Tumult Labs
Tumult Labs builds differential privacy software that lets enterprises and government agencies safely share and publish insights from sensitive data. Its Tumult Analytics platform operationalizes mathematically-proven privacy guarantees for customers in public sector, banking, and advertising.
- Company typePrivate
- Founded2019
- HeadquartersDurham, United States
- Headcount11–50
- GTM typeB2B
- OfferingSoftware
What Tumult Labs does
Tumult Labs is a Durham, North Carolina-based privacy technology company founded in 2019 that builds differential privacy software for enterprise and government data sharing. Its core platform, Tumult Analytics, operationalizes differential privacy — a mathematical framework that adds calibrated noise to query outputs to guarantee individual privacy while preserving aggregate utility. The platform is built on proprietary algorithms including the HDMM (High-Dimensional Matrix Mechanism, deployed for the 2020 U.S. Census), the AIM algorithm for synthetic data generation, and the MST workflow, all composed through the open-source Tumult Core framework that automatically deduces end-to-end privacy guarantees. A complementary product, Tumult Tune, was announced in 2024 to help users visualize and optimize privacy-utility trade-offs.
The company sells primarily to regulated, data-intensive organizations: U.S. government agencies (Census Bureau, IRS, Department of Education), the Wikimedia Foundation, and enterprises in banking/finance and advertising/publishing. Its revenue model is enterprise SaaS subscription supplemented by professional services for solution design, tuning, and deployment (a 'Design, Tune, Stage, Deploy, Manage' workflow), distributed via direct enterprise field sales with a 'Request a Demo' conversion motion and a hosted self-evaluation environment. Pricing is not publicly disclosed.
Tumult Labs operates with 11–50 employees and was led by CEO Gerome Miklau (co-inventor of the Matrix Mechanism) and Chief Scientist Ashwin Machanavajjhala (Census Bureau advisor). The company has open-sourced its privacy-critical code on GitLab and published a public architecture whitepaper. As of the most recent website announcement, 'The Tumult Labs team is joining LinkedIn,' indicating the company was acquired by LinkedIn.
Tumult Labs firmographics
Firmographics- Name
- Tumult Labs
- Legal name
- Tumult Labs Inc.
- Website
- https://tmlt.io
- Company type
- Private
- Founded year
- 2019
- Operating status
- Operating
- Headcount range
- 11–50 employees
- Short description
- Tumult Labs builds differential privacy software that lets enterprises and government agencies safely share and publish insights from sensitive data. Its Tumult Analytics platform operationalizes mathematically-proven privacy guarantees for customers in public sector, banking, and advertising.
- Ownership category
- akta.pro rank
Tumult Labs industry classification
Industry- Product category
- Privacy Software
- NAICS
- Computing Infrastructure Providers, Data Processing, Web Hosting, and Related Services (518), Computing Infrastructure Providers, Data Processing, Web Hosting, and Related Services (5182)
- SIC
- Services-Prepackaged Software (7372)
- akta.pro primary industry
- Data Security & Privacy for Cloud (DLP, DSPM, Tokenization) (HDABAHAK)
- akta.pro secondary industries
- Data Security & Privacy Services (DLP, Encryption, Privacy Ops) (BPAKAHAM), Data Loss Prevention (DLP) (HDADAFAA)
Keywords
Where Tumult Labs is headquartered
LocationHeadquarters
- HQ city
- Durham
- HQ country
- United States
- HQ region
- North America
Offices2 records
Markets served
Tumult Labs business model
Business model- GTM type
- B2B
- Offering type
- Software
- Cost components
- Personnel, Technology or R&D
Revenue model
- Platform/SaaS Subscription: Tumult Labs provides differential privacy software as a hosted platform service. The company offers access to Tumult Analytics platform through subscription, with enterprise licensing based on usage and deployment scale. The 'Request a Demo' flow and hosted demonstration environment indicate a subscription-based go-to-market model targeting enterprise customers with compliance needs.
- Professional Services: The company provides services for designing and deploying differential privacy solutions tailored to customer needs. Their workflow includes 'Design, Tune, Stage, Deploy, and Manage' professional services for implementing DP solutions, as seen in case studies with the Census Bureau and Wikimedia Foundation.
