This interview is with Chongwei Chen, President & CEO at DataNumen.

 

Chongwei Chen, President & CEO, DataNumen

Can you introduce yourself and tell us about your role at DataNumen? What sparked your interest in data recovery and protection?

I’m the President and CEO of DataNumen, where we specialize in developing data recovery and repair software solutions for individuals and businesses worldwide. My journey into data recovery actually began during my Master’s studies at Zhejiang University. I was inspired by an article in Popular Computer Weekly about a programmer named Zhou Yi, who developed shareware by himself and was successfully selling it online, generating substantial revenue.

This sparked my entrepreneurial interest in developing and selling software. My first attempts weren’t exactly success stories – I developed an image viewer called UniView and later a development tool called DLL to Lib, but both received lukewarm market reception with minimal sales. Then came my third product, Advanced Zip Repair, a tool for repairing corrupted ZIP files. Interestingly, my initial motivation for creating Advanced Zip Repair was quite casual – so much so that I can barely remember the exact details now. I believe it started when I spent hours downloading a massive ZIP file from the internet, only to discover it wouldn’t open. However, when I examined it with a hex file editor, I realized that most of the data was actually intact – only the tail end had minor corruption that could be completely repaired, saving me from having to re-download the entire file.

Initially, Advanced Zip Repair was even less successful than my previous attempts – I sold only three copies in six months. I was ready to abandon my ambition completely. However, just before giving up, I made a small adjustment to the business model. That seemingly minor change had an unexpected and dramatic impact – the sales jumped to over $600 on that very month, and by the time I graduated, I had a steady monthly income of over $2,000. This experience taught me something profound about market dynamics and the invisible hand of market forces.

That “first bucket of gold,” as we say, not only determined DataNumen’s future direction but also shaped my philosophy of balancing both market understanding and technical innovation. It’s what led me to specialize in data recovery software and build DataNumen into the company it is today – one that truly understands both the technical challenges and market needs in data protection and recovery.

You’ve been CEO of DataNumen for over 24 years. How has your journey in the tech industry shaped your approach to leadership and innovation?

Looking back on 24 years as CEO, I’d say the journey has taught me that true innovation in our field requires both deep technical patience and strategic talent acquisition. We’ve developed over 30 file repair tools, each specifically designed to handle corruption in particular file formats. This is an incredibly competitive space with very high technical barriers to entry. What I’ve learned is that doing technology work is very similar to conducting scientific research – both require the ability to settle down and focus deeply. Take formats like Outlook’s PST, SQL Server’s MDF, or AutoCAD’s DWG files – these are extraordinarily complex, with format documentation that can span hundreds or even thousands of pages in English. To truly understand these formats and design sophisticated data recovery algorithms, you need what I call the “spirit of moving mountains” – working day and night, reading repeatedly until you achieve complete comprehension. When format specification documentation isn’t publicly available, we have to invest enormous time and energy in reverse engineering. This high technical barrier is precisely why DataNumen has been able to maintain a technological monopoly advantage in the global market for over a decade. But sustaining this requires constant innovation and the right people. My leadership approach has evolved around two key strategies to stay competitive:

First, I leverage the excellent platform that Zhejiang University provides to recruit outstanding master’s degree graduates for our data recovery software R&D and innovation work. These individuals bring fresh academic rigor and cutting-edge knowledge.

Second, I utilize global platforms like UpWork to find highly specialized talents worldwide for software development and innovation. This allows us to tap into expertise that might not be available locally.

The combination of patience for deep technical work and strategic global talent acquisition has shaped my entire approach to leadership – knowing when to dig deep personally and when to find the right people to push boundaries we couldn’t reach alone.

In your experience developing data recovery solutions, what’s the most challenging technical problem you’ve encountered, and how did you overcome it?

