Artificial Intelligence
Get ready for AI
Assessment Phase
Take a close look at your organization’s AI readiness — business processes, technology infrastructure, and data assets.
Business Opportunity Identification: Working with stakeholders to identify business processes where AI can deliver significant value. This involves understanding pain points, goals, and data availability.
Data Assessment: Evaluating quality, quantity, and relevance of data needed for training and deploying AI models. This includes data cleansing, labeling, and gap analysis.
Technology Infrastructure Assessment: Assessing the existing IT infrastructure’s capability to handle AI workloads. This may involve storage, processing power, and network bandwidth considerations.
Organizational Readiness Assessment: Evaluating the organization’s culture, skills, and governance structure for AI adoption. This includes assessing leadership buy-in, workforce training needs, and ethical considerations.
From strategy to roadmap
Recommendation Phase
Get your AI strategy on a sound footing with the right solution architecture and implementation roadmap.
AI Strategy Development: Creating a tailored AI strategy aligned with business goals, considering identified opportunities and assessment findings.
Solution Architecture Design: Recommending the most suitable AI approach (machine learning, deep learning, etc.) and designing the technical architecture for the chosen solution.
Implementation Roadmap Development: Creating a roadmap outlining steps for AI implementation including timelines, resource allocation, and risk mitigation strategies.
Get your AI solutions online
Implementation Phase
Ready your teams to move ahead and took full advantage of AI technologies.
Data Engineering and Preparation: Cleaning, pre-processing, and preparing data for AI model training.
Model Development and Training: Developing and training AI models based on the chosen approach and data sets.
Model Deployment and Integration: Deploying the trained model into production and integrating it seamlessly with existing business processes.
Change Management and User Adoption: Developing a change management plan to onboard stakeholders, train users, and ensure effective adoption of the AI solution.
Performance Monitoring and Optimization: Continuously monitoring the AI model’s performance, identifying areas for improvement, and retraining as needed.
Close the gap with specialized services
Additional Services
Make the most of your AI implementation by establishing the right frameworks and methodologies.
Security and Explainability: Enhancing security measures to protect sensitive data and ensure the explainability of AI model based decisions.
Governance and Ethical Framework: Developing a governance framework to ensure responsible and ethical use of AI throughout the process.
Real Estate
Reinstate West Project
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Commercial Properties
Sky Tail Tower
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