Steve Salvin is the founder and CEO of Aiimi, an AI platform which has been quietly scaling since 2013. Having bootstrapped the corporate since launch, Steve has grown Aiimi to 8-figure revenues and their tech is utilized by the likes of the FCA, PwC, and the UK government.
Steve has been working in tech for the reason that 80s (even studying AI at university) and is a serial entrepreneur. He’s an enormous believer in constructing AI and technology that empowers users and offers them more control.
Aiimi’s tech allows corporations to seek out and make sense of their data – bringing together what is usually a sprawling mass of knowledge, documents, and digital information – helping teams access information immediately.
You initially studied AI over 30 years ago, what were you studying and what initially attracted you to the sector?
I studied Computation during my Bachelor of Science on the University of Manchester in 1987. It was a natural alternative; following a fascination for computers that began after I was just a toddler. I remember the day I got one in all my very own on the age of 12 – I spent hours teaching myself to code in my room. Since my school didn’t teach computing, I went on to persuade my teachers to effectively rearrange the timetable, in order that I could slot in lessons at a close-by college that did. This paved the best way for me to check Computation at university, where I even studied a module in AI all those years ago. My profession has been on this field ever since. Ultimately, it’s my passion for computers that first led me here and which has kept me here.
Could you share the journey behind your first startup that deployed next-generation document management and workflow technology, and what your key takeaways from this experience were?
I founded my first startup in 1996, having been inspired by a project I used to be working on in my previous role at PwC. The project opened my eyes to the challenges waiting to be solved through enterprise content management, and more revolutionary workflow technology. And so I arrange APS. We built next-generation content management tools and worked with the likes of HBOS and Bupa. We grew quickly and were a 20-strong team inside just two years. I learned loads in these early days as a first-time founder, but the important thing takeaway was don’t be afraid to make decisions – if it seems to be a nasty decision you possibly can make one other one. You have got to maintain moving in a fast-moving startup environment.
Could you share the genesis story behind Aiimi?
After I sold APS, I worked for OpenText for a number of years. But I discovered that I missed being in the driving force’s seat and dealing closely with customers. Plus, my time within the industry up so far had opened my eyes to an issue that wasn’t going away: the large disconnect between transactional structured data and unstructured content inside organisations.
It struck me what number of businesses lacked insight into what data was being created, shared, and used across their teams, and the way. The more data businesses accrued and stored in numerous systems, the more serious issues became. And, unable to seek out the knowledge they needed to do their jobs, staff were being slowed down, doubling up on work, and making misguided decisions. This was the issue I set out to unravel after I founded Aiimi in March 2007. Our mission is to assist businesses find and make sense of their data, giving them the knowledge they should unlock efficiencies, spot opportunities, and de-risk their operations. Put simply, we connect people to insight.
Your technology is utilized by significant clients just like the FCA, PwC, and the UK government. What makes Aiimi’s AI platform stand out to such high-profile clients?
We’re extremely proud that our customers decide to work with us as a homegrown British AI business. Our approach is what helps to set us apart. We’re not only a software vendor; we’re an experienced team of knowledge, digital, and AI experts who thrive on understanding the precise details of the challenges our customers face. It’s our firm belief that technologies like AI ought to be utilized in an ethical way that offers users more, not less, control over their data. We also strongly imagine there isn’t a “one size matches all” approach to data management.
We invest an enormous period of time into attending to know our customers in order that we are able to deploy the fitting technology solutions and tailor our services in step with the needs of individual organisations. And since we understand that these needs change over time, we proceed to work closely alongside our customers to evolve our offering throughout our relationship with them.
Besides our industry-leading consulting services, the opposite thing that sets us apart is the cutting-edge technology that we’re capable of offer our customers. Our continued investment in Aiimi’s IP, the Aiimi Insight Engine, alongside generative AI and emerging technologies, ensures that we’re capable of serve essentially the most novel use cases around, and solve even the thorniest of business challenges.
You are a proponent of constructing AI that empowers users and offers them more control. Are you able to elaborate on how Aiimi’s tech achieves this and the impact it has in your clients’ operations?
At Aiimi, we imagine that AI should give users more, not less, control over their data. AI ought to be a driver of knowledge quality and brand-new insights that genuinely help businesses make their most significant decisions with confidence. That’s why we construct AI tools that help organisations see their entire data picture, automate data governance, and enable them to get to the answers they need. Since well-governed data is behind any secure and successful AI application, our tools also put the ability in organisations’ hands to adopt models more widely in a protected and controlled way – when we are able to get an organisation’s trickiest, most complex unstructured data into the fitting format and of a high quality that might be utilized by AI models, that’s where they’ll unlock real business value.
Our platform also gives authorised users full visibility into our AI-powered answers. We use fully explainable approaches to AI , in order that users with permission to achieve this can use the platform’s interactive dashboards to look “under the hood” and see exactly what data models are working with, what insights they’ve gleaned, and the way they arrived at them. This provides our customers a comprehensive understanding and audit trail for a way their data has been used to tell decision making; a hugely vital step in making AI-powered answers usable and protected for enterprises.