The most challenging technical problem I’ve encountered is one that goes to the heart of data recovery: file corruption manifests in countless different ways, and the question becomes – how do you design a system that can recover the maximum amount of data regardless of the specific type or pattern of corruption? Traditional data recovery approaches often work well for specific, predictable corruption scenarios, but real-world file damage is incredibly varied and unpredictable. You might have header corruption, scattered bit flips, partial overwrites, or complex combinations of multiple damage types.

My solution drew heavily on my background in artificial intelligence. During my undergraduate studies, I had the privilege of working in the AI laboratory under Professor Wu Zhaohui – who later became the President of Zhejiang University – where I learned fundamental AI concepts. I then pursued my Master’s degree under Professor Chen Dezhao, focusing specifically on artificial neural network research, which resulted in four high-quality publications in SCI and EI journals.

Leveraging this AI expertise, I designed an artificial intelligence-based data recovery algorithm that could adapt to different corruption scenarios and optimize recovery rates dynamically. Rather than using fixed recovery patterns, this AI system could analyze the specific damage characteristics and determine the most effective recovery approach for each unique situation.

I first implemented this algorithm in an early product Advanced Outlook Express Repair, where it achieved the industry’s best data recovery rate. The success was so significant that I made it a core component of all our subsequent product development. This AI-driven approach has become our competitive differentiator – it’s why our data recovery products consistently maintain the highest recovery rates in their respective categories. The algorithm essentially uses artificial intelligence to analyze each corruption pattern it encounters, making our tools more intelligent and effective over time.

You’ve mentioned using AI models to stay updated on industry trends. Can you share a specific instance where this approach led to a significant improvement or innovation in your products?

A perfect example of this is our flagship product, DataNumen SQL Recovery, which demonstrates how our AI-driven approach has kept us ahead of industry trends and significantly outperformed the competition. When we were developing DataNumen SQL Recovery, the industry standard for SQL Server database recovery was still largely based on traditional, rule-based algorithms. While these methods worked for minor corruption scenarios, they struggled with complex and severe damage patterns that are increasingly common in modern database environments.

By staying current with AI developments and recognizing the potential for machine learning in data recovery, we implemented our artificial intelligence-based data recovery technology specifically for corrupted SQL Server databases. This wasn’t just a minor enhancement—it represented a fundamental shift in how we approach database recovery. The results were remarkable. DataNumen SQL Recovery achieved recovery rates that are 1.5 to 10 times higher than comparable products in the market. This dramatic improvement wasn’t just incremental progress—it was a quantum leap that essentially redefined what was possible in SQL Server database recovery.

This success with DataNumen SQL Recovery validated our broader strategy of integrating AI across our entire product line. It showed that staying ahead of technological trends—specifically the evolution of AI and machine learning—could translate directly into measurable, dramatic improvements in product performance that customers could immediately recognize and value.

DataNumen works with Fortune 500 clients. How do you balance meeting the needs of large corporations while still creating products accessible to individual users?

That’s an excellent question, and the answer actually highlights something fascinating about data recovery—when facing data disasters, Fortune 500 companies and individual users have exactly the same fundamental need: to recover as much data as possible. Both want to see our product’s recovery effectiveness before making a purchase decision.

This shared core requirement has shaped our entire business model. We develop trial versions for every single product, allowing users to repair their corrupted files and see the actual recovery results before buying the full version. Whether you’re a Fortune 500 CTO or someone who lost family photos, you want proof showing that our solution works for your specific situation. The main difference lies in the evaluation process and scale. Individual users typically see the trial results and purchase the full version immediately—it’s a straightforward, fast decision cycle.

Fortune 500 companies, however, operate at a completely different scale. Before deploying our products across their various subsidiaries and departments, they usually contact us directly to coordinate comprehensive evaluations. They’ll test our trial versions across multiple subsidiaries and different use cases. Sometimes they even request full-featured versions for more extensive evaluation periods that can last several months.

