Data Privacy Lab
Data Privacy Lab is a non-profit academic research program at Harvard University's IQSS that develops privacy-preserving technologies and policy frameworks, serving government, corporate, and non-profit partners through a dues-based partnership model and targeted research projects.
- Company typePrivate
- Founded2001
- HeadquartersCambridge, United States
- Headcount—
- GTM typeB2B
- OfferingSoftware
What Data Privacy Lab does
Data Privacy Lab is a non-profit academic research program housed within the Institute for Quantitative Social Science (IQSS) at Harvard University, founded by Latanya Sweeney in 2001 at Carnegie Mellon University and relocated to Harvard in 2011. The lab develops privacy-preserving computational techniques and integrated policy frameworks that allow organizations to share sensitive data while maintaining provable privacy guarantees. Its technology portfolio spans de-identification algorithms (Datafly, k-Same face de-identification, Privacert Risk Assessment Server), credential and identity validation services (SSNwatch, Identity Angel), surveillance research infrastructure (Camera Watch, Smart Cameras, Privacy-Preserving Watchlist, bio-terrorism surveillance), and consumer-facing web tools (theDataMap, aboutMyInfo, MyDataCan, DataTags, SnapIt, ForeverData). The underlying technology combines classical statistical privacy techniques such as k-anonymity with applied computer vision, structured-data anomaly detection, and machine-learning-based fraud classification.
The lab's business model is structured as a multi-tier partnership program rather than a commercial SaaS operation. Corporate, non-profit, and government partners pay annual dues of $50,000 for access to faculty, students, internal publications, seminars, and rapid-turnaround studies on partner-specified privacy problems. Targeted research projects performed at cost run approximately $200,000 per year for typical two-year engagements involving a single faculty member and graduate student. Operating capacity is further sustained by institutional funding from Harvard through IQSS, federal research grants, and National Science Foundation (NSF) awards. The primary customer segments are government agencies (federal, state, and local), corporate organizations holding sensitive consumer data, non-profit advocacy organizations, and academic researchers. Distribution occurs through peer-reviewed academic publications, conference presentations, open-source software releases, formal academic courses (e.g., Harvard CS105), the Technology Science journal, and direct partner engagement.
Data Privacy Lab firmographics
Firmographics- Name
- Data Privacy Lab
- Legal name
- President and Fellows Harvard University
- Website
- https://dataprivacylab.org
- Company type
- Private
- Founded year
- 2001
- Operating status
- Operating
- Short description
- Data Privacy Lab is a non-profit academic research program at Harvard University's IQSS that develops privacy-preserving technologies and policy frameworks, serving government, corporate, and non-profit partners through a dues-based partnership model and targeted research projects.
- Ownership category
- akta.pro rank
Data Privacy Lab industry classification
Industry- Product category
- Data Privacy Software & Research
- NAICS
- Scientific Research and Development Services (5417), Other Scientific and Technical Consulting Services (54169), Research and Development in the Social Sciences and Humanities (541720)
- SIC
- Services-Computer Programming, Data Processing, Etc. (7370), Services-Commercial Physical & Biological Research (8731), Services-Testing Laboratories (8734)
- akta.pro primary industry
- Privacy-Preserving Data (De-identification, Anonymization, PII Redaction) (HDAAALAG)
- akta.pro secondary industries
- AI Privacy Engineering & Data Governance (PII, consent, retention) (HDAAAKAB), Data Security & Privacy Services (DLP, Encryption, Privacy Ops) (BPAKAHAM), De-identification, Tokenization & Privacy-Preserving Data Platforms (HLACAIAK), Data Loss Prevention (DLP) & Sensitive Data Discovery (PHI/PII) (HLACAJAC)
Keywords
Where Data Privacy Lab is headquartered
LocationHeadquarters
- HQ city
- Cambridge
- HQ country
- United States
- HQ region
- North America
Offices2 records
Markets served
Data Privacy Lab business model
Business model- GTM type
- B2B
- Offering type
- Software
- Cost components
- Personnel, Technology or R&D, Operations, Marketing or Sales
Revenue model
- Partnership Program Dues: Corporate, non-profit and government partners pay annual dues of $50k/year for access to publications, seminars, turnaround studies, and faculty.
