For nearly two decades, I’ve worked in roles where data was supposed to make everything easier—where it promised to provide clarity, help make decisions, and lead teams to success. Instead, what I often faced was a mess. Data scattered across tools, locked in spreadsheets, stuck in CRMs, buried in emails. Each time I needed to pull things together to get real insights, it felt like wading through quicksand. The simplest question: “What is the performance of such campaign?” or “How is the conversion rate of our leads *really* evolving this quarter?” would take hours, days to unearth, to clean up, especially if we were looking for accurate metrics. Sound familiar?
This isn’t just a minor inconvenience. It’s a massive problem. And while it is a problem faced by any function, it is especially prevalent in commercial operations – namely sales enablement, marketing, CX and revenue operations (or RevOps). These are folks that don’t often face actual customers but that are expected to make sure the engine works. They rely on accurate, timely data to drive decisions and revenue. That is, in fact, their job: to extract insights related to leads, prospects or clients to make sure the business can advance faster, better, and to predict how revenue or churn (among other key metrics) are going to evolve over time.
And in today’s AI-powered world, the gap between potential and reality is only growing. We hear about AI breakthroughs almost daily—ChatGPT’s explosion onto the scene, for example, has been nothing short of transformative. It’s reached more than 200 million weekly active users, and the number just keeps growing.
Like a good friend of mine mentions in his recently published book: How did we get here? Gradually, then all of a sudden.
But what good is advanced AI if your data is fragmented, unstructured, and impossible to manage?
This is the problem that Tinkery was created to solve.
Commercial data is broken. Let’s fix it.
I’ve been around, as they say.
I’ve led marketing, communications and sales teams, and have also been a part of those. I’ve felt on my own skin the frustration of having “dirty” information in our CRM and needing months (yeah, months!) to clean up all leads, unify properties and properly structure the whole database. Often, the CEO or other C-level executives do not understand what’s going on: why can’t Marketing, Sales or Customer Success answer such simple questions?
The problem is not about the qualifications of your team – I’ve been lucky to work with excellent “operations” individuals throughout my career, that’s not the issue – but about data overload and data quality, which always leads to decision paralysis or, what’s almost as bad, decision by gut-feeling.
A RevOps manager struggles to optimize the sales pipeline because their data is locked in silos—some in the CRM, some in spreadsheets, some in marketing reports. A marketing ops professional spends hours piecing together campaign performance from half a dozen platforms, only to find that critical insights are missing or that certain leads’ contact information is incorrect, or that the CRM is using different parameters for the same thing. It’s frustrating, and worse—it’s costly.
Tinkery is here to change that. We believe that data should empower teams, not overwhelm them. That’s why we built a platform that takes the chaos of fragmented data and transforms it into something meaningful.
All LLMs are zero-shot inference, they have all the knowledge, but using them to make ontologies (context maps) is hard through zero-shot.
Tinkery allows you to interact with your data in zero-shot prompting, by transforming such prompt into a multi-shot prompt by leveraging the ontologies it created.
In other words, Tinkery doesn’t just clean your data—it gives it context and creates a narrative from the scattered pieces. And, compared to other tools, it builds a picture that evolves over time, not just a one-off photo.
A recent report from McKinsey found that companies leveraging Generative AI could increase sales productivity by 3 to 5 percent of current global sales expenditures. That’s already meaningful, but it’s not even counting its biggest upside, the potential improvement in sales and customer retention by knowing who to target when, and how to bring them more effectively to a purchase or upsell.
But here’s the catch: most teams don’t have the luxury of dedicated data scientists or engineers to sift through and organize that data. That’s where Tinkery comes in—we’re making it possible for non-technical users to harness the power of AI without having to wade through the complexity.
What’s Next?
In just a few weeks, we’ll be launching our freemium version of Tinkery. This is your chance to experience firsthand how Tinkery can help your team turn fragmented, unmanageable data into actionable insights. If you’ve ever felt the frustration of missing out on business opportunities because of disjointed data, now is the time to change that.
Want to be one of the first to get access? Sign up now and join us on the journey from data chaos to clarity. You’ll wonder how you ever managed without it.
After all, data should work for you—not the other way around.