InterPARES Trust AI

What InterPARES Trust AI does

InterPARES Trust AI is a multi-national interdisciplinary research project running from 2021 to 2026, headquartered at the University of British Columbia's School of Information in Vancouver, Canada. It is the continuation of a research lineage that began with InterPARES 1 in the late 1990s and aims to design, develop, and leverage artificial intelligence to support the ongoing availability and accessibility of trustworthy public records. The project organizes its work across seven working groups (Creation and Use; Appraisal and Acquisition; Arrangement and Description; Retention and Preservation; Management and Administration; Reference and Access; and General Studies) and 40+ active studies, drawing on over 100 researchers and partners across five continents.

Its technology scope covers natural language processing, computer vision, speech and audio processing, multimodal AI, generative AI detection, knowledge graphs, and process automation, applied to archival use cases such as records classification, metadata enrichment, ancient document recognition, audiovisual archive processing, and AI-generated content detection. The project produces open research outputs including a multi-lingual Terminology Database, the Teachable AI curriculum for archival professions (with a companion GitHub AI/ML tutorial repository hosted under UBC-NLP), and a Paradata Documentation Framework for preserving contextual information about AI processes used on records.

The project is funded by a Social Sciences and Humanities Research Council (SSHRC) Partnership Grant and does not sell commercial products or services. Its go-to-market is community-driven: knowledge is disseminated through international symposiums, annual summer schools in Italy, academic publications, and direct engagement with archival institutions, government records professionals, and industry partners. Stakeholders include UBC, San Jose State University, Carleton University, Uppsala University, University of Macerata, Tianjin Normal University, Universiti Kebangsan Malaysia, UNESCO, ICA, ICCROM, the Bank of Canada, and multiple national archives.

Name

InterPARES Trust AI

Legal name

InterPARES Trust AI

Website

https://interparestrustai.org

Company type

Private

Founded year

2021

Operating status

Operating

Headcount range

1–10 employees

Short description

InterPARES Trust AI is a 2021-2026 multi-national academic research project based at UBC that designs and applies AI to preserve trustworthy public records, serving archivists, government records professionals, and academic researchers across five continents.

Ownership category

akta.pro rank

Product category

Archival Research Services

SIC

Services-Computer Programming Services (7371)

akta.pro industry

PRIMARYHDAAAMAE

Regulatory Readiness & Audit Automation (e.g., EU AI Act, NIST AI RMF, ISO/IEC 42001)

Hardware, Technology & Telecom/Artificial Intelligence & Machine Learning/AI Ethics & Compliance Solutions

SECONDARYHDAAAMAJ

Documentation & Reporting Automation (Model Cards, Datasheets, Impact Assessments)

Hardware, Technology & Telecom/Artificial Intelligence & Machine Learning/AI Ethics & Compliance Solutions

SECONDARYHDAAAKAL

Audit, Explainability & Accountability Tooling (traceability, reporting)

Hardware, Technology & Telecom/Artificial Intelligence & Machine Learning/AI Security, Privacy & Model Governance

SECONDARYBPAEAHAJ

Responsible AI, AI Governance & Compliance Services

Business & Public Services/IT & Digital Services (Managed Services, Systems Integration)/Data, Analytics & AI Services

SECONDARYHDAAAMAL

Safety & Alignment Evaluation (red-teaming, harmful capability testing)

Hardware, Technology & Telecom/Artificial Intelligence & Machine Learning/AI Ethics & Compliance Solutions

Keywords

• Archival research
• AI records management
• Digital preservation
• Archival science
• Responsible AI

Headquarters

HQ city

Vancouver

HQ country

Canada

HQ region

North America

Offices1 record

Markets served

GTM type

B2B

Offering type

Services

Cost components

Personnel, Technology or R&D, Operations, Marketing or Sales, Others

Revenue model

1. Research Grant Funding: The project is funded through SSHRC (Social Sciences and Humanities Research Council) Partnership Grant as a multi-national interdisciplinary research initiative

Go-to-market motion1 record

Distribution channels3 records

Marketing channels5 records

Core offering

InterPARES Trust AI is a multi-national interdisciplinary research project (2021-2026) that designs, develops, and leverages artificial intelligence to support the ongoing availability and accessibility of trustworthy public records. The project produces original research across seven working groups, an educational Teachable AI curriculum, a Terminology Database, and a GitHub-based AI/ML Tutorial Repository, building a sustainable partnership between academia, archival institutions, government records professionals, and industry across five continents.

