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Research & Development Data Use Notice

Last updated: June 7, 2026

Plain-language summary. We do research to make the platform better. Identifiable client data is never shared with research partners or used in public research without your consent or a written agreement. For internal improvement and validation, we use anonymized, de-identified, aggregated, or synthetic data. You keep your source data; we keep our platform IP.
Not legal advice. This Notice is a working document and has not been reviewed by counsel. Specific research collaborations should be governed by a written research or data-sharing agreement, reviewed by qualified Canadian and (for Barbados clients) Barbadian counsel.

This Notice supplements our Privacy Policy and explains how Project Bindr (ABA Hughes Inc.) uses data for research and development (R&D).

1. What We Research

Project Bindr may conduct R&D related to:

  • hybrid retrieval-augmented generation (RAG) AI;
  • document intelligence and asset extraction;
  • digital twin onboarding;
  • energy and metering review workflows;
  • warranty and operational readiness;
  • AR and spatial work order workflows; and
  • AI-assisted facility management reports.

2. Research Collaborators

Research may involve academic or industry collaborators, which may include Algoma University, the University of Toronto Mississauga, or other approved partners. Where a collaboration involves your data, the following boundaries apply.

3. Protecting Identifiable Client Data

  • identifiable client data will not be shared with research partners without your consent or a written agreement;
  • anonymized, synthetic, de-identified, or aggregated data may be used for product development and validation;
  • public research outputs will not identify clients without your approval; and
  • confidential, building-security-sensitive information (such as floor plans, access notes, and infrastructure details) will be protected and excluded from research datasets unless specifically approved.

4. What "De-identified" and "Synthetic" Mean Here

  • Anonymized / de-identified — data from which direct and reasonably linkable identifiers have been removed so it can no longer be readily associated with you;
  • Aggregated — combined data that reflects patterns across multiple sources rather than any single client; and
  • Synthetic — artificially generated data modelled on real patterns but not drawn from a specific client's records.

5. Ownership

You retain ownership of your source data. Project Bindr retains ownership of the platform, its models, methods, and trade secrets, and of de-identified, aggregated, and synthetic datasets and learnings derived through R&D, as described in the Terms of Use.

6. AI Model Training

We do not use identifiable client data to train public, third-party foundation models unless you explicitly authorize it. We may use anonymized, aggregated, or synthetic data to evaluate and improve internal models and workflows. Human review remains required for operational decisions.

7. Questions & Opt-Out

You can ask how research and data handling apply to your deployment, and you can raise concerns or opt-out preferences with us. Where a written research or data-sharing agreement exists, its terms govern.

8. Contact