- Targeted Research Projects: Specific research projects with faculty performed at cost. Typical two-year project with faculty and graduate student costs approximately $200k/year.
- Institutional Funding: Funding from Harvard University through IQSS, federal research grants, and NSF funding for specific projects.
Pricing tiers
| Model | Billing | Price |
|---|---|---|
| Subscription | Annual | Standard Partnership - $50k/year |
| Other | Multi-year contract | Targeted Research Projects - Approximately $200k/year |
Go-to-market motion1 record
Distribution channels3 records
Marketing channels5 records
Data Privacy Lab product offering
Product offeringCore offering
Data Privacy Lab develops privacy-enhancing software tools, de-identification algorithms, and identity protection services while conducting cross-disciplinary research at the intersection of technology and policy. It sells standalone tools such as Datafly (de-identification), SSNwatch (SSN validation), Identity Angel (identity theft alerts), and Privacert (HIPAA certification), and operates web services including theDataMap, aboutMyInfo, and MyDataCan. Revenue is generated through corporate/government partnership dues ($50k/year) and targeted multi-year research projects (~$200k/year).
Product overview
Data Privacy Lab, a research program within Harvard University's Institute for Quantitative Social Science, operates as a research-focused organization rather than a commercial product company. The lab develops a portfolio of privacy-enhancing technologies including de-identification tools (Datafly, k-Same), identity protection services (Identity Angel, SSNwatch), surveillance technologies (Camera Watch, Smart Cameras, Privacy-Preserving Watchlist), and public-facing tools (theDataMap, aboutMyInfo, MyDataCan, DataTags). The portfolio includes core research algorithms and web-based services, with the Privacert tool providing commercial HIPAA certification. These tools work together to enable data sharing with provable privacy guarantees while supporting homeland security, bio-terrorism surveillance, and individual privacy protection.
Differentiator
Problem solved
Functional benefit
Products and services
- Datafly De-identification system that applies k-anonymity techniques to render data anonymous for sharing while maintaining practical usefulness, used for HIPAA compliance assessments and public-use files.
- Identity Angel AI-driven system that crawls publicly available web information to identify people at risk of identity theft and notifies them when personal information can be combined to impersonate them.
- SSNwatch (SOS Social Security Number Watch) Validation service that matches people to Social Security Numbers using publicly available information to identify issuing state, date issued, estimated age range, and activity status, supporting identity theft prevention and credential verification.
- Camera Watch Database of approximately 6,000 URLs of publicly available online cameras displaying public places in the United States, with search functionality for surveillance research and observation of public spaces.
- k-Same Face De-identification Algorithm that de-identifies faces in video surveillance data by averaging image components (k-Same-Pixel or k-Same-Eigen), guaranteeing that face recognition software cannot recognize de-identified faces with better than 1/k likelihood of being correct.
- Smart Cameras (Video Count) System that captures publicly available camera images at regular intervals to automatically count faces and detect unusual crowd behaviors by comparing face counts against historical expectations.
- Privacy-Enhanced Linking Link analysis algorithms with guarantees of privacy protection modeled after Fair Information Practices, including Association Rule Learning (GenTree) and Robust Rule Learning, used for homeland security link analysis.
- Privacy-Preserving Watchlist Solution for matching government watchlists against transactional data without revealing the watchlist to data holders or exposing non-target individuals, designed for homeland security screening.
- Privacy-Preserving Bio-terrorism Surveillance System using a selective revelation approach to conduct bio-terrorism surveillance on de-identified medical data with provable privacy guarantees, leveraging Privacert Risk Assessment Server for HIPAA compliance.
- ScamSlam Machine learning technology to defeat fraudulent email schemes by identifying fraudulent intent hidden in email text.
- Privacert HIPAA Certification tool that assesses data compliance and de-identification standards under the HIPAA scientific standard, including a Risk Assessment Server for evaluating de-identification risk.
- theDataMap Web service showing where user data goes when collected by websites and services.
- aboutMyInfo Web service that determines whether user data is unique or identifiable based on demographic combinations.
