomaly detection model designed to identify potentially erroneous data loads in TCR data. Uses an isolation forest model with aggregated data and automatically runs daily.

Stress Testing Scenarios with Deep Learning

Pilot project to explore neural-network based machine learning methods for creating stress testing scenarios and estimating PnL (profit and loss) on FO (Futures and Options) portf…

MPD Entity Risk Modeling

Entity-level risk modeling project. Use statistical and probabalistic models to predict firms experiencing changes in capital levels. Very early stage R&D effort.

The Advanced Trade Analytics Platform (ATAP)

ATAP aims to provide insights into trends and behaviors in trade activity to support a proactive risk management and enforcement posture in the agency’s mission execution.

Critical Infrastructure Network Anomaly Detection

CyberSentry currently ingests hundreds of terabytes of data from Critical Infrastructure Partners every single day. At petabyte-scale over all collected network data, CyberSentry…

Malware Reverse Engineering

This AI capability uses deep learning to assist CISA analysts with understanding the content of malware samples, automating tasks such as triage and indicator extraction.

Voice Analytics for Investigative Data

Investigative Prioritization Aggregator

This use case intends to solve the problem of overwhelming data volumes that make it difficult for HSI personnel to prioritize high-value targets in criminal investigations.