AI integration

Our approach is to identify the practical opportunities where AI can deliver the greatest return on your investment. We start by understanding your strategic goals and then integrate AI to solve your specific challenges, all while ensuring every solution is built on a foundation of ethical and responsible use. The result is a powerful tool that works for you, giving you the ability to search and relate information from vast content archives, automate workflows that empower your team, and deliver a seamless experience for your users.

AI can make large information archives instantly searchable, guide users to relevant resources faster, automate repetitive tasks, and help monitor for accessibility or security issues. The result is improved transparency, efficiency, and user satisfaction without increasing operational risk.

We follow strict data governance, encryption standards, and privacy-by-design principles. All integrations are vetted against accessibility and security requirements, and we ensure compliance with applicable regulations such as GDPR, HIPAA, AODA, and WCAG.

Our services include, but are not limited to: AI-powered search, content summarization, chatbot and virtual assistant deployments, document classification, workflow automation, and accessibility compliance monitoring. Each solution is customized to your organization’s use cases and constraints.

Our approach to integrating AI is always fit-for-purpose. We believe the tool must match the task, so our selection process is grounded in your specific strategic needs and operational realities.

We start by defining the precise business problem you need to solve and conducting a thorough assessment of your data assets, as the quality and nature of your data are often the most critical factors. From there, we evaluate a shortlist of potential models—whether open-source or commercial—against a strict set of criteria: performance and accuracy for your specific use case, total cost of ownership, scalability, and crucially for public sector and regulated industries, data security and compliance with privacy legislation.

This rigorous evaluation allows us to weigh the trade-offs between highly customizable open-source models and powerful commercial APIs. It ensures we select a solution that is not only effective and transparent but also secure, maintainable, and aligned with your long-term goals.

Not typically. Our approach is to augment your team, not replace it. AI handles repetitive or data-heavy tasks so your staff can focus on higher-value work such as strategy, service delivery, and complex problem-solving.

This is one of the most important and difficult challenges in AI. We believe no AI system is completely free of bias or infallible. Our process, therefore, focuses on a rigorous system of checks and balances designed to actively mitigate this risk, starting with the data itself and continuing through deployment and ongoing monitoring.

Since we integrate established, purpose-built AI solutions rather than build models from scratch, our process focuses on your data inputs, diligent selection, and comprehensive testing during implementation. We prioritize models from reputable providers who are transparent about their data governance and bias mitigation strategies, ensuring their approach is suitable for your organization.

Our primary focus is on how the AI is used within your application. During testing, we evaluate the model’s outputs against a diverse set of user scenarios, defined in discovery, to check for output disparities. For example: An AI-powered intranet might give a correct answer about parental leave to a senior doctor, but the wrong answer to a new nurse because it doesn’t check their union agreement. Blue Goose’s robust testing protocol makes sure this doesn’t happen. We employ robust, documented testing procedures, that account for different roles in your organization to ensure it works correctly for everyone.

For any application involving sensitive or high-stakes decisions, we mandate a ‘human-in-the-loop’ review process. This ensures a human expert validates the AI’s output before it’s finalized, providing an essential layer of oversight. After launch, we believe in transparency and implement monitoring to track performance and provide feedback mechanisms for users to report problematic answers.

Success is measured against the specific goals we define together during discovery.

Before we move to design and development, we work with your team to establish clear, measurable KPIs based on your objectives. For one project, success might be defined as improving the user experience, measured by higher task completion rates, increased revenue, or better user satisfaction scores. For another, it could be increasing operational efficiency, measured by the reduction in time your staff spends on a specific workflow. We establish these targets upfront and then use analytics to monitor performance after launch.

Most likely—we would need to audit your system to give you a definitive answer. We design integration points, such as APIs, to work with older platforms while maintaining performance and security. This allows organizations to modernize without replacing entire systems.

We provide tailored training for both technical and non-technical staff. This includes hands-on sessions, reference guides, and best practice policies to ensure your team understands how to use your platform’s features effectively and efficiently.

Simple integrations like AI-powered search can be deployed in 6–8 weeks. More complex projects involving multiple workflows or systems may take 12–20 weeks, depending on scope and compliance requirements.

Our approach to data privacy is tailored to each project because the requirements depend entirely on the sensitivity of your data, the AI model being used, and your specific compliance obligations. We follow a “Privacy by Design” methodology, making data protection a foundational part of the strategy, not an afterthought.

During discovery, we work with your team to conduct a privacy and security assessment. This allows us to architect a solution that meets your exact needs, whether that involves advanced data anonymization, strict access controls, or selecting a self-hosted model to maintain full data sovereignty.

For our public sector clients, we ensure the solution architecture adheres to all jurisdictional requirements, including data residency laws like FIPPA (or PHIPA). This guarantees your data is handled in full compliance, allowing you to leverage AI while rigorously protecting your organization’s and your users’ privacy.

We provide an expert, external perspective that is essential for high profile projects. Our team has over 20 years of industry experience, including a decade focused on large public sector and non-profit projects.

Blue Goose focuses on practical, secure, and compliant AI solutions that deliver measurable value, balancing what’s possible with what’s pragmatic. Every project is handled directly by our small, senior team. We don’t outsource our work, ensuring integration is done right the first time.

Our team holds certifications from the Nielsen Norman Group (NNG) and Google in UX research and design, and we are Certified Professionals in Accessibility Core Competencies (CPACC) from the International Association of Accessibility Professionals (IAAP).