With the Aiimi Insight Engine, you aim to unravel the issue of underutilized data inside enterprises. Could you explain how the engine works and the type of insights it has unearthed for businesses?
A typical enterprise uses a whole lot of various systems to store data. The issue is that these systems quickly grow to be outdated and sometimes don’t speak the identical language. In consequence, the knowledge inside them is lost or forgotten about, and is unimaginable to seek out when employees need it. Recent Gartner research shows that 47% of digital employees struggle to seek out the knowledge needed to effectively perform their jobs. The Aiimi Insight Engine addresses this disconnect by creating an information mesh layer on top of an organisation that connects these disparate sources.
The Aiimi Insight Engine discovers, enriches, and joins-up information in order that it will possibly be immediately accessed by those that need it – plus,brand-new insights are unlocked by combining previously disconnected datasets, like structured telemetry data and unstructured customer call transcripts. This helps teams realise efficiencies, and glean the insights needed to unravel business challenges and spot opportunities. At the identical time, the tool pinpoints and secures sensitive information, helping organisations de-risk their operations. Naturally, the info insights and possible use cases vary hugely from one organisation to the subsequent. That is why we work closely alongside our customers, to assist each get one of the best out of the Aiimi Insight Engine.
Our recent work with a Government department offers example. Their team of analysts needed to access accurate information summaries from data from multiple sources, to provide timely and precise briefings to the federal government and public. They typically used open-source data, like trusted news outlets and web sites. But with this volume of knowledge ever-increasing, finding, retrieving, and collating all this information had grow to be increasingly difficult. They required an AI-powered solution to streamline this process and enable them to create these briefings more efficiently and effectively. They selected the Aiimi Insight Engine for its ability to intelligently process large datasets – on this case, those news sources and web sites – to seek out relevant information, before transforming this data right into a consumable set of insights using secure Generative AI and Extractive AI models. With the assistance of our technology, they were capable of increase their efficiency and enable more practical decision-making.
The risks of ‘shadow’ AI might be substantial for businesses. Could you define what shadow AI is and discuss the risks related to it?
‘Shadow AI’ refers to when employees bolt AI tools (like ChatGPT) onto their work systems for the sake of ease and efficiency, without their employer knowing or consenting to the technology. Employees could have good intentions. But shadow AI can pose serious data security risks.
Firstly, employees could also be feeding AI models sensitive information without realising – and there’s no guarantee this data won’t find its way into the general public domain. Generative AI tools that haven’t been vetted by IT leaders can also be unreliable and produce inaccurate results, particularly if used for inappropriate use cases. Inaccurate results that seem like incredibly convincing to users, often known as ‘hallucinations’, often go undetected. And the results of poor decisions that follow have the potential to be hugely costly for corporations.
To avoid shadow AI, it’s vital to teach teams on what protected and ethical AI practice looks like, and supply clear guidance on which AI tools can and might’t be used securely at work. I’d advise avoiding public large language models altogether in the case of your corporate data. As an alternative, spend money on protected, reliable and robust AI tools that enable employees to do their jobs effectively and efficiently. This fashion, staff won’t must resort to unauthorised, potentially insecure tools in the primary place.
Implementing enterprise AI safely and securely is critical. What steps does Aiimi take to make sure the security and integrity of its AI solutions?
Security is baked into the Aiimi Insight Engine and all of our technology. Our built-in AI & Data Governance toolkit gives our customers complete control, so that they know exactly where their personal or sensitive data lives (and might remediate any issues) and the way our AI platform operates of their business. They can even “track and trace” every user interaction with their AI system and auto-verify the sources used for AI-generated answers with full traceability and data lineage. Because we use a variety of AI models, each auto-selected by our enterprise AI platform for his or her reliability, security, and price to perform a given task, we are able to tightly control aspects like security, speed, and price based on individual customer requirements. For instance, ensuring AI models chosen are used in step with ISO 8000, or that they consider NCSC guidance, GDS, and/or DevSecOps principles.
Looking ahead, what future developments in AI and data management are you most enthusiastic about, and the way is Aiimi preparing to integrate these advancements into its offerings?
The chances for AI-driven data insights are limitless – particularly for organisations that get the basics of knowledge governance, data quality, and knowledge retrieval right. For the time being, we’re specializing in exploring one of the best use cases for GenAI in business and developing our product roadmap accordingly. For instance, we’re helping customers discover where essentially the most value might be realised from AI- akin to by turning unstructured data into structured formats that may then be fed into BI reporting to support downstream decision-making. That is an important first use case for businesses just getting began with AI. It provides tangible advantages and has a quick, clear ROI. We’re also supporting our existing customers to take their next steps with AI and ensuring they get essentially the most out of the ever-evolving tech.
We’re planning to expand our headcount over the approaching 12 months, too. We sit up for welcoming recent members to our diverse and inclusive Aiimi community. This strengthened team will enable us to proceed to grow, innovate, and enhance our offering in step with our customers’ evolving needs.