Go-to-market motion2 records
Distribution channels3 records
Marketing channels7 records
Tumult Labs product offering
Product offeringCore offering
Tumult Labs builds and sells a differential privacy software platform (Tumult Analytics) that enables organizations to safely share, publish, and monetize insights from sensitive personal data. The platform operationalizes differential privacy—a mathematical framework that adds calibrated noise to query results to prevent individual re-identification while preserving aggregate statistical utility. Offerings include a hosted SaaS platform, open-source core libraries, and professional services for designing and deploying DP solutions.
Product overview
Tumult Labs provides a differential privacy platform consisting of Tumult Analytics as the primary commercial product, complemented by Tumult Tune (an upcoming optimization tool), and Tumult Core as an open-source library. The platform operationalizes privacy-safe data sharing for enterprises, enabling organizations to safely use, share, and monetize insights from personal data while maintaining mathematical privacy guarantees. The offering includes professional services for solution design, deployment, and ongoing support.
Differentiator
Problem solved
Functional benefit
Brands
- Tumult Analytics: The company's differential privacy platform for operationalizing privacy-safe data sharing for the enterprise.
- Tumult Tune
Products and services
- Tumult Analytics Tumult Analytics is the company's production-ready differential privacy platform that enables organizations to prototype, tune, and deploy differentially private data products. It supports privacy IDs for user-level privacy guarantees, even when each user contributes multiple records, and includes privacy-budget management across complex data transformations. Targeted at enterprise data, privacy, and analytics teams in regulated industries.
- Tumult Tune Tumult Tune is a product that helps users easily understand and optimize privacy-utility trade-offs for differentially private data products. It enables visualization and tuning of parameters to achieve an optimal balance between privacy protection and data accuracy for aggregated data releases. Targeted at data scientists, analysts, and data stewards deploying differential privacy pipelines.
- Tumult Core Tumult Core is an open-source software library providing core differential privacy primitives and a framework where simple, easy-to-audit components can be composed in complex ways, with end-to-end privacy guarantees automatically deduced from properties of individual components. Targeted at developers and researchers building and auditing differential privacy implementations.
Quantifiable outcome
- The College Scorecard project released more data than with previous approaches, enabling students and families to compare costs and outcomes across institutions
- +3 more outcomes
Companies that use Tumult Labs
Customer profileNamed customers4 records
Segments4 records
Ideal customer profiles3 records
Tumult Labs technology and API
TechnologyTechnology focussed Yes
API detail
- Has API
- No
- API docs
- API detail
Core technology
AI maturity
App detail
AI capability7 records
Feature7 records
Tumult Labs partnerships and signals
Strategic signalPartnerships
Four partnerships are on record, tiered core and flagship.
- U.S. Census BureaucoreTumult Labs worked with the U.S. Census Bureau to design and implement differential privacy solutions for their most challenging data release problems. This partnership resulted in the deployment of Tumult's software for the 2020 Census Disclosure Avoidance Modernization, including HDMM algorithm technology. The Census Bureau has committed to reusing Tumult's software for the next decade.
- Wikimedia FoundationcoreTumult Labs collaborated with Wikimedia Foundation engineers to design, implement, and deploy a differentially private solution for publishing Wikipedia usage metrics with geographic detail. The collaboration followed Tumult's Build-Tune-Deploy workflow, resulting in a production pipeline that enables more granular, equitable, and safe data releases about Wikipedia platform usage.
- U.S. Department of EducationflagshipPartnered with the IRS to enable the College Scorecard project, joining sensitive data sets from the Department of Education and the IRS in a privacy-protected way. This resulted in a platform allowing students and families to compare college costs, outcomes, and financial outcomes across institutions.
- Internal Revenue Service (IRS)flagshipCollaborated with the IRS to support educational accountability through differential privacy. The IRS needed to share earnings data linked to educational outcomes while adhering to stringent privacy standards mandated by U.S. law (Title 26). Tumult facilitated discussions and designed a DP strategy enabling more data publication than legacy methods.
