Bric offers an open‑source platform that lets social and behavioral science researchers collect and analyze digital data from mobile sensors, web browsers, SMS, and social‑media sources. Its modular libraries—such as Passive Data Kit, QuestionKit, and Automated Conversational Kit—provide privacy‑first data acquisition, on‑device processing, and context‑aware interventions, enabling rapid prototyping of large‑scale, secure studies without building custom infrastructure.
Funding
Funding not disclosed
Founders
Product
Problem
Researchers in social and behavioral sciences often lack accessible, privacy-preserving tools for collecting and analyzing diverse digital data streams such as mobile sensor logs, web search behavior, SMS interactions, and social media footprints. This limits the ability to conduct large‑scale, context‑aware studies on mental health, decision making, and online behavior.
Solution
Bric provides an open‑source technology platform that enables researchers to build, deploy, and manage data collection applications across mobile devices, web browsers, and messaging channels. The platform includes libraries for passive sensor acquisition, on‑device feature extraction, context‑aware survey delivery, and reinforcement‑learning driven interventions, all designed with privacy‑first principles that transmit only aggregated metrics. Collected data are stored in a standardized server framework that supports secure encryption, cross‑platform data importers, and extensible codebook generation for downstream analysis. By offering modular components such as Passive Data Kit, QuestionKit, and Automated Conversational Kit, Bric allows investigators to rapidly prototype novel study designs without building infrastructure from scratch.
Target Audience
Primary users are academic and institutional researchers in psychology, economics, public health, and related social sciences who need scalable, privacy‑preserving tools for digital behavioral data collection and intervention studies.
Features
- Passive Data Kit library for Android sensor logging, on‑device processing, and secure Django server backend
- QuestionKit engine that generates context‑aware surveys based on real‑time activity clustering and location analysis
- Webmunk‑based browser extension framework for remote manipulation of search result ordering and baseline behavior capture
- Automated Conversational Kit with reinforcement‑learning scheduling to deliver personalized SMS mental‑health interventions
- Custom importers for social‑media data donations that transform raw downloads into encrypted feature sets and generate reusable codebooks
- Open‑source licensing and modular architecture enabling researchers to extend or replace components for specific study needs