But here’s what I find remarkable—despite the vastly different organizational complexity and procurement processes, the fundamental value proposition remains identical. A corrupted SQL Server database is just as critical whether it belongs to a multinational corporation or a small business. Our AI-based recovery algorithms don’t distinguish between Fortune 500 data and individual user data—they simply focus on maximizing recovery rates. This universality of need has actually simplified our product development strategy. We build one excellent solution that scales from individual use to enterprise deployment.

You’ve expressed excitement about AI-driven predictive storage failure technology. Based on your extensive experience in data recovery, what potential pitfalls or challenges do you foresee in implementing this technology widely?

That’s a great question. With over two decades in the data recovery industry, I’ve seen firsthand both the promise and limitations of technology solutions. While AI-driven predictive storage failure technology is incredibly exciting, I foresee several significant challenges based on my experience with complex data systems.

First, the accuracy challenge. In data recovery, we deal with the aftermath of storage failures daily, and I’ve learned that storage degradation patterns can be incredibly subtle and varied. An AI system needs to distinguish between normal wear patterns and genuine failure indicators. False positives could lead to unnecessary hardware replacements and costs, while false negatives could result in catastrophic data loss – exactly what the technology is meant to prevent.

Second, there’s the implementation complexity. From my work reverse-engineering file formats and developing recovery algorithms, I know how intricate storage systems can be. Each manufacturer has different failure signatures, and integrating predictive AI across diverse hardware environments – especially in Fortune 500 companies with legacy systems – will be enormously challenging.

Third, I’m concerned about over-reliance. Having worked with thousands of data loss cases, I’ve seen how people can become complacent when they trust technology too much. Predictive technology might give users a false sense of security, potentially leading them to neglect proper backup strategies. The best prediction system in the world can’t prevent sudden catastrophic failures like power surges or physical damage.

Finally, there’s the data privacy aspect. Predictive systems need access to storage usage patterns and system telemetry, which raises questions about what data is being collected and how it’s protected. The technology has tremendous potential, but it should complement, not replace, robust backup and recovery strategies.

Can you walk us through a real-world scenario where your data recovery software made a crucial difference for a client? What lessons did you learn from this experience?

Absolutely. I’ll share a case that really crystallized for me how critical timing is in data recovery situations. A professional CAD company contacted us in what could only be described as a panic situation. They had completed a major design project and were preparing to send the CAD files to their client when disaster struck – Outlook suddenly wouldn’t open. Their PST file had become corrupted, and they couldn’t access any emails or contact information. This wasn’t just an inconvenience – they were facing a tight deadline and potentially losing a contract worth hundreds of thousands of dollars. Time was absolutely critical. They found us through the Internet and immediately downloaded DataNumen Outlook Repair. Within hours, they had recovered virtually all of their emails and contact information. Most importantly, they were able to deliver the CAD files to their client before the deadline, saving that substantial contract.

This experience taught me invaluable lessons about the psychology of data disasters. When clients face data loss, they’re not just dealing with a technical problem – they’re experiencing genuine anxiety and urgent pressure. Every minute counts. This realization led us to completely redesign our customer experience around speed and immediacy:

First, we eliminated all friction from our trial downloads. Users can instantly download trial versions from our website without filling out forms or waiting for manual approval.

Second, our trial versions allow users to repair their files and see results quickly, giving them confidence in the solution before purchasing.

Third, we streamlined the purchase process so satisfied customers can buy the full version instantly and typically receive it within minutes – not hours or days.

Finally, we developed an AI chatbot trained on our data recovery expertise and product knowledge base that can answer customer questions 24/7, because data disasters don’t wait for business hours.

That CAD company case taught us that we’re not just selling software – we’re providing peace of mind under pressure.

As someone who’s witnessed the evolution of data storage and recovery, what advice would you give to young entrepreneurs looking to innovate in this space?

While data recovery technology has been evolving for many years, it’s far from obsolete. As long as there’s data, there will be data disasters, and consequently, there will always be a need for data recovery solutions. The most promising direction for innovation right now is the comprehensive integration of AI technology into data recovery.

