I solve complex unit economic problems with technical sovereignty. Below is the documented proof of how I've reshaped Newfold Digital's core product lines using data as my primary lens.
$2.1M+
Annual OPEX Cut
$3.0M
Monthly License Recovery
28%
Sign-up Lift
It wasn’t just that our support costs were high; it was the realization that we were fighting a losing battle. When I looked at the unit economics, the math was brutal: we were spending $6.00 every time a customer reached out, which in some cases wiped out the entire profit margin for that user's monthly plan. But the human side was worse. Our "Time-to-First-Response" was creeping past four hours. Customers weren't just leaving because of technical issues; they were leaving because they felt ignored. We were essentially paying millions of dollars to provide a slow experience that frustrated both our agents and our customers.
I realized that another "chatbot" wouldn't solve this—people hate being told to read an FAQ. We needed a "Technical Agent," not a "Chat Agent." I decided to architect an Agentic RAG system, but the real "secret sauce" was integrating the Model Context Protocol (MCP). This allowed the AI to actually do things—like resetting a server permission or restarting a service—rather than just talking about it. The goal was to build a system that had the "brain" of a senior support tech but the "hands" to execute commands directly on the server, eliminating the hallucination problem by grounding every action in our actual technical documentation.
The shift was night and day. By dropping the cost per contact to $0.15, we saved $175,000 every month, but the real win was the "Trust Recovery." Imagine a customer whose site goes down at 3 AM; instead of waiting until 9 AM for a human to wake up and click a button, the AI fixed it in seconds. We saw a 15% drop in churn specifically because we removed the friction of waiting. Our human agents were also finally freed from "resetting passwords" all day, allowing them to focus on the truly complex architectural problems they were hired to solve.
Bubble size represents ticket volume. AI shift shows radical compression of cost and response time.
Total Efficiency Gain
$2.1 Million
We were essentially tenants in our own house. Every month, we were writing a $3M check to external vendors for the control panels our customers used. This "Vendor Tax" was eating 12% of our margin, but the financial cost wasn't even the biggest problem—it was the lack of sovereignty. If we wanted to ship a new security feature or a better backup UI, we couldn't. We were stuck on the vendor's timeline. We were a massive company that had lost the ability to innovate because we didn't own the "front door" to our own product.
I defined the "DESTINY" roadmap with one goal: ownership. This wasn't just about building a new UI; it was about building a proprietary ecosystem. I pushed the team to focus on a "Modular Migration." We knew we couldn't move millions of customers overnight without a disaster, so we built the new panel to be lean and horizontally scalable. We prioritized the features that would allow us to cross-sell our own services (like SSLs and Backups) directly, something the third-party vendors made intentionally difficult.
The result was financial and creative freedom. We are on track to recover $36M in annualized margin, which gives us the "pricing destiny" to offer better hardware to our users without raising their bills. For the engineering team, it changed the culture. They went from "configuring someone else's software" to "building the future of the company." We moved from being a reseller of tools to being a true technology platform.
Recovered Monthly Margin
$3.0M
Platform Ownership
100%
Backups are the ultimate "silent" feature—no one cares about them until everything goes wrong. When I audited our logs, I found a terrifying inconsistency: our success rates varied wildly depending on which server brand a customer was on. Our "Mean Time to Recovery" was three times slower than the industry average. If a small business owner lost their data, it could take us days to get them back online. That’s not just a technical lag; that’s a potential business failure for our customer. We were failing at our most basic promise: keeping data safe.
I decided we had to stop relying on "black box" vendor solutions that we couldn't see inside of. I drove the development of our own Central Backup System (CBS). We bet on "Distributed Parallel Processing"—essentially breaking a huge backup into tiny pieces and processing them all at once. I gave the team a clear mandate: "Recover-First Architecture." The system was designed so that even if the network was slammed, the path to restoring a site would always be the fastest lane.
We hit a 99.9% success rate, but the real metric was the 58% reduction in recovery time. When a site broke, we could now bring it back 2.4x faster than before. This led to a 70% drop in panicked support tickets. The human outcome was "Peace of Mind"—both for the customer, who knew their livelihood was safe, and for our engineers, who no longer had to spend their weekends manually stitching together corrupted files.
RECOVERY TIME
-58%
RELIABILITY
99.9%
Our P&L was leaking money in a way that felt unfair. We had a "one size fits all" approach where a tiny group of power users—about 12%—were using 60% of our server resources. These users were essentially being subsidized by the "mom and pop" shops who barely used any data. This created a "Negative Unit Margin" for our best servers. Meanwhile, new customers were overwhelmed by our complicated plans and were dropping out of the sign-up funnel because they didn't understand what they were buying.
I moved us to a "Value-Based Tiering" strategy. I realized we needed to stop selling "storage" and start selling "performance." We split the product: a "Standard" tier that was cheap and simple for hobbyists, and a "Performance" tier that was resource-gated for pros. This allowed us to lower the entry price to attract more people while ensuring that the high-traffic users were moved to a plan that actually covered the cost of the hardware they were exhausting.
The clarity of the new plans led to an immediate 28% jump in sign-ups—turns out, when you make things easy to understand, people buy more. By moving the "heavy" users to the performance tier, we recovered 18% of our gross margin that was previously just "leaking" away. We ended up with a healthier business where every customer was on a plan that actually made sense for their needs, and our LTV (Lifetime Value) for professional users more than doubled.
Gross Margin Delta
+18%
Entry Conversion
+28%