XU: Tech is really the engine of your app. Why use AI-based technologies?

KC: When we started the company, we envisioned a way for people to literally ask their data for answers, or “chat with your data” as our name alludes to. Our team of data scientists has built a proprietary AI that learns and understands Natural Language (NL), or “human language” – the way we put ideas together in words when communicating with other humans. chata.ai's superpower is translating “human language” into “database query language”, which is basically the “language” a developer would use to search, retrieve, and calculate data stored in a database. Enabling NL-based software interactions is important because it allows people to explore business data in the same way they would ask another human for that information, and it's powerful because it's so intuitive.

XU: How does your forecasting system fit into that picture?

KC: chata.ai's company culture is really based on our teams having the freedom to solve problems they see in the domains we develop in. Our forecasting system was conceptualized out of this culture and driven to the finish line by one of our very talented PhDs and a core team of engineers. They recognized some limitations in the underlying technology around current forecasting systems and the subjectivity introduced to them. Because of our experience in helping machines learn complex and dynamic concepts, we saw an opportunity to leverage those capabilities into a machine-generated forecasting technology.

XU: So, what’s chata.ai's approach to forecasting?

KC: We believe that data reveals the most accurate narrative of the realities of a business. One of the limitations of current forecasting is the level of subjectivity and bias that can be introduced. This often leads to forecasts that are based on how people want the future to look, as opposed to how it will most likely look, based on objective data. It's the complex dynamics in the historical data that ultimately predict the most likely scenarios. We’re after an accurate forecast that’s neither idealistic nor disheartening, it just reflects the reality at hand and offers the most probable, best-case, and worst-case outcomes based on multiple simulations of future scenarios.

With every new transaction in the accounting software, new data is created. Rolling forecasts are valuable to operating businesses, however it’s critical that a rolling forecast is able to adapt its understanding of the holistic businesses narrative as it changes over time. Our forecasting system not only automatically learns from new data as time goes on, it also understands when a predicted forecast was wrong, learns from this variance, and applies what is learned into future forecasts on a go-forward basis.

XU: Forecasting is having a moment in the accounting ecosystem, what do you think all the hype is about?

KC: There’s no doubt that cash flow can make or break businesses, especially when they're starting out or trying to aggressively grow. Risk management is something we all deal with. The economy is volatile, change happens fast, and we can't always be sure of what the future holds. People are looking to make informed decisions, or at least some way to see the potential outcomes of their decisions and where their business is headed.

Forecasting is really a decision-making tool that enables you to make the best decisions possible in line with the business goals you want to achieve. Financial professionals are responsible for helping clients meet those goals, so those questions about the future are a critical necessity.

XU: What makes your forecasting system different?

KC: Our forecasting is automatic, rolling, objective and perhaps most uniquely, a system that learns.

Lots of advisors may be hesitant to offer forecasting support to clients because of how much time it can take. Using machine learning, the forecast builds itself, updates in real time, and accounts for changes in business dynamics as time goes on. If one of your client's customers suddenly starts paying their invoices ten days sooner than they did previously, the system notices that and adjusts the outstanding AR forecast for that specific customer to reflect that. If a new revenue stream is added to the data, it notices that too and makes appropriate changes automatically.

There are already many sophisticated forecasting tools and apps offered in the ecosystem and we're not in the business of replacing those solutions that provide things like manual scenario modelling or manual altering of high-level forecast assumptions. In fact, our plan is to expose our forecasting technology to interested app developers with a vision of providing them with an automated base forecast that is generated from the underlying operational data. Their users can then employ different app-specific tools available for manual adjustments, scenario modelling, etc.

XU: How can financial professionals implement this tool in their practice?

KC: Because our forecasting system is constantly learning and adjusting, users can expect a zero-effort forecast that improves over time as the underlying fundamentals of the business or economy change. That means that financial professionals have the capacity to provide data-driven forecasting services to their clients, offering greater value without adding to their workload.

We see this forecasting system as a means of helping financial professionals empower their clients to achieve key goals and objectives through better decision-making. Rather than presenting inescapable absolutes or wishful estimates, we want to give users the opportunity to see probable outcomes so they can look at the forecast and say “We’re aiming for this target and the data shows us that with some minor operational changes that target is very attainable.” Financial professionals can use the tool to advise their clients to take calculated risks and make better informed decisions.

XU: What excites you most about introducing this new tool?

KC: The forecasting technology that our team has developed is so complex behind the scenes, but it's profoundly simple on the surface, which makes it incredibly user-friendly. That's a very powerful thing.

We believe we have an opportunity to really add something remarkable to our partners' practices and to add unique value to the offerings from other app developers we work with. We are most excited about putting this system to the test, working actively with our customers to bring them new value, and ultimately helping businesses make better data-driven decisions.

The team…

The chata.ai team aims to empower financial professionals and business owners to make data-driven decisions more easily and more often. Through their AI-driven business intelligence platform, users simply ask questions and receive immediate answers, from anywhere, at any time. Integrating directly with Xero, chata.ai offers customizable Dashboards, automated reporting, intelligent forecasting, and more.