AI Assistant for Government Policy Questions

Inform

What it collects

Operational data

Anonymized data

Official PSPC and Government of Canada policy documents, directives, guides, FAQs, and intranet pages stored in GC repositories. These documents are vectorized for retrieval at runtime. No personal information is included in the corpus.

Enterprise Policy Chatbot — GC AI Register

About behaviour

Anonymized data

Natural-language questions submitted by GC employees at runtime. The system also accepts feedback and flagging actions from users. The register confirms no personal information is involved.

Enterprise Policy Chatbot — GC AI Register

Run by: Public Services and Procurement Canada (PSPC)
Where: No fixed location
Kept: Not stated by the Helpful Places.
Shared with: Not stated by the Helpful Places.
Your copy: You cannot see the data it holds about you. What you can do

What it is for

Inform

This AI assistant helps Government of Canada employees find answers to questions about PSPC and GC policies, directives, and procedures by searching official policy documents and citing its sources. It is intended to make policy information easier to find and to reduce repetitive questions to policy teams. Users are informed that they are interacting with an AI system. No personal information is collected or used.

What it collects and what happens to it

Data taken in

Operational data

Anonymized data

Official PSPC and Government of Canada policy documents, directives, guides, FAQs, and intranet pages stored in GC repositories. These documents are vectorized for retrieval at runtime. No personal information is included in the corpus.

Enterprise Policy Chatbot — GC AI Register

About behaviour

Anonymized data

Natural-language questions submitted by GC employees at runtime. The system also accepts feedback and flagging actions from users. The register confirms no personal information is involved.

Enterprise Policy Chatbot — GC AI Register

Processing

Search & Retrieval

Uses a retrieval-augmented generation (RAG) architecture combining semantic vector search and keyword search over vectorized GC policy documents. Retrieved passages are used to ground the natural-language answers the system produces.

Enterprise Policy Chatbot — GC AI Register

Language Models

A language model composes natural-language answers from the retrieved policy passages. The system applies guardrails and access controls to constrain outputs to the intended policy domain.

Enterprise Policy Chatbot — GC AI Register

What it does

Understanding (Semantic AI)

Human decides

The system uses semantic and keyword search to match employee questions to relevant policy documents stored in GC repositories. It retrieves and surfaces passages from official sources rather than generating novel content.

Enterprise Policy Chatbot — GC AI Register

Creating (Generative AI)

Human decides

The system composes natural-language answers to policy questions by synthesizing retrieved content from official documents. It cites its sources so that users can verify the guidance provided. A human user decides whether to act on the answer.

Enterprise Policy Chatbot — GC AI Register

Outputs

Generated content

Anonymized data

Natural-language answers to policy questions, with citations to the source policy documents. Outputs are advisory — users decide whether to act on the guidance provided.

Enterprise Policy Chatbot — GC AI Register

Run by

Public Services and Procurement Canada (PSPC)

The federal department deploying and operating the Enterprise Policy Chatbot to support GC employees with policy guidance. PSPC is responsible for the system's development and operation as part of the Government of Canada.

Enterprise Policy Chatbot — GC AI Register

Built by

Not stated by the Helpful Places.

Kept for

Not stated by the Helpful Places.

Shared with

Not available to me

The register confirms no personal information is collected or used. GC employees do not have a data-subject access right because no personal data about them is held by this system.

Enterprise Policy Chatbot — GC AI Register

Stored

Not stated by the Helpful Places.

How to read the colours

Can it identify you?

Anonymized data: Data about people with the link to who is broken. Stripped of identifiers, blurred, aggregated, or noised so this system can’t reasonably tie a record back to an individual.
Pseudonymous data: Each person’s data is tied to a token (hash, ID, template) that lets this system recognise the same person across events, but the token itself doesn’t reveal a name. Reidentification is possible with extra information.
Identifiable data: The data either contains a direct identifier (name, address, account name, recognisable face or voice, plate number) or carries a token this system uses to look up legal identity during processing.

Who completes the loop?

Human decides: This mode suggests; a person decides what to do next. The AI is always advisory — a human is in the loop on every decision. Example: a triage tool ranks cases for a clinician who chooses which to see first.
Human executes: This mode decides; a person carries out the result. Example: an optimizer plans the day’s trash-collection routes, and drivers run them.
Autonomous: This mode decides and acts on its own. No person reviews each decision or carries out the resulting action.

Definitions from the DTPR standard. Amber is about your data, violet about who decides. The fuller the shape and the deeper the colour, the more identifying the data or the less a person is involved.

What you can do

Ask about this system

Questions go to the Helpful Places, not the vendor.

Your rights

Right to Be Informed of AI UseGC employees are informed that they are interacting with an AI system before using the chatbot. The register confirms: AI use is disclosed to users.
Right to Algorithmic TransparencyThe system is listed in the Government of Canada's public AI register, which describes its purpose, capabilities, data sources, and accountability. Source citations accompany every answer, making the retrieval logic partially observable to users.

Risks and safeguards

Societal & cultural harmThe system could provide incorrect or outdated policy guidance, leading employees to act on inaccurate information.Safeguard: The system cites source documents with every answer so users can verify guidance against official policy; guardrails and access controls constrain outputs to the policy domain; a feedback and flagging mechanism allows users to report problematic responses.