![[=] Equal Experts](https://www.equalexperts.com/wp-content/themes/equalexperts/assets/logo.svg){kind=logo}
Pioneering responsible AI since 2009
We build AI services into businesses using MLOps and composite AI system approaches. Applying modern engineering practices to the development of AI systems means organisations can rapidly develop, deploy, test and iterate in this complex and fast-changing area of technology.
Simplifying the complexities of using AI
Our team of senior engineers and data scientists have helped large enterprises and government departments understand the benefits and risks of AI systems. We help you and your teams understand, in human language, how AI works and how it might enhance your operations.
Find out how you can put AI to use responsibly, securely, and efficiently.
Travelopia used GenAI to reduce response times and enhance customer interactions.
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How cloud search saved money and increased revenue
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Using events to better predict and prevent financial fraud with HMRC.
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Make your developers even more efficient
Your developers are already using AI co-pilots to expedite manual work, write the first draft of code, analyse existing code, or using prompts to make existing code better.
Get actionable insights from large, unstructured data
94% of business leaders feel they can get more value from their data. Organise and structure your messy data into actionable intelligence to make better decisions with AI — or have AI make those decisions for you. This could mean protecting our business from fraud or analysing claims and complaints to direct your operations staff to the highest value work.
Transform customer service operations
Reduce customer service costs by leveraging generative AI to help answer customer questions. Improve conversion by providing better product recommendations or promotions by applying AI to your customer’s online buying experience.
Ensure your data quality is AI-ready
Your AI technology is only as good as the data that powers it. We’ve helped enterprises with their data quality, tackling their most costly challenges in data governance, trust, and security, data integration and the development of data pipelines.
Our approach:
Responsible innovation first
Our approach is always looked at through the lens of responsible innovation.
We embrace best practices of engineering excellence and take a risk-based approach to innovation. We:
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Define a clear proof-of-concept
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Adhere to strong policy guarantees
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Create threat models for risk assessment
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Value practical innovation over being visionary
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Focus on business impact over working software
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Balance user needs with business goals
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Practise constant verification, not wishful thinking
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Emphasise learning over knowing all the answers
Find out how you can put AI to use responsibly, securely, and efficiently.
Our AI Services
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GenAI Use Case Discovery
We bring our hands-on experience of working with AI in production to identify where it can benefit you and find achievable use cases which will make a difference.
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GenAI and AI Strategy Development
We help you create roadmaps and backlogs for use cases and the technology stack to support them.
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AI-powered digital products
We fold AI components and models into wider digital products.
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AI platforms
We implement platforms to support, operate and maintain Gen AI and AI use cases.
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MLOps and LLMOps
We build, monitor, evaluate and deploy machine learning and other models so you can make better decisions faster. We follow experimental and iterative approaches to reduce risks in automated decision-making.
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AI engineering
We implement AI solutions in production, creating the environments for continual development and testing to enable reliable operations at scale.
Simon Case
Simon is the SVP of AI and Data at Equal Experts. He has over 20 years of experience across data engineering, data science, machine learning and Generative AI, and he holds a PhD in Artificial Intelligence from the University of Bristol. Simon regularly works at both strategic and implementation levels, helping organisations create and implement their data and AI visions. Simon has been part of the data transformation of numerous clients including Travelopia and John Lewis & Partners.
Our team
Blog
Adventures in how to use ChatGPT – can it answer questions about my business?
Pretty much everyone by now has heard of – and probably played with – ChatGPT (If you haven’t, go to https://openai.com/blog/chatgpt/ to see what all the fuss is about.); it’s a chatbot developed by OpenAI based on an extremely large natural language processing model, which automatically answers questions based on written prompts.
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Blog
Balancing business opportunities with responsible innovation in Generative AI
Here’s a fact you probably won’t know about me – I went to the same school as Alan Turing. I mentioned this while appearing as a panellist at the recent Konnecta Ko-Lab: Series 1 discussion in Sydney. Having attended the same educational institution as one of the founding fathers of artificial intelligence, I guess I was always destined to be interested in AI. It’s a fact that certainly grabbed the attention of the audience. AI, particularly Generative AI, continues to captivate technologists and business leaders worldwide. During the panel, we dived headfirst into the technical aspects of implementing AI, but some of the more compelling and challenging audience questions revolved around how organisations can balance AI’s opportunities with the concerns surrounding the new technology.
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Blog
Could MLOps be the key to accelerating your next AI project?
Despite huge adoption of AI and machine learning (ML), many organisations are still struggling to get ML models into production at scale. The result is AI projects that stall, don’t deliver ROI for years, and potentially fail altogether. Gartner Group estimates that only half of ML models ever make it out of trials into production. Why is this happening? One of the biggest issues is that companies develop successful ML prototype models, but these models aren’t equipped to be deployed at scale into a complex enterprise IT infrastructure.
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Blog
How to secure your first generative AI integration
Generative AI is already providing businesses with exciting functionality and productivity gains. However, it isn’t always easy to understand the security implications of GenAI tools. Engineering teams wanting to use or explore these tools may therefore struggle to gain security approval. Most organisations have a regulatory responsibility to risk assess new software. These risk assessments include exercises like architectural reviews, data protection assessments, penetration tests and procurement processes. There are several reasons these activities are difficult when evaluating GenAI tools:
Learn moreWhy Equal Experts?
Ensuring access to data is secure, reliable, and timely requires engineering skills as well as collaboration across a wide group of stakeholders. You need to work with experts that have years of experience working with data and applying rigorous software engineering practices to the flow of data.
Our consultants have experience working across many organisations which means they are well suited to solving technical challenges while working within existing organisational constraints. They work with your teams and engage the wider organisation to ensure work is aligned to supporting business needs and not just a technology initiative. This allows you to realise value from your data initiatives faster, and continuously.
Find out how you can put GenAI to use responsibly, securely, and efficiently.