Small Biz Leader · January 29, 2026
This interview is with Talia Mashiach, CEO, Founder and Product Architect, Eved.
Interview
Interview with Talia Mashiach, CEO, Founder and Product Architect, Eved
Small Biz Leader · January 29, 2026
Small Biz Leader · January 29, 2026
Small Biz Leader · January 29, 2026
This interview is with Talia Mashiach, CEO, Founder and Product Architect, Eved.
This interview is with Talia Mashiach, CEO, Founder and Product Architect, Eved.
For a long time, I was operating reactively, solving problems as they came up, putting out fires, and keeping things moving day to day. The real turning point came when I learned how to step out of that cycle and start leading proactively.
That shift started with setting clear, measurable goals before the year began, not just broad ambitions, but specific metrics we could track month by month. It forced us to focus on executing against a plan rather than reacting to the latest challenge.
The second inflection point was when I built the right leadership team and gave them a clear playbook. Once the right people were in the right seats, with ownership and structure, I could finally step into the role of CEO, thinking ahead, setting a vision, and ensuring the team had what they needed to win.
It changed everything. Instead of managing every detail, I started managing direction, and that’s when Eved began to truly scale.
I realized pretty early on that if I was going to grow a company, I had to truly understand the numbers myself. It’s something a lot of entrepreneurs struggle with; we’re naturally drawn to building, creating, or selling, but not necessarily to the financial side. It’s easy to assume your accountant or finance partner has it covered.
But the truth is, you can’t be an effective CEO if you don’t understand how to read your own numbers. Once I pushed through that learning curve and made it a regular practice, the numbers started to tell me the story of the business: what was working, what wasn’t, and where I needed to adjust.
Over time, it became second nature. Every week, I review a focused dashboard of key metrics—not everything, just the ones that actually drive performance. That habit changed how I lead. Instead of reacting to issues after the fact, I can see early signals and make smarter, faster decisions.
For me, numbers aren’t just financials anymore; they’re the narrative of how the company is performing and the levers we can pull to shape its future.
I’ve learned that it’s easy for entrepreneurs to get excited about new ideas. Sometimes, we convince ourselves that something feels right without grounding it in data or strategy. So, before green-lighting anything, I start with alignment: does this opportunity support our core goals as a business, and does it fit within our priorities for the current year?
Then, we measure potential impact. We assign an “impact score,” essentially asking: what’s the expected ROI, and is it worth the effort and resources required to get there?
If something scores high on alignment and impact, and we can clearly define how success will be measured, that’s when it earns the green light. Otherwise, even great ideas go on the parking lot list until the timing or conditions are right.
For me, discipline in saying “no” is as important as the excitement of saying “yes.” It’s how we stay focused on building sustainably, not just experimenting endlessly.
The key for us has been shifting the mindset from “AI as a tool” to “AI as an operating system.” I don’t want my team just using AI; I want them designing with it.
To make that real, we built an internal AI framework that trains every leader to map their workflows as systems, identifying where decisions, data, or approvals can be automated, and where human judgment adds the most value. Each function has its own “AI playbook” that documents how automation supports strategy, not just tasks.
That structure has changed how my team thinks. Instead of asking, “What tool should we use?” they now ask, “How do we design this process so it never needs to be done manually again?”
By embedding that thinking into every department, from finance to operations to client experience, we’ve built a culture where AI isn’t a project; it’s part of how we lead. And that’s what enables scale.
Today, our biggest transformation with AI has been on the marketing and sales side.
On the marketing side, our AI agents have allowed us to generate nearly 10 times the amount of content we produced before implementing AI, across campaigns, thought leadership, and client education. Each piece still goes through human review, but the ideation, first-draft creation, and channel optimization are fully automated. The KPI for that AI workflow is clear: consistent volume and quality that drives brand awareness and lead flow without adding headcount.
On the sales side, we’re using AI to reduce the amount of time it takes for each rep to move a deal through the funnel, which allows us to raise individual sales targets by about 20% without increasing burnout. The AI supports reps with automated research, follow-up drafting, and deal tracking, freeing them up to focus on relationships and strategy.
Where we’re headed next, and what we’re actively building, is an autonomous sales agent that will manage defined SQL goals, run performance analytics, and trigger escalations when lead quality or conversion velocity drops below thresholds. That’s the future state: an intelligent, closed-loop system where AI not only supports but actively manages growth workflows.
We’re not fully there yet, but every step we take toward it has already made us faster, leaner, and more focused on what humans do best: creativity, connection, and judgment.
For us, the key to fast but safe experimentation is knowing what kind of risk we’re taking and how easily we can reverse it.
If a test can be undone quickly, we move fast and take bigger swings. That’s where we innovate aggressively—things like messaging, campaign creative, or process automation. The cost of failure is low, and the learning is immediate.
However, if a change could impact our customers or cash flow, we slow down. Those experiments go through a much more thorough review; we model outcomes, define clear success metrics, and make sure we can track impact before rolling anything out broadly.
It’s really about calibrating the level of risk to the level of reversibility. That mindset keeps us innovating constantly, but always with the discipline to protect our customers, our brand, and our balance sheet.
It’s one of the hardest things to do: breaking into an entrenched industry with something new. The biggest lesson for me was realizing that even though you’re selling to a company, you’re really selling to a person.
You have to find that rare individual inside a large organization who’s willing to take a personal risk—someone bold enough to champion innovation in a culture that often rewards playing it safe. Those people are like needles in a haystack, so the first step is finding companies that allow for that kind of thinker to exist.
Once we found those early champions, we didn’t approach them like customers; we treated them like partners. We said, “Let’s build this together.” We adapted to their systems and processes, co-created features around their needs, and focused on helping them succeed internally.
That partnership mindset built trust. When they started to see results, they became our strongest advocates—the ones who brought us into other divisions and helped Eved scale across the enterprise.
You can’t expect to make a lot of money from those first few deals; your return is in credibility. But if you deliver, that trust becomes the foundation for everything that follows.
The first thing I would do is make sure I deeply understand the financials, not just the top-line numbers, but where money is truly being made or lost. You can’t professionalize operations until you know your financial story. So I’d start by consolidating all the data, analyzing performance across locations, and identifying the key drivers of profitability.
Once you have that clarity, the next step is building a repeatable operating model, something that allows each location to perform consistently and efficiently. When I built my last company, one of the best pieces of advice I received was to think like a franchise even before we were one. We created what we called EvedU, a “university” of standardized protocols, training, and systems that defined exactly how each location should run.
The goal was simple: to make every customer experience identical in quality and consistency. If you can understand your financial levers and systematize your customer experience, you create the foundation to scale, not just grow.
Even if you’re not building your company to become a franchise, it’s smart to think like one. That mindset forces discipline to document your processes, create repeatable systems, and make sure success isn’t dependent on any one person’s knowledge. It’s the foundation for scale.
And today, with the power of AI, that’s easier than ever. You can literally take the expertise that lives in your head, your playbooks, your decisions, your best practices, and use AI to help turn that knowledge into structured, repeatable operating systems.
That’s how you move from working in the business to building a business that runs beyond you.