Canada.ca AI Answers is an AI-powered chat agent to help people get quick accurate answers to their questions about all federal government programs and services. Visitors to Canada.ca are already testing AI Answers with thousands of questions in a series of trials and beta tests across topics ranging from Employment Insurance to Indigenous Status Cards to Measles.
The Canada.ca Experience Office team built AI Answers with one principle: helping all users with their questions comes first, technology, while essential, comes second. The team took a light-weight approach, while still applying the “faster” principles that TBS has developed as a guiding framework. Accuracy, security and operations approaches have all been built in. Through iterative architecture improvements, many rounds of usability testing, rigorous evaluation of accuracy, and improvements after each trial phase, AI Answers is growing into a full Canada.ca service.
Before you think about running a quick hackathon to spin up a government AI help application, read on to understand what production-ready AI for the Government of Canada actually requires and how AI Answers can serve as the foundation you build on, not the project you compete with.
Accurate answers in French require innovative approaches
North American foundation models like those from OpenAI and Anthropic handle French answers and French web addresses (URLs) less reliably than questions in English. They’re trained on mostly English content, and therefore are stronger at producing answers in English. If your team is designing an AI application, keep this in mind. For a successful chat application from the Government of Canada, it needs to provide equal quality in both official languages.
In early tests of AI Answers, the French answers were more likely to be inaccurate. In addition, the French citation web addresses (URLs) were more likely to be hallucinated. Most Government of Canada URLs are crafted in the selected language (eg. …agence-revenu/services/paiements.html and revenue-agency/services/payments.html). We noticed the AI model tended to prefer to just switch the language tags and leave the url in English, or it generated its own translation of the URL, which was often incorrect.
To improve the accuracy in French, the AI Answers team developed an approach that takes advantage of the multilingual nature of AI models. The AI agents receive all search results and web addresses in French with an English translation of the question. Then the main answer agent generates the response in English first behind the scenes. The final step is to translate it back into a French response that follows the Canada.ca writing style. The French response is displayed to the user, with the appropriate citation link to a Government of Canada French page. By the second trial on Canada.ca, this translation approach produced answers and citations in French with accuracy scores almost identical to English and much better than trying to process the question completely in French.
On the English page of AI Answers, a similar approach is used for questions asked in a language other than French or English. For those questions, the search query is crafted in English and the citation links to an English page, but the answer is produced for the user in the same language as their question. English versions are kept in the database for evaluation and analysis. By the second trial, the language of the question was no longer impacting the accuracy evaluations by subject matter experts. We hope that as AI models improve how they use languages other than English over time, we may be able to remove this translation process.
Architecting security and safety at all levels
There are multiple levels of guardrails in AI Answers, from the user experience through to the cloud service. Research and red-teaming showed that longer conversations and longer questions cause context drift and increase reliance on training data instead of authoritative government content. The design therefore prevents users from asking more than three questions per conversation and limits the length of their questions.
Authority to operate (ATO) in the Government digital ecosystem requires significant work by the team across threat detection, incident management, and extensive security engineering.
Bias testing
This work to ensure AI Answers is safe to operate aligns with TBS’s Guide on the use of generative AI best practices to mitigate bias. The team has begun testing bias evaluation techniques that will focus on testing variances in responses based on 15 single-variable changes, as well as large open source safety question sets to ensure inappropriate or harmful content is redacted.
Getting to production-ready for a government service
There’s a difference between building a prototype capable of answering questions and building an accurate, safe, and secure product for millions of clients a month. Production services require:
- Demonstrated duty of care for accuracy: Evidence that accuracy thresholds are defined, measured, and actively managed and supported to ensure responsible deployment. Accuracy should be evaluated by subject matter experts from responsible institutions. Ongoing monitoring through a built-in evaluation process confirms the accuracy of AI-generated responses.
- Privacy protection guardrails: Demonstrated safeguards ensure that privacy risks are mitigated through blocking mechanisms at two stages - a first programmatic stage to detect and block specific keywords and characters (e.g. email addresses, URLs, postal codes, telephone numbers) from being submitted to the AI and a second AI-powered detection stage as a backup. These controls prevent storing and disclosure of personal or sensitive information.
- Safety measures: Safety controls are in place to prevent biased and harmful content. Proactive detection, mitigation, and red-teaming practices address safety vulnerabilities before and after launch.
- Operational reliability practices: Operational practices ensure AI Answers remains reliable, trusted, and secure over time. Defined procedures for monitoring, maintenance, and version control, support continuous improvement and public trust.
- Malicious use prevention: Safeguards are in place to detect and mitigate malicious prompt injections, both static and dynamic. Testing, monitoring, and audits ensure resilience against unauthorized instructions or data exfiltration.
Long description
The diagram is divided into two horizontal swim lanes.
Top lane – “Commercial chat solution (e.g. ChatGPT)”:
A linear pipeline flows left to right: Question → Input Guardrails (Generic/Harm) → Context block containing “Conversation” and “Search” (labelled “Generic/not GC specific”) → Large Language Models (icons for Gemini, Claude, OpenAI) → Output Guardrails (Generic/Harm) → Answer.
Bottom lane – “AI Answers solution”:
Two entry points appear on the left: “External uses” (Canada.ca, AI Answers) and “Internal uses” (Content design). Both feed into Input Guardrails (Privacy/Harm). The context block is larger and labelled “GC specific,” containing six elements: GC System instructions, Conversation, Departmental instructions, Search (GC only), GC & dept skills/tools, and Web Content (GC only). An additional component, “SME Evaluations,” sits below the context block and feeds into a “Continuous evaluation” loop. The context feeds into the same set of LLMs (Gemini, Claude, OpenAI), which connect to an “Agents” node. Agents pass through Output Guardrails (Accuracy/Harm/Bias) before producing the Answer. Arrows from the Continuous evaluation loop return to both the Agents and the Context block, indicating iterative refinement.
Rolling out
The initial technical implementation of the Canada.ca AI Answers prototype was fairly straightforward and happened very quickly. The next stages of testing, evaluation and administration towards building a production service have required a larger experienced team. Understanding user needs, content ecosystems, government service delivery, and maintaining public trust—that requires years of research, testing, and collaboration with teams across government.
Canada.ca AI Answers has a beta test site live at ai-answers.alpha.canada.ca. Teams across government continue to refine system prompts, evaluate answers, and identify new problems to solve. We are working towards a pilot on Canada.ca in 2026.
For IT teams interested in building specialized agents that AI Answers can call for complex program scenarios, or for communications teams who want to customize prompts for their department’s specific needs, reach out to the Canada.ca Experience Office.
Building better government services means building together, not building separately.
AI Answers is a Canada.ca service built by the Canada.ca Experience Office in partnership with the Canadian Digital Service and content and communications teams across government.
Long description
A screenshot of a conversation on AI Answers. It shows the introductory text of the application: Get answers to your [Canada.ca](http://Canada.ca) questions. This is followed by: Answers provided by this AI service are information and not official advice. Improvements are ongoing. It then has an expand/collapse pattern that lets users expand for information about Privacy and AI terms of use. The conversation shown starts with the question, “How to apply for dental?” and it is followed by a response that reads, “All eligible Canadians can now apply for the Canadian Dental Care Plan (CDCP). Check the eligibility checklist before applying to make sure you qualify. You can apply online through the CDCP application page or through your My Service Canada Account (MSCA). It is then followed by a tooltip that reads, “AI can make mistakes, always check your answer.” Below is text that reads, “Check your answer and take the next step:” below that is a citation link for a Government of Canada page as well as a Chat ID. At the very bottom there is a question, “Was this helpful?” with linked “Yes” and “No” responses.