- MyDataCan Web service giving users control over their personal data and transparency into how it is used.
- DataTags System for compliant data sharing with automatic privacy classification and handling requirements.
- SnapIt Web tool that preserves a web page exactly as it appears today for archival purposes.
Quantifiable outcome
- 87% of US population can be uniquely identified using only date of birth, gender, and ZIP code
- +2 more outcomes
Companies that use Data Privacy Lab
Customer profileNamed customers4 records
Segments4 records
Ideal customer profiles4 records
Data Privacy Lab technology and API
TechnologyTechnology focussed Yes
API detail
- Has API
- No
- API docs
- API detail
Core technology
AI maturity
App detail
AI capability13 records
Feature6 records
Data Privacy Lab partnerships and signals
Strategic signalPartnerships
Ten partnerships are on record, tiered major, minor and core.
- U.S. Federal Trade Commission (FTC)majorLatanya Sweeney served as Chief Technology Officer at FTC, launching summer research fellows program and blogging on Tech@FTC to facilitate exploration of technology, policy and business solutions.
- Corporate Partners (Various)majorFormal corporate partnership program at $50k/year providing access to turnaround studies, publications, seminars, and faculty consultation. Partners include companies with databases of customer records seeking de-identification services and privacy assessments.
- Government Agencies (Various)majorGovernment partnerships for applying re-identification techniques to assess data anonymity, refining declassification rules, and developing privacy-preserving surveillance technologies.
- Non-Profit Organizations (Various)minorNon-profit partnerships for applying privacy metrics to compare impact of different legislative proposals and privacy policies.
- Harvard Institute for Quantitative Social Science (IQSS)coreThe Data Privacy Lab is a formal program within IQSS at Harvard University, providing institutional affiliation, administrative support, and access to Harvard's broader research ecosystem including faculty across Computer Science, Medicine, Law, and Government.
- Harvard School of Engineering and Applied SciencescoreAcademic collaboration with SEAS faculty for research on technical privacy solutions.
- Harvard Medical SchoolcoreCollaboration on healthcare privacy, medical records de-identification, and HIPAA compliance research.
- Harvard Law SchoolcorePartnership on law and policy aspects of data privacy, Common Rule revisions, and regulatory analysis.
- Massachusetts Institute of Technology (MIT)coreAcademic collaboration leveraging MIT faculty expertise in computer science and privacy research.
- Carnegie Mellon University (Historical)coreHistorical partnership from 2001-2011 when the lab operated at CMU Heinz School of Public Policy and School of Computer Science.
Scale indicators4 records
Recent moves7 records
Expansion highlights5 records
Data Privacy Lab competitors and assessment
Company assessmentEmerging players
- Sarus Technologies: Sarus offers a privacy-preserving analytics layer that allows data scientists to query sensitive data without seeing it. It is an emerging player addressing similar use cases (HIPAA-grade analytics, government data, de-identification) but as a commercial SaaS rather than a research lab.
- LeapYear Technologies: LeapYear provides a differential-privacy platform for data analytics and machine learning on sensitive data. It is an emerging commercial peer that overlaps with the Lab's privacy-preserving analytics mission, though it focuses more on enterprise data science than on policy research.
Direct peers
- MOSTLY AI: MOSTLY AI is a synthetic data platform that generates privacy-preserving synthetic datasets for analytics and AI training. It is directly comparable because it pursues the same fundamental mission as Data Privacy Lab — enabling data sharing and analytics while protecting individual identity — via privacy-preserving data tooling.
- CMU CyLab: CMU CyLab is the cybersecurity and privacy research institute at Carnegie Mellon, the Lab's original institutional home (2001-2011). It is directly comparable as a university-based interdisciplinary privacy and security research lab producing both academic output and policy-relevant privacy tools.
- Tumult Labs: Tumult Labs provides differential-privacy software for generating provably private datasets, including US Census data products. It is directly comparable because, like Data Privacy Lab, it focuses on mathematically grounded privacy guarantees (rather than heuristics) and serves government/statistical-agency use cases for public-release datasets.
