Your AI Readiness Journey
- Assessment of your data: what you have, your needs and getting there.
- An overview of your challenges and how AI can help.
- Responsible AI and where it relates to your specific needs.
In this digital age, where innovation reigns supreme, Transparity stands at the forefront as your trusted partner for AI consultancy services and the good news for you, we’ve been here a while.
At Transparity, we’re not just keeping up with the future, we’re helping you shape it. Introducing our cutting-edge Artificial Intelligence Consultancy Services – your gateway to transformative business solutions.
A crucial part of any machine learning project is the core data being used / analyzed. Since the building of machine learning models can be involved, it’s always advised to review the overall architecture of a system to ensure that delivery is swift and successful. This is where the AI readiness review comes in. At Transparity AI, one of the very first steps we take is to review everything we need to build a successful machine learning model, that way from the start we have a strong foundation meaning a swift return for you and your teams.
BMT have selected Transparity as their AI partner of choice to explore AI use cases that improve team efficiency and employee experience, and under this partnership are now actively exploring bespoke AI solutions built in the Microsoft Cloud alongside Microsoft’s Copilot offerings.
“We have worked with Transparity to ready our underlying data strategy; because great AI needs great data and we are excited to explore the use cases that generative and applied AI built to meet the very specific needs of our business.”
Simon Willmore – Head of Digital Strategy at BMT
AI Readiness Assessments are the key to unlocking the transformative power of AI and ML for our customers. We delve deep into your organisation to uncover untapped opportunities, leveraging the latest trends and technologies. We continue to be inspired by the stories we hear and thrive on the opportunity to create operational efficiencies and learn together.
Azure Machine Learning is a cloud-based platform that empowers data scientists and developers to build, train, and deploy ML models at scale. It simplifies the end-to-end machine learning lifecycle, from data preparation to deployment, enabling organisations to harness the full potential of artificial intelligence for data-driven insights and decision-making.
Azure OpenAI is a dynamic collaboration between Microsoft’s Azure cloud platform and OpenAI’s cutting-edge artificial intelligence technology. This partnership empowers businesses to harness the potential of AI at scale, driving innovation, enhancing customer experiences, and unlocking new insights for a brighter digital future.
Cognitive Search is a powerful information retrieval technology that combines AI, machine learning, and natural language processing to make data discovery and retrieval more intuitive and efficient. It enables organisations to extract valuable insights from their data repositories and deliver relevant information to users, enhancing decision-making and productivity.
Generative AI is a transformative technology that enables machines to create, mimic, or enhance content autonomously. Whether it’s generating realistic images, human-like text, or innovative designs, Generative AI is revolutionising industries, creativity, and problem-solving by pushing the boundaries of what’s possible in the digital realm.
Microsoft Copilot is a revolutionary AI-powered coding assistant integrated into Visual Studio and making it’s way into the entire toolset. It assists developers by offering context-aware code suggestions, auto-completions, and documentation, streamlining the coding process, and promoting best practices for more efficient and reliable software development.
Transparity’s AI Consultancy Services are your gateway to realising the full potential of AI. Together, let’s revolutionise your business and shape a brighter tomorrow. As part of our AI projects, our experts start with a Readiness Assessment which is designed to empower you with a clear understanding of the needs, impacts and potential of AI as a practical solution to your organisation’s biggest challenges. Over the course of a few days we’ll take a comprehensive look at your data as well as the needs of the business; to establish whether you’re ready to take advantage of AI and machine learning, and how they can support your goals. Register your interest today.
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As a part of the initial scoping sessions, a key part of the Transparity methodology is Discovery.
We carry out an AI / ML readiness assessment which comes in the form a number of workshops with key personnel in order to determine whether a data science project is feasible and what groundwork (if any) needs to be done before a project can begin. As a part of this readiness assessment there are a number of components which are looked at, some of which are:
• Data Availability
• Data Quality
• Data Transport Architecture
• Access to Tooling
• Reporting Maturity
Being a Microsoft partner, Transparity leverage all of the security, consistency and functionality of the Azure suite of tools.
This includes Azure DevOps for version control and project tracking, Azure AI insights (previously Azure Cognitive Services) for machine learning modules and code, Azure AD (soon to be Entra ID) for security around access to data and model development.
Machine Learning Contains Two Main Schools of Technology: Supervised and Unsupervised
Machine learning and Artificial Intelligence are centered around innovations which allow computer programs to be trained / exposed to data sets and for the program to either learn pre-determined patterns within the data set so they can be recognized in future data sets or can automatically detect patterns within unknown data sets. These are known as supervised and unsupervised learning, respectively.
As part of the Azure suite of tools, there are a number of options available when it comes to choosing the correct environments for building machine learning models.
As a part of the project, training will be provided to ensure you understand the structure of the models, the layout of the environment and the location of support materials.
All of this will aid you in diagnostics and model support, and riven ownership of the solution delivered. As a part of this statement of work, a support package will be developed in agreement with Transparity to ensure that models are supported where needed. There are key components that should be understood (where possible) which will allow the business support team of the models to aid in diagnostics and determine any modifications needed.
This can be managed as part of a standard Support and Minor Mods agreement where you have one.
Data Science solutions delivered, as with most data science solutions, require maintenance, modifications, and issue resolution from time to time.
Transparity also like to be able provision time to help clients with small changes or answer queries on an ad-hoc basis, without the need to raise PO’s or book in work. We offer a combined approach to support and minor modifications.
A typical Transparity client would have 4-5 days per month (1-2 days for support and maintenance and 3-4 days for minor modifications).
With over 20 years’ experience in tech, Alister takes the lead on our Data & AI practice. Alister has worked in the wonderful world of data, analytics and business intelligence throughout his career and has been part of the Microsoft Partner ecosystem for decades. With a passion for helping clients harness tech & data that makes an impact to organisations every day.
Learn how DAA achieved a consistent baseline reporting capability and full analytics associated with these systems.
How leading fresh cosmetics giant Lush brought together disparate data sources for deeper customer insights.
McCarthy Stone approached us as they were transitioning some key systems in the business. They recognised the value of data and the need to put in place a data strategy.
