Data Room for AI Company Deals in Canada (2026)

How it works in Canada

Canada built its AI sector around research hubs: Mila in Montreal, the Vector Institute in Toronto and Amii in Edmonton, all part of the Pan-Canadian AI Strategy. Many startups are founded by graduate students and professors, and some keep academic appointments. Deals include seed and growth rounds, acqui-hires by large US technology companies and acquisitions of applied AI firms in health, finance and industry.

Diligence here goes deeper than standard software. Buyers ask where each training dataset came from, what licence or consent covers it, whether scraped content was used and whether customer data was used to train shared models. They want model cards, evaluation results, compute contracts and the terms of any open-weight models used as a base. Research partnerships with universities raise questions about who owns improvements, and whether the founders’ institution has a claim.

There is no federal AI statute in force. The proposed Artificial Intelligence and Data Act died on the order paper when Parliament was prorogued in January 2025. Existing law still applies: privacy statutes, consumer protection, human rights law and sector rules. Quebec Law 25 requires notice when a decision about a person is based exclusively on automated processing, and the person can ask about the information and factors used.

Best data rooms for artificial intelligence

Our five criteria, re-weighted for this use case, plus a small bonus for providers built around it.

1 Ellty ~C$211/mo
9.4 Visit Ellty
2 iDeals Quote
8.9
3 Ansarada Quote
8.7
4 Datasite Quote
8.7
5 Intralinks Quote
8.5
6 Drooms Quote
8.5
7 Firmex Quote
8.4
8 SmartRoom Quote
8.3
9 Box ~C$21/user/mo
8.0
10 DealRoom Quote
8.0

Privacy 28%Workflow 21%Control 22%Usability 16%Cost 14%

What goes in the data room

Artificial intelligence: index

01
Corporate and founders
Cap table, founder agreements and disclosure of academic appointments and outside activities.
02
Research IP and institutional claims
University and institute IP policies, invention disclosures, licences or releases from the founders’ institutions.
03
Training data inventory
Each dataset with source, licence, consent basis, personal information content and retention.
04
Model documentation
Model cards, architecture notes, evaluation results, bias testing and base model licences.
05
Compute and cloud
GPU and cloud contracts, committed spend, credits from cloud programs and their expiry.
06
Customer contracts
Terms on using customer data for training, output ownership, warranties and indemnities.
07
Privacy and automated decisions
Privacy impact assessments, Law 25 automated decision notices and human review procedures.
08
Grants and tax credits
SR&ED claims, IRAP agreements, Scale AI or provincial funding with IP and location conditions.
09
Security
Model access controls, prompt injection testing, incident log and penetration test results.
10
Team and immigration
Key researcher agreements, work permit status and retention plans.

Canadian rules that apply

Quebec Law 25, automated decisions

Businesses that use personal information to make a decision based exclusively on automated processing must inform the person and, on request, explain the information and the main factors used. The person can ask for a human review. Buyers check products used in Quebec against this rule.

PIPEDA and training data

Personal information collected for one purpose generally needs consent for a new purpose such as training a model. Investors ask how training data containing personal information was collected and what consent or de-identification applies.

Federal AI legislation status

Bill C-27, which contained the Artificial Intelligence and Data Act, died when Parliament was prorogued on January 6, 2025. Buyers still ask for the company’s AI governance policies because future federal rules and foreign rules such as the EU AI Act may apply.

Features to insist on

Data room	Activity log	Dynamic watermarks	View and download rights	Q&A module	AI help
Ellty	Yes	Yes	Yes	Yes	Yes
iDeals	Yes	Yes	Yes	Yes	No
Ansarada	Yes	Yes	Yes	Yes	Yes
Datasite	Yes	Yes	Yes	Yes	Yes
Intralinks	Yes	Yes	Yes	Yes	No
Drooms	Yes	Yes	Yes	Yes	Yes
Firmex	Yes	Yes	Yes	Yes	No
SmartRoom	Yes	Yes	Yes	Yes	No

Activity log. Per-user history of opens, prints and downloads with timestamps, which you can export for the closing binder.
Dynamic watermarks. The reader's identity and the date are printed across every page, which discourages screenshots and identifies the source of a leak.
View and download rights. Choose, document by document, whether a guest may only read, may print or may download, and change it later.
Q&A module. Bidders post questions inside the room; counsel or the CFO drafts the reply, someone approves it, and every exchange stays on file.
AI help. Vendor-listed automation such as sorting uploads into the index, summarizing long agreements, searching the room or proposing answers.

How to set it up

1
Build a dataset register
List every dataset used in training or fine-tuning, where it came from, its licence and whether it holds personal information. Upload the register with the actual licence terms. Investors will test the largest datasets first.
2
Clear institutional claims
If founders worked at a university or AI institute, get a written release or licence from that institution and upload it. Unclear ownership of research done before incorporation is a frequent deal blocker.
3
Document the models
Upload model cards, evaluation benchmarks and the licence for any base model you built on. Note any restrictions in open-weight licences that might limit commercial use, user numbers or the markets you can serve.
4
Show privacy decisions
Add privacy impact assessments, Law 25 automated decision notices for Quebec users and the procedure for human review. These documents answer questions from enterprise customers, insurers and buyers at once.
5
Protect the technical folders
Weights, prompts and evaluation sets are trade secrets. Keep them out of the room or view-only for named technical reviewers late in the process, with full download blocking and printing turned off.

Common mistakes

Training on scraped or customer data with no record of the licence or consent behind it.
Ignoring the founders’ university IP policy because the code was written at home.
Using an open-weight base model whose licence restricts the planned commercial use.
Putting model weights in a downloadable folder.

FAQ

Is there an AI law in Canada that buyers check against?

No federal AI statute is in force. The Artificial Intelligence and Data Act died with Bill C-27 in January 2025. Buyers check privacy law, Quebec Law 25 automated decision rules, consumer protection and sector rules such as those for financial institutions. Companies selling into Europe should also show how they assess obligations under the EU AI Act.

Who owns AI research done at Mila or Vector?

It depends on the agreements and the university policies that cover each researcher. Institutes and universities have different IP rules, and some leave ownership with the creator while others claim it. Get the specific policy and a written release or licence for anything the startup relies on, and upload both.

Should model weights be in the data room?

Usually not. Buyers can assess models through documentation, evaluation results and a supervised demonstration. If a final bidder needs deeper access, set up a controlled environment rather than a file download, and limit it to named reviewers under a specific confidentiality agreement.

Data room for artificial intelligence deals in Canada