case studies

4 Jun 2025

A production application to support survivors of human trafficking

DrivenData developed Freedom Lifemap, a digital tool designed to support survivors of human trafficking on their journey toward reintegration and independence.

The organization¶

EverFree develops and scales transformative solutions to end human trafficking so that all people can thrive in freedom and dignity. EverFree provides comprehensive, effective care for survivors of exploitation, and unites partners and communities to measure impact, improve care, and stop exploitation.

The challenge¶

As of 2021, an estimated 50 million people worldwide were living in modern slavery, forced to work or marry against their will. EverFree sought to rapidly develop a production version of Freedom Lifemap (FLM), a research-backed, participant-centered tool for survivors to assess their strengths and vulnerabilities using 49 indicators across the six areas of well-being that define freedom. The application had to provide a scalable solution, enabling service providers to offer personalized and holistic care across a broad spectrum of needs, from counseling to employment services.

The approach¶

Leveraging our expertise in building secure, data-driven platforms, we worked closely with EverFree to define essential features for launch. These included user management, secure data sharing, and holistic tracking of survivors' progress. The application was built using Django for its robust backend capabilities and Vue.js on the frontend to handle real-time updates and lightweight interactivity, ensuring a smooth and responsive user experience. The application also provides offline functionality for survey facilitation—designed to be simple, robust, and automatic—which enables facilitators to use FLM in more remote areas without the risk of data loss. Modern branding and straightforward interface provide a clean, user-friendly experience.

EverFree Freedom Lifemap screenshot — Example lifemap for a participant. Fake data is shown to protect participant privacy.

The results¶

DrivenData did an outstanding job building our Freedom LifeMap platform, providing us with innovative solutions to visualize complex data and track survivor pathways. Their expertise and dedication were invaluable in creating a tool that enhances our impact and helps us better support vulnerable populations.

Katie Rootlieb, Chief Operating Officer, EverFree

Today, EverFree’s Freedom Lifemap technology connects survivors with individualized care and strengthens organizations with data to guide and improve programs, measure outcomes, and stop exploitation. Working with survivors, case workers use the assessment to identify priorities and develop individualized care plans. Since the launch of the new platform in August 2024, over 1,700 assessments have been conducted for over 1,500 survivors and nearly 200 users across 23 organizations are actively using the tool.

Our real-world impact

All projects

Partners: Max Planck Institute for Evolutionary Anthropology, Arcus Foundation, WILDLABS

Automating wildlife identification for research and conservation

Detected wildlife in images and videos—automatically and at scale—by building the winning algorithm from a DrivenData competition into an open source python package and a web application running models in the cloud.

Partners: Private sector, social sector

Building LLM solutions

Built solutions using LLMs for multiple real-world applications, across tasks including semantic search, summarization, named entity recognition, and multimodal analysis. Work has spanned research on state-of-the-art models tuned for specific use cases to production ready retrieval-augmented AI applications.

Partners: The World Bank, The Conflict and Environment Observatory

Identifying crop types using satellite imagery in Yemen

Used satellite imagery to identify crop extent, crop types and climate risks to agriculture in Yemen, informing World Bank development programs in the country after years of civil war.

Partners: Bureau of Ocean Energy Management, NOAA Fisheries, Wild Me

Protecting endangered beluga whales with computer vision

Designed and administered a computer vision challenge that produced state-of-the-art machine learning models to identify and match individual endangered beluga whales from photo surveys.

Partners: ReadNet

Crowdsourcing solutions for AI assisted early literacy screening

Ran a machine learning challenge to develop automatic scoring methods for audio clips from literacy screener exercises. Automated scoring can help teachers quickly and reliably identify children in need of early literacy intervention.

Partners: IDEO.org

Illuminating mobile money experiences in Tanzania

Analyzed millions of mobile money records to uncover patterns in behavior, and then combined these insights with human-centered design to shape new approaches to delivering mobile money to low-income populations in Tanzania.

Partners: Insecurity Insight, Physicians for Human Rights

Tracking attacks on health care in Ukraine

Built a real-time, interactive map to visualize attacks on the Ukrainian health care system since the Russian invasion began in February of 2022. The map will support partner efforts to provide aid, hold aggressors accountable in court, and increase public awareness.

Partners: Wellcome

Addressing algorithmic bias in medical research

Conducted a literature review to understand the current state of bias identification & mitigation in mental health research, and synthesized recommended best practices from the field of machine learning.

Partners: CABI Plantwise

Mining chat messages with plant doctors using language models

Automated recognition of agricultural entities (such as crops, pests, diseases, and chemicals) in WhatsApp and Telegram messages among plant doctors, enabling new ways to surface emerging trends and improve science-based guidance for smallholder farmers.

Partners: NASA

Monitoring water quality from satellite imagery

Created an open-source package to detect harmful algal blooms using machine learning and satellite imagery. Included running a machine-learning competition, conducting end user interviews, and engineering a robust, deployable pipeline.

Partners: Data science company foundation

Matching students with schools where they are likely to succeed

Used machine learning to match students with higher education programs where they are more likely to get in and graduate based on their unique profile, with a focus on backgrounds traditionally less likely to attend college or apply to more competitive programs.

Partners: Fair Trade USA

Mapping fair trade products from source to shelf

Visualized the flow of fair trade coffee products from the farms where they are grown to the stores where they are sold, connecting the nodes in supply chain transactions and increasing transparency for customers and auditors.

Partners: University of Maryland

Processing multimodal tutoring data

Built well-engineered data pipelines to extract machine learning features from audio, video and transcript data collected from online tutoring sessions, enabling a team at the University of Maryland to study how relationship-building affects student outcomes.