Taxiing to the Runway: Deployment and User Enablement
We will configure permissions for different user groups, ensuring responsible Copilot usage. A review of existing systems is Important to Copilot’s success. Connecting Copilot with existing systems and workflows creates a cohesive experience. These inegrations option will be presented to the client. Several pilot programs will be created including pilot groups and specific schedules to gather feedback, refine training, and ensure a smooth transition for everyone.
Soaring Through the Clouds: Adoption and Continuous Improvement
Comprehensive training resources will be provided including ongoing support to address user queries and concerns. We will monitor usage data to understand user behavior, identify areas for improvement and make data-driven decisions about overall enhancements. Rollouts to expand to other teams and logical groups within the company. User Feedback is continuously gathered and leveraged to refine training materials and enhance Copilot’s integration.
Microsoft Copilot Studio: Building Your Custom AI Airship
This platform empowers you to craft bespoke AI solutions tailored to your specific needs. The implementation here involves a more technical journey:
Setting the Course: Project Planning and Data Preparation
We work with the client to define project’s goals, scope, and success metrics. What problem are we solving, and how will the impact be measured? Together with the client, we will Identify relevant data sources and prepare them for training. Ensure data quality, relevance, and alignment with the client’s AI model’s needs. The appropriate AI models will be selected. Training methods are devised based on the project’s requirements and data characteristics.
Building and Testing: From Blueprint to Reality
The team will train and refine the AI model using Copilot Studio’s tools, iteratively improving its performance and accuracy. The model’s performance will be be tested and validated rigorously across various scenarios, to ensure it meets expectations. We will integrate the trained model with the client’s target applications or systems, ensuring seamless data flow and functionality.
Taking to the Skies: Deployment, Monitoring, and Refinement
We will deploy the trained model to a production environment, making it accessible to the users or systems. The team will continuously monitor performance, collect usage data, and identify areas for improvement. Leverage feedback and data insights, we will refine the model and ensure it remains effective and relevant over time.
Our unique approach for successful implementations includes the following pillars
Cultural Compass: We prepare clients for AI adoption by addressing concerns and fostering a culture of acceptance and responsible use.
Security as priority: We prioritize data privacy and security throughout the implementation process, adhering to relevant regulations and best practices.
Governance responsibility: We enable clients to establish clear guidelines and oversight mechanisms for using and managing Microsoft Copilot, ensuring responsible development and deployment.
Our Commitment to
By aligning with ISO 42001, we ensure that our governance practices meet international standards for AI management, promoting security, fairness, and accountability in all AI implementations.
