Throughout the PoC, we will collaborate closely with the organization to identify and develop specific use cases where RAG-based GenAI can deliver significant value. The process includes data gathering, prompt engineering, and iterative testing to ensure alignment with business objectives. By the end of the PoC, we will demonstrate a working prototype that showcases the potential of GenAI to enhance decision-making, automate processes, and drive innovation within the organization.
Week 1: Kickoff and Requirements Gathering
- Requirements gathering: Defining a specific use case based on pain points, identifying data sources.
- Documentation: Develop a project plan with milestones, deliverables, success metrics.
Week 2: Environment Setup and Data Preparation
- Tech environment setup: Provision Azure infrastructure, install & configure data analytics platform
- Data Preparation: Identify & gather data, data cleanup and preprocessing, ensure data security & compliance measures are in place
- Initial Data Load: Perform an initial load into data platform, validate data integrity & quality
Week 3: Solution Development
- Solution Design: Design data models, outline analytics workflows and processing pipelines
- DevelopmentImplement data ingestion and transformation processes, develop ML models, dashboard & reports for visualization
Week 4: Testing and Refinement
- Testing: Functional testing, validate results against success criteria
- Refinement: Optimize data models and processing workflows for efficiency, enhance dashboard & reports
- User Training: Training for end-users and administrators, creating user-guide & documentation
Week 5: Demonstration and Handover:
- Demonstration: Present final solution along with key insights
- Stakeholder Review: Gather feedback and discuss next steps
Benefits:
- Innovation Validation: Tests the viability of innovative AI ideas in a real-world setting before committing to full-scale implementation.
- Stakeholder Engagement: This activity demonstrates GenAI's potential to stakeholders, building support and enthusiasm for AI initiatives. Demonstrates the potential of GenAI to stakeholders, building support and enthusiasm for AI initiatives.
- Focused Investment: Identifies the most promising AI use cases and ensures resources are invested in high-impact projects.
- Risk Reduction: Mitigates the risks associated with AI adoption by validating concepts on a smaller scale.
- Custom Solutions: Develops AI models and solutions tailored specifically to the organization's needs and data.
- Performance Insights: Provides insights into the performance and scalability of GenAI applications within the organization's environment.
- Rapid Prototyping: Allows for the quick development and iteration of AI models, enabling faster innovation cycles.
- Capability Assessment: Evaluates the organization’s infrastructure and readiness to support AI technologies.
- Improved Decision-Making: Enhances decision-making capabilities with AI-driven insights and data analysis.
- Competitive Advantage: Positions the organization as a leader in AI adoption, leveraging cutting-edge technology to stay ahead in the market.
Technology Stack: Azure Data & AI Services include Azure Data Factory, Azure Cosmos DB, Azure Synapse Analytics, Azure Data Lake, Azure Machine Learning, Azure OpenAI Services, Fabric Data Science, Copilot Studio, Azure AI Studio
Price:
Price for this PoC will vary based on the complexity and scope of the engagement.