Scale indicators1 record
Recent moves7 records
Expansion highlights6 records
Tumult Labs competitors and assessment
Company assessmentDirect peers
- TripleBlind: Privacy-enhancing computation platform offering differential privacy and federated learning for enterprises. Comparable as a commercial PETs vendor serving healthcare, financial services, and ad tech with overlapping data collaboration use cases.
- Privitar (Informatica): Enterprise data privacy platform providing de-identification, tokenization, and differential privacy capabilities, now part of Informatica. Directly comparable as a commercial data-privacy vendor serving financial services and government customers.
- LeapYear Technologies: Enterprise differential privacy platform serving banks, insurers, and government agencies. Directly comparable as a commercial DP vendor targeting the same regulated buyers with similar secure-computation and data-monetization use cases.
- Anonos (formerly Statice): Synthetic data and privacy-preserving data sharing platform serving regulated industries. Comparable because it offers differentially private synthetic data generation as a core commercial product with similar data-monetization use cases.
- OpenDP: Harvard-developed open-source differential privacy library backed by a major academic consortium. Most directly comparable peer because it competes in the same DP tooling category with overlapping algorithms (SmartNoise lineage) and targets similar government/research customers.
Broad incumbents
- Microsoft SmartNoise: Open-source differential privacy SDK developed by Microsoft in partnership with Harvard. Comparable as an open-source DP library competing with Tumult Core, though embedded within Microsoft's broader data and AI platform rather than offered as a standalone enterprise product.
- Google (TensorFlow Privacy / DP-SGD): Google's open-source differential privacy tooling integrated into TensorFlow for ML training. Comparable as a DP technology provider with overlapping algorithms (DP-SGD), though positioned as part of Google's broader ML/AI platform rather than a focused privacy product.
- IBM diffprivlib: IBM's open-source differential privacy library offering DP primitives and machine learning tooling. Comparable as an alternative DP toolkit, but distributed through IBM's broader data science ecosystem rather than as a focused enterprise platform.
Market position
Strengths5 records
Weaknesses5 records
Competitive moat5 records
Key risks6 records
Key highlights6 records
Customer concentration
Tumult Labs social profiles
Digital presenceTumult Labs financial estimates
Financial estimateRevenue estimate
Valuation estimate
Tumult Labs leadership team
Management profileNumber of profiles
Profiles4 records
Tumult Labs funding detail
Funding detailFunding overview
Funding rounds
Investors
Funding detail is available on the Subscription and Enterprise plan.Contact sales →
Tumult Labs 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 Tumult Labs
What does Tumult Labs do?
Tumult Labs builds and sells a differential privacy software platform (Tumult Analytics) that enables organizations to safely share, publish, and monetize insights from sensitive personal data. The platform operationalizes differential privacy—a mathematical framework that adds calibrated noise to query results to prevent individual re-identification while preserving aggregate statistical utility. Offerings include a hosted SaaS platform, open-source core libraries, and professional services for designing and deploying DP solutions.
Is Tumult Labs a public or private company?
Tumult Labs is a private company. It is classified as founder individual operated bootstrapped and is currently operating.
When was Tumult Labs founded?
Tumult Labs was founded in 2019. It employs 11 to 50 people.
Where is Tumult Labs based?
Tumult Labs is headquartered in Durham, United States, in the North America region.
How does Tumult Labs make money?
Two revenue lines are on record. Platform/SaaS Subscription is the primary driver. The others are professional Services.
Who are Tumult Labs's main competitors?
Direct peers on record are TripleBlind, Privitar (Informatica), LeapYear Technologies, Anonos (formerly Statice) and OpenDP. Broad incumbents are Microsoft SmartNoise, Google (TensorFlow Privacy / DP-SGD) and IBM diffprivlib.
Does Tumult Labs have an API?
No public API is recorded for Tumult Labs.
What industry is Tumult Labs in?
Tumult Labs's product category is Privacy Software. Its primary akta.pro industry code is HDABAHAK, Data Security & Privacy for Cloud (DLP, DSPM, Tokenization), with a secondary code of BPAKAHAM, Data Security & Privacy Services (DLP, Encryption, Privacy Ops). Its NAICS code is 518 and its SIC code is 7372.