This represents a massive opportunity for young entrepreneurs who understand both AI and the complexities of data systems. Let me give you a specific example of where innovation is desperately needed. Currently, most raw-level data recovery relies on file-carving techniques combined with file system metadata, using rule-based methods to mechanically recover data. While this works for straightforward cases, it performs poorly in complex scenarios – like when a hard drive has been repeatedly formatted and had different file systems installed on it in the past.

If young entrepreneurs could develop AI systems that comprehensively analyze data disaster cases rather than relying on rigid rules, the recovery effectiveness would be dramatically superior to current methods. The AI could learn to recognize patterns and relationships that rule-based systems simply can’t detect. However, there’s a significant technical challenge that represents both an obstacle and an opportunity: computational power. Most data disaster cases involve enormous amounts of data – from several gigabytes to hundreds of terabytes.

Current AI models running on traditional computer systems simply don’t have the computational capacity to process such massive datasets effectively. This leads to what I see as the ultimate frontier: combining quantum computing with AI. If entrepreneurs can successfully merge these technologies, they could solve the computational bottleneck that currently limits AI-driven data recovery, achieving truly maximized data recovery rates. The entrepreneur who cracks this quantum-AI combination will revolutionize our entire industry.

Looking ahead, how do you see the role of data recovery changing in the next decade, and how is DataNumen preparing for these shifts?

Looking ahead to the next decade, I see two fundamental shifts that will reshape our entire industry, and we’re already positioning DataNumen to lead these transformations. First, we’re moving from the relatively simple world of single-PC data recovery to a complex ecosystem encompassing smartphone data recovery, distributed cloud-based data recovery, and virtual machine data recovery.

Each of these environments presents unique technical challenges that require completely different approaches. We’ve been aggressively investing in R&D to stay ahead of this trend. For example, our DataNumen Data Recovery now supports smartphone data recovery. Similarly, we’ve enhanced both DataNumen Outlook Repair and DataNumen SQL Recovery to fully support virtual machine environments, which are becoming the backbone of modern enterprise infrastructure.

The second major shift is philosophical—moving from purely reactive to proactive data protection. The traditional model of waiting for disasters to strike and then attempting recovery is giving way to a comprehensive approach that combines proactive data protection with reactive recovery capabilities. This creates a more robust shield around digital assets. This evolution has fundamentally transformed DataNumen’s identity. We’re not just a data recovery software company, but a comprehensive data protection provider. We now offer data backup solutions, business continuity plans, and enterprise disaster recovery plans as integrated services.

This transformation isn’t just about expanding our product line; it’s about reimagining our role in our clients’ digital ecosystems. Instead of being the emergency responders who arrive after disaster strikes, we’re becoming the trusted advisors who help prevent disasters and ensure seamless recovery when the unexpected does happen. The companies that adapt to these shifts will thrive; those that don’t will fail.

Thanks for sharing your knowledge and expertise. Is there anything else you’d like to add?

Thank you for this opportunity to share our journey and vision. I want to conclude this interview with one key message: “Recover your data. Recover your life!”

In today’s digital age, data has become inseparable from our lives. Your family photos, business documents, creative work, financial records, communication history – these aren’t just files on a storage device. They’re the digital fabric of your personal and professional identity.

When someone loses years of family photos, or a business faces the potential loss of critical client data, or a researcher loses months of work – we’re not just talking about recovering bits and bytes, but recovering memories, livelihoods, relationships, and futures. That’s why our work goes far beyond technical algorithms and software development.

Every corrupted file we encounter represents someone’s piece of life that needs to be restored. Whether it’s helping that CAD company meet their deadline, or enabling a family to recover precious memories, or allowing a Fortune 500 company to maintain business continuity – we’re in the business of getting back people’s digital lives.

In today’s interconnected world, your data protection strategy isn’t just an IT decision – it’s a life decision. Only by better protecting and recovering your data can you ensure your personal and professional success remains secure and resilient. The future belongs to those who understand that in our digital age, taking care of your data means taking care of your life.