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AI Assistant for Government Employee Productivity

Inform · Employment & Work · Research & Development

What it collects that can identify you

Sensitive personal information
Identifiable data
  • Employees interact with the system using their GC accounts; future MS Graph integration would provide access to personal email, calendar entries, and SharePoint content associated with identifiable individuals.
About behaviour
Pseudonymous data
  • User queries, prompts, and interaction histories submitted to the system may be logged and used to contextualize responses or improve the system. The register confirms personal information is involved.

Also collects operational data, which is anonymized data.

Run by
Indigenous Services Canada (ISC)
Where
No fixed location
Kept
Retained not specified in register
Shared with
Accountable organization
Your copy
You cannot see the data it holds about you. What you can do

What it is for

InformEmployment & WorkResearch & Development

This system is an AI-powered chatbot and agent interface deployed internally at Indigenous Services Canada for use by Government of Canada employees. It supports tasks such as document creation, summarization, question answering, image generation, and code execution by connecting employees to one or more AI models. Users should be aware that the system currently does not disclose to users that they are interacting with AI.

What it collects and what happens to it

Data taken in

Sensitive personal information
Identifiable data
  • Employees interact with the system using their GC accounts; future MS Graph integration would provide access to personal email, calendar entries, and SharePoint content associated with identifiable individuals.
Operational data
Anonymized data
  • The initial phases focus on internal service-related data as knowledge base inputs, including organizational data sources similar to those used by the Radia Pro solution, such as policy documents, procedures, and service guides.
About behaviour
Pseudonymous data
  • User queries, prompts, and interaction histories submitted to the system may be logged and used to contextualize responses or improve the system. The register confirms personal information is involved.

Processing

Language Models
  • The system interfaces with one or more underlying AI language models to provide chatbot, summarization, document creation, and question-answering capabilities. The specific model(s) are not disclosed in the register entry.
Speech & Audio
  • The system includes both speech-to-text and text-to-speech capabilities, enabling voice-based interaction for employees and spoken output from the AI.

What it does

Creating (Generative AI)
Human decides
  • The system generates text, documents (Word, PowerPoint), images, and code in response to employee prompts. A human user reviews and uses the generated content; the AI does not act on its outputs without human direction.
Acting (Agentic AI)
Human executes
  • The system supports agent-based processing and multi-tool orchestration, enabling it to plan and execute multi-step workflows such as querying knowledge bases, executing code, and coordinating tools. Future integrations with MS Graph may enable scheduling and email actions.
Sensing (Perceptive AI)
Human decides
  • The system includes speech-to-text and OCR (optical character recognition) capabilities, enabling it to process spoken language and scanned documents into structured text that can be further processed.
Understanding (Semantic AI)
Human decides
  • The system uses semantic understanding to query knowledge bases and return relevant information, summaries, and matched content from organizational data sources in response to employee queries.

Outputs

Generated content
Anonymized data
  • The system produces generated text, Word documents, PowerPoint presentations, images, and code outputs in response to employee prompts. These outputs are reviewed and used by human employees.
A recommendation or prediction
Anonymized data
  • The system produces summaries and advisory outputs (answers, suggestions, analysis results) that employees use to inform their work. These are recommendations, not binding decisions — a human employee decides how to act on them.

Run by

Indigenous Services Canada (ISC)
  • The federal department responsible for deploying and operating this AI chatbot and agent interface for internal Government of Canada employee use.

Government of Canada AI Register — Pro B AI Chatbot

Built by

LibreChat
  • LibreChat is the open-source software platform providing the chatbot and agent interface. The system is developed using open-source components with an aim to share code across departments.

Government of Canada AI Register — Pro B AI Chatbot

Kept for

Retained not specified in register
  • The register confirms personal information is involved but does not specify a retention period. Retention of interaction logs and generated outputs should be governed by Treasury Board and ISC records management policies.
  • Duration: not specified in register

Shared with

Not available to me
  • The system is an internal government tool accessible only to GC employees at Indigenous Services Canada. Members of the public do not have access to this system or its outputs.
Available to the accountable organization
  • GC employees at Indigenous Services Canada have access to the system for internal productivity tasks. Access is limited to authorized government employees.

Stored

Stored on 3rd Party Cloud
  • The system is built on LibreChat (open source) and is intended to integrate with Microsoft 365 services (MS Graph, SharePoint) in future phases, suggesting cloud-based storage components. Specific storage infrastructure is not disclosed in the register.
  • Duration: not specified in register
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 should be informed when they are interacting with an AI system. The register currently records that AI use is NOT disclosed to users — this is a gap. Employees are encouraged to raise concerns with the Indigenous Services Canada Privacy Office or their manager.
  • Right to Algorithmic TransparencyGC employees have the right to understand, in general terms, how the AI system processes their inputs and generates outputs. Information about the system's capabilities is documented in the user guide feature of the tool. Questions about how the system works can be directed to the Indigenous Services Canada project team.
  • Right to Purpose LimitationPersonal information processed by this system should only be used for the internal service productivity purposes for which it was collected. The register confirms that initial phases focus on internal service data, with more sensitive data use requiring additional risk assessment and engagement before being introduced.

Risks and safeguards

  • Reputational harmAI-generated content (text, images, documents) may be inaccurate, misleading, or misattributed, potentially causing reputational harm to employees or the department if acted upon without review.Safeguard: Initial phases focus on internal service-related data with lower sensitivity; risk assessments are required before expanding to more sensitive data; human employees review and act on AI outputs.
  • Loss of autonomyThe system does not currently disclose to users that they are interacting with AI, which undermines informed consent and user autonomy. Future agentic integrations (email, calendar, SharePoint via MS Graph) could enable the system to act on behalf of users without clear boundaries.Safeguard: AI use disclosure is noted as 'No' in the register — this gap should be remediated; agentic features are deferred pending further risk assessment; scope is limited to internal service data in initial phases.
  • Civil liberties harmLack of AI disclosure to users (confirmed in the register) may violate employees' right to know when they are interacting with automated systems, a basic transparency expectation in public sector AI governance.Safeguard: The register records 'AI use disclosed to users: N' — immediate remediation through mandatory disclosure notices is recommended; the department should align with Treasury Board guidelines on AI transparency before expanding the system's scope.