Historically, automation has often relied on standardization — and accounting has been no exception. For years, we've seen tools built on template-driven thinking, comparable to industrial mass production where components or products are manufactured to function the same way for everyone.

In accounting, standardization works well in certain areas — just as some standardized components are essential in manufacturing. When building a complete product, like a car or a complex industrial system, it makes no sense to reinvent what already works efficiently. A well-designed standard component almost always outperforms a bespoke one when the task allows for it.

What's changed is the rise of AI, bringing new capabilities in contextual matching. For the first time, we can address challenges that lie at the intersection of standardization and client-specific customization.

However, applying full standardization to the accounting process of any arbitrary company rarely works. It performs well when the end product is acceptable in a standard form — like buying a car off the lot or delivering a financial report for a solo consultant whose operations resemble another. But the reality is, most businesses differ significantly — and their accounting needs reflect that complexity.

Client-specific customization has traditionally been expensive. What AI enables — particularly through contextual processing — is the ability to deliver tailored services without additional effort. The system is designed to adapt to the client, not the other way around.

In broad terms, companies vary greatly. As a result, delivering a fully standardized accounting product is neither practical nor effective. Some processes can and should be standardized, but fully automating the entire accounting process — such as continuous bookkeeping — requires artificial intelligence. AI's strength in contextual matching allows us to handle individual documents, transactions, and journal entries while also recognizing larger patterns, company-specific contexts, or even industry-wide nuances.

By building our product around this principle, we achieve something traditionally seen as a trade-off: delivering a highly automated yet deeply customized accounting service.

Our platform can be tailored not just at the individual client level, but also across industries and even entire accounting firms. This is possible because we seamlessly combine classic, standardized processes with AI-driven contextual processing — integrating them into a cohesive, scalable system.

Lastly, it's important to recognize that accounting itself isn't a one-off product — it's a continuous process. Our solution is designed to adapt to the technical and regulatory landscape surrounding that process. It learns from historical data and continuously improves, supporting and automating the workflow in real time. The result is greater data accuracy, reduced costs, and enhanced security — all delivered continuously and intelligently.

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