Product overview

InterPARES Trust AI is a multi-national interdisciplinary research project (2021-2026) focused on designing, developing, and leveraging AI to support the ongoing availability and accessibility of trustworthy public records. The initiative produces original research through six working groups (Creation and Use, Appraisal and Acquisition, Arrangement and Description, Retention and Preservation, Management and Administration, and Reference and Access), along with educational resources including the Teachable AI curriculum modules, an AI/ML Tutorial Repository on GitHub, and a Terminology Database. The project forms a sustainable partnership between academia, archival institutions, government records professionals, and industry to create original research, train highly qualified personnel, and generate knowledge exchange across these communities.

Differentiator

Problem solved

Functional benefit

Products and services

• Teachable AI for the Archival Professions (AD01) Educational curriculum modules teaching archivists and records managers how to leverage AI tools to support archival arrangement and description. Includes modules on introduction to AI, critical AI/ML ethics, processing textual records, image-based records, and audiovisual records. Designed for archival professionals and archives school students.
• AI and ML Tutorial Repository GitHub-based repository housing tutorials for hands-on workshops covering NLP tasks (POS tagging, NER, text classification, machine translation), speech processing, image processing, and practical machine learning. Used by archivists and records professionals attending project workshops.
• Terminology Database Vocabulary database at the intersection of recordkeeping and information technology, continuing previous InterPARES project work on trust in cloud environments. Provides definitions for terms representing fundamental archival and AI concepts. Available in English, Portuguese, and Spanish.
• Annual Summer School on AI for Archival Professions Annual intensive training program held in San Benedetto del Tronto, Italy, providing in-depth training on AI applications for archival professions. Targeted at archivists, records professionals, and researchers seeking hands-on AI literacy.
• Paradata Documentation Framework Framework for documenting AI processes, code, training data, parameters, and technical environment to preserve contextual materials supporting records authenticity when AI is applied to archival processes. Used by archival institutions and researchers implementing AI in recordkeeping.

Quantifiable outcome

• Over 400 publications and presentations disseminated through the research project
• +2 more outcomes

Segments4 records

Ideal customer profiles4 records

Technology focussed Yes

API detail

Has API

No

API docs

API detail

Core technology

AI maturity

App detail

AI capability11 records

Feature4 records

Partnerships

14 partnerships are on record, tiered core and flagship.

• University of British Columbia - School of InformationcoreStrategic or Co-development Partner · 1 January 2021Principal investigator institution. Luciana Duranti serves as Principal Investigator and Co-Director from UBC School of Information. Hosts project headquarters and coordinates international research activities.
• San Jose State University - School of InformationcoreStrategic or Co-development Partner · 1 January 2021Lead institution for Appraisal and Acquisition Working Group. Patricia Franks serves as Working Group Chair. Contributes research on AI for retention and disposition in recordkeeping systems.
• Carleton University - School of Journalism and CommunicationcoreStrategic or Co-development Partner · 1 January 2021Lead institution for Smart Grid and Digital Twin research. Tracey Lauriault serves as lead researcher. Contributes expertise on digital preservation and critical data studies.
• UNESCO - International Council on ArchivesflagshipStrategic or Co-development Partner · 1 January 2021Key institutional partner including UNESCO Memory of the World program and ICA (International Council on Archives). Eng Sengsavang from UNESCO contributes to AI-assisted digitization research. Project produces special issue publications for UNESCO.
• International Centre for the Study of the Preservation and Restoration of Cultural Property (ICCROM)coreStrategic or Co-development Partner · 1 January 2021Maria Mata Caravaca serves as Working Group Chair for Arrangement and Description. Contributes expertise in cultural heritage preservation and AI applications.
• University of Macerata, ItalycoreStrategic or Co-development Partner · 1 January 2021Emanuele Frontoni leads AI Applied to Cultural Heritage study. Pierluigi Feliciati leads Reference and Access studies. Strong collaboration on AI literacy and archival access research.
• Tianjin Normal University, ChinacoreStrategic or Co-development Partner · 1 January 2021Partnership on AI in records and archives management in China (GS03). Sherry Xie leads research on trustworthy AI and records management roles.
• Universiti Kebangsan MalaysiacoreStrategic or Co-development Partner · 1 January 2021Umi Mokhtar leads research on records classification using NLP techniques. Contributes Southeast Asian perspective to AI and records management.
• Bank of CanadacoreStrategic or Co-development Partner · 1 January 2021Alex Richmond leads enterprise master data management research. Contributes case study on AI applications in financial institution recordkeeping.
• Government archival institutions (UK, Brazil, Israel, Italy, and others)coreStrategic or Co-development Partner · 1 January 2021Multiple national archives participate as partners and contribute case studies. Includes The National Archives (UK), National Archives of Brazil, Israel State Archives, Italian national archives, and others providing research data and practical applications.
• City of Toronto ArchivescoreStrategic or Co-development Partner · 1 January 2021Carlos Granados-Ocon participates in Creation and Use Working Group. Contributes municipal government perspective on records management and AI.
• Swedish Transport AdministrationcoreStrategic or Co-development Partner · 1 January 2021Göran Samuelsson participates in Creation and Use Working Group. Contributes to Digital Twin preservation research.
• Uppsala University, Sweden - Department of Archives, Libraries and MuseumscoreStrategic or Co-development Partner · 1 January 2021Isto Huvila contributes to paradata research and co-edits book 'Paradata: Documenting Data Creation, Curation, and Use' published by Cambridge University Press 2025.
• City University of New York - Archival Technologies LabcoreStrategic or Co-development Partner · 1 January 2021James Lowry leads CU09 study on AI, Warfare, and Evidence. Contributes expertise on archival technologies and international contexts.

