AI Consulting Services

Within the corporate sphere, the fog of uncertainty and the expectation of ROI shrouds AI adoption, obscuring the path with ambiguity regarding use cases, resource requirements, and strategic prioritization. OmniData offers clear direction and expert guidance to navigate the complexities of AI adoption and value creation. Our AI consulting services for Microsoft Azure are designed to help customers get started with or extend their use of Azure by providing the expertise, capabilities, and know-how they may lack in-house or need to augment.

Here’s a summary of our services and what customers can expect from an engagement with OmniData:

• AI and alignment with Business goals: Clarify the evolution of AI and the role it can play in your company. Identify the catalytic factors that help companies derive value from the use of AI and Machine Learning. Align the use of AI with your company specific KPIs and financial value drivers. Incorporate non-technical factors such as culture impact, senior leadership buy-in and responsible AI.

• AI Use case identification and appraisal: Gain an understanding of matured and implementable use cases across different industries. Use OmniData's Use Case design framework to clearly define the business problem to be solved, the suggested solution and the business impact. Prioritize use cases based on value and implementation effort while unearthing the requirements from technology, business processes and human resources.

• Company AI Readiness Assessment: Leverage OmniData's years of experience and exposure to different industries and their adoption of AI in practice to assess your company's readiness. OmniData's assessment methodology will provide a detailed comparison that can be used to assess your AI maturity.

• AI Governance: Learn why it's important to mitigate the influence of bias in models, increase fairness and inclusivity, and ensure transparency, privacy, and safety. Governing AI in companies also requires driving modeling frameworks appropriate to the need and setting up business structures to assess the financial impact of these solutions.

AI engagements include:

• AI Vision: We help create custom object detection models using Azure AI Vision Studio. This service is ideal for customers looking to enhance their visual data processing capabilities.
• AI Language: Our team assists in using language models to interpret the semantic meaning of written or spoken language, which is crucial for improving natural language processing applications.
• Generative AI with Azure OpenAI: We train models to generate original content based on natural language input, helping customers innovate with AI-generated content.
• AI Fundamentals: We offer training on creating no-code predictive models, exploring conversational AI, and more, to build foundational AI skills.
• Innovate with AI in Azure (CAF): This service introduces approaches to innovating with AI, including Machine Learning, AI Applications & Agents, and Knowledge Mining.
• Azure Well-Architected Framework (WAF): We help solution architects build a technical foundation for their workloads using a set of quality-driven tenets, architectural decision points, and review tools.

EXAMPLE IMPLEMENTATION AGENDA:

1. Initial Assessment:

• Understand customer requirements and current capabilities.
• Identify key areas for AI integration and improvement.

2. Planning and Strategy:

• Develop a detailed project plan and timeline.
• Define success metrics and key performance indicators (KPIs).

3. Design and Development:

• Design AI models and solutions tailored to customer needs.
• Develop and test AI models using Azure AI tools and frameworks.

4. Implementation:

• Deploy AI models and solutions in the customer’s Azure environment.
• Integrate AI solutions with existing systems and workflows.

5. Optimization and Monitoring:

• Optimize AI models for performance and accuracy.
• Set up monitoring and maintenance processes to ensure continuous improvement.

6. Training and Support:

• Provide training sessions for customer teams on using and maintaining AI solution

OUTCOMES Engineering Changes: -Implementation of AI models and solutions in the customer’s Azure environment. -Integration of AI capabilities with existing systems and workflows.

Technical Artifacts:

• Custom AI models and algorithms.
• Detailed documentation of AI solutions and implementation processes.
• Training materials and user guides.
• Performance reports and success metrics.

By engaging with OmniData, customers can expect to enhance their AI capabilities, achieve their strategic goals, and drive innovation using Microsoft Azure.

This is a 40-hour service engagement. Actual outcomes and pricing will vary based on project scope.