- Harvard Privacy Tools Project: The Privacy Tools Project at Harvard SEAS builds technology for sharing sensitive data with privacy guarantees, sharing overlapping institutional context with Data Privacy Lab at Harvard. It is directly comparable as a Harvard-affiliated academic effort producing practical privacy-preserving data-sharing tools for research and policy.
- Hazy: Hazy provides enterprise synthetic data generation for financial services and other regulated industries. It is directly comparable to Data Privacy Lab's anonymization and de-identification mission, offering a commercial productization path that contrasts with the Lab's open-source, research-driven approach.
- Statice (Anonos): Statice, now part of Anonos, builds privacy-preserving data transformation tooling that enables data sharing while protecting individuals. It is directly comparable because it commercializes the same de-identification and pseudonymization techniques the Lab has researched, targeting regulated industries with similar data-sharing pain points.
- Privacert: Privacert is a HIPAA certification and data de-identification risk-assessment tool originally developed by the Data Privacy Lab. It is directly comparable because it operationalizes the Lab's Privacert Risk Assessment Server for commercial use, addressing the same de-identification and HIPAA-compliance use cases for healthcare and government data sharing.
Broad incumbents
- Microsoft Research - Privacy Research Group: Microsoft's privacy research group conducts fundamental and applied research on privacy, including differential privacy, federated learning, and data governance. It is a broad incumbent that overlaps with the Lab's research mission, but operates as part of a much larger commercial platform with broader scope and engineering scale.
Market position
Strengths5 records
Weaknesses5 records
Competitive moat4 records
Key risks6 records
Key highlights6 records
Customer concentration
Data Privacy Lab social profiles
Digital presenceData Privacy Lab compliance and trust
Trust signalCompliance1 record
Data Privacy Lab financial estimates
Financial estimateRevenue estimate
Valuation estimate
Data Privacy Lab leadership team
Management profileNumber of profiles
Profiles1 record
Data Privacy Lab funding detail
Funding detailFunding overview
Funding rounds
Investors
Funding detail is available on the Subscription and Enterprise plan.Contact sales →
Data Privacy Lab M&A and investment
M&A and investmentM&A
Investments
M&A and investment is available on the Subscription and Enterprise plan.Contact sales →
Frequently asked questions about Data Privacy Lab
What does Data Privacy Lab do?
Data Privacy Lab develops privacy-enhancing software tools, de-identification algorithms, and identity protection services while conducting cross-disciplinary research at the intersection of technology and policy. It sells standalone tools such as Datafly (de-identification), SSNwatch (SSN validation), Identity Angel (identity theft alerts), and Privacert (HIPAA certification), and operates web services including theDataMap, aboutMyInfo, and MyDataCan. Revenue is generated through corporate/government partnership dues ($50k/year) and targeted multi-year research projects (~$200k/year).
Is Data Privacy Lab a public or private company?
Data Privacy Lab is a private company. It is classified as nonprofit foundation owned and is currently operating.
When was Data Privacy Lab founded?
Data Privacy Lab was founded in 2001.
Where is Data Privacy Lab based?
Data Privacy Lab is headquartered in Cambridge, United States, in the North America region.
How does Data Privacy Lab make money?
Three revenue lines are on record. Partnership Program Dues are the primary driver. The others are targeted Research Projects and institutional Funding.
Who are Data Privacy Lab's main competitors?
Emerging players on record are Sarus Technologies and LeapYear Technologies. Direct peers are MOSTLY AI, CMU CyLab, Tumult Labs, Harvard Privacy Tools Project, Hazy, Statice (Anonos) and Privacert. Microsoft Research - Privacy Research Group is listed as a broad incumbent.
Does Data Privacy Lab have an API?
No public API is recorded for Data Privacy Lab.
What industry is Data Privacy Lab in?
Data Privacy Lab's product category is Data Privacy Software & Research. Its primary akta.pro industry code is HDAAALAG, Privacy-Preserving Data (De-identification, Anonymization, PII Redaction), with a secondary code of HDAAAKAB, AI Privacy Engineering & Data Governance (PII, consent, retention). Its NAICS code is 5417 and its SIC code is 7370.