Scale indicators4 records

Recent moves6 records

Expansion highlights10 records

Direct peers

• Internet Archive: Non-profit digital library building a global archive of web and cultural content. Comparable in mission scope (trustworthy long-term digital preservation) and non-commercial funding model.
• Council on Library and Information Resources (CLIR): Non-profit research and policy organization supporting libraries, archives, and cultural heritage institutions. Comparable to InterPARES in conducting applied research and convening academic/government partners around information stewardship.
• Open Preservation Foundation: Non-profit that develops and sustains open-source digital preservation tools and hosts community working groups. Comparable as a research-to-tooling consortium serving archives, libraries, and memory institutions.
• Digital Preservation Coalition: International non-profit coalition that supports digital preservation research and practice across memory institutions. Closely comparable to InterPARES as a multi-stakeholder research and knowledge-mobilization network focused on preserving trustworthy digital records.
• Partnership on AI: Multi-stakeholder non-profit researching responsible AI governance, including documentation, fairness, and accountability practices. Comparable to InterPARES in convening cross-sector experts to define responsible AI norms and frameworks.
• LYRASIS: Non-profit technology and services organization serving libraries, archives, and museums globally. Comparable in offering shared research-driven services and infrastructure to memory institutions across many countries.

Broad incumbents

• Arkivum: Commercial digital preservation service provider primarily serving research-intensive and archival organizations in Europe. Comparable in addressing long-term preservation of trustworthy records, though delivered as managed service rather than research output.
• Preservica: Commercial vendor of digital preservation and records management software used by regulated enterprises and government archives. Comparable as a deliverer of trustworthy digital records solutions, but as a commercial product rather than research consortium.

Emerging players

• Montreal AI Ethics Institute: Independent non-profit producing applied research on AI ethics and governance. Comparable as a research-driven organization producing frameworks and educational content on responsible AI, though without an archival specialization.
• AI Now Institute: Research institute studying the social implications of AI, with policy-focused outputs. Comparable in producing research-driven frameworks for responsible AI, though focused on broader social impacts rather than archives specifically.

Market position

Strengths4 records

Weaknesses4 records

Competitive moat5 records

Key risks5 records

Key highlights6 records

Customer concentration

• Xx.com/itrustai
• GitHubgithub.com/UBC-NLP/itrustai-tutorials
• Facebookfacebook.com/interparestrust
• LinkedInlinkedin.com/company/interpares-trust-ai
• Instagraminstagram.com/interparestrust

Revenue estimate

Valuation estimate

Number of profiles

Profiles3 records

Funding overview

Funding rounds

Investors

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M&A

Investments

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Frequently asked questions about InterPARES Trust AI