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Strategic Communications Advisory For Visionary Founders
Actionable
Takeaways
Speed Over Perfection in Early Stages
Elad emphasizes optimizing for speed when building a new company. By focusing on rapid execution, Synthpop was able to get its first paying customer before taking investor money. This approach allowed them to prove value quickly and align their priorities around what was important for growth. Founders should focus on getting early customer traction before scaling too quickly.
Leverage Vertical-Specific Insights for GTM Success
Synthpop's focus on specific healthcare verticals, such as durable medical equipment and diagnostic testing, allowed them to target less saturated markets that are more open to innovation. For B2B founders, narrowing focus to high-opportunity niches can help accelerate adoption and make the GTM process more effective.
Position as a Labor Solution, Not Just Software
Instead of positioning Synthpop as a SaaS tool, Elad and his team framed their offering as a labor-saving solution. By focusing on how their AI agents perform tasks typically done by employees, they created a unique value proposition that made it easier for customers to adopt their product. Founders should think about positioning their product in terms that solve their customers' immediate operational pain points.
Pre-sell and Validate Before Fundraising
Before taking investment, Elad validated his idea by securing commitments from paying customers. This not only reduced the risk for investors but also ensured they were building something with real demand. Early-stage founders can learn from this approach by ensuring there's tangible market demand before fundraising or scaling operations.
AI is a Tool, Not the Story
Elad sees AI as a means to an end, not the end itself. He predicts that in five years, the term “AI” will no longer be a selling point; instead, the focus will be on the intelligence and efficiency it enables. For founders, this means emphasizing outcomes and value over the technology itself when crafting messaging and positioning.
Conversation
Highlights
How Synthpop Built AI Agents That Resolve 93% of Customer Support Tickets Autonomously
In a recent episode of Category Visionaries, Elad Ferber, CEO of Synthpop, shared how his company is pioneering a fundamentally different approach to customer support automation. Unlike traditional chatbots that simply deflect tickets, Synthpop’s AI agents actually resolve customer issues end-to-end—and they’re doing it at scale.
The Problem with Traditional Support Automation
Most companies attempting to automate customer support hit the same wall. They deploy chatbots that can answer simple questions, but the moment complexity enters the picture, these systems fail spectacularly. Elad identified the core issue: “The vast majority of agents out there, they don’t have any access to your back end systems. They don’t have any access to your database. They’re just LLMs that are trained on text, and they’re trying to provide good answers based on that text.”
This limitation means traditional chatbots can only handle straightforward FAQs. When a customer needs their subscription upgraded, a refund processed, or account information updated, the bot hands off to a human agent. The result? Companies automate maybe 20-30% of their support volume while still paying for the infrastructure and facing customer frustration.
Synthpop took a radically different path. Instead of building another chatbot layer, they built AI agents that can actually execute actions across a company’s entire tech stack.
Building Agents That Actually Do Things
The breakthrough came from rethinking what an AI agent should be capable of. Elad explains the architecture: “We give agents access to all the tools that your support agents have access to. So that means access to Stripe, access to your database, access to your own internal APIs, to Salesforce, to your CRM.”
This isn’t just about reading data—it’s about taking action. When a customer asks for a refund, Synthpop’s agent doesn’t just acknowledge the request. It verifies the customer’s identity, checks the refund policy, processes the refund through Stripe, updates the CRM, and confirms completion with the customer. All without human intervention.
The technical implementation requires solving several hard problems simultaneously. The agents need to understand natural language requests, map those requests to specific actions across multiple systems, handle authentication and permissions correctly, and manage complex multi-step workflows. Elad’s team spent years building the infrastructure to make this possible.
The 93% Resolution Rate
Synthpop’s agents achieve something remarkable: they fully resolve 93% of customer interactions autonomously. This isn’t ticket deflection or partial automation—these are complete resolutions where the customer’s problem is entirely solved without any human agent involvement.
The remaining 7% represents genuinely complex cases that require human judgment. As Elad notes, “There’s always going to be the super long tail of one off edge cases that require human intervention.” But by handling the vast majority autonomously, Synthpop’s agents fundamentally change the economics of customer support.
The GTM Strategy: Targeting High-Volume Support Teams
Synthpop’s go-to-market approach focuses on companies with specific characteristics. Their ideal customers are B2C or B2B2C companies with high support volumes—think e-commerce, fintech, SaaS platforms serving end consumers. These companies typically handle thousands or tens of thousands of support tickets monthly.
The sales process involves a detailed discovery phase where Synthpop analyzes a prospect’s support ticket history. Elad describes the approach: “We actually go through historical support tickets with customers and kind of go tag by tag and kind of map out, okay, how much of your support volume can we actually automate?”
This data-driven analysis gives prospects concrete projections of automation rates and cost savings before they commit. It also helps Synthpop identify which integration work will deliver the highest ROI, allowing them to prioritize development accordingly.
The Integration Challenge
Every customer deployment requires custom integration work. Synthpop needs to connect to each company’s specific tech stack—their payment processor, database, CRM, internal APIs, and proprietary systems. This presents both a challenge and a competitive moat.
Elad acknowledges the complexity: “Every company’s different and has a different tech stack, different tools.” But this customization requirement also makes Synthpop incredibly sticky once deployed. After investing in the integration work and training the agents on company-specific policies and workflows, switching costs become prohibitive.
The team has built reusable components for common integrations—Stripe, Salesforce, major e-commerce platforms—which accelerates deployment for new customers. But there’s always custom work required to handle each company’s unique business logic and edge cases.
Lessons on Pricing and Positioning
Synthpop’s pricing model evolved through experimentation. They charge per resolution rather than per seat or per ticket volume. This aligns incentives: customers only pay when the AI agent successfully resolves an issue.
Elad shared a key insight about pricing psychology in the AI agent space: “I think a lot of companies are still hesitant to pay a lot for AI agents because AI is so new.” Rather than trying to capture the full value created immediately, Synthpop prices to accelerate adoption, knowing they can expand revenue as customers see results.
The positioning has also sharpened over time. Early on, Synthpop described themselves as an “AI agent platform.” Now they lead with the outcome: autonomous customer support that actually resolves issues. This shift from technology-first to outcome-first messaging has improved conversion rates significantly.
The Vision for Autonomous Operations
Looking ahead, Elad sees customer support as just the beginning. “Customer support is a great wedge because it’s like one of the most standardized and routine business processes,” he explains. But the same architectural approach—giving AI agents tool access and the ability to execute actions—can extend to sales, operations, back-office functions, and more.
The key insight is that most business processes are more routine and automatable than people assume. They just require agents that can actually interact with systems rather than merely conversing with humans. As Elad’s team proves out this model in customer support, they’re building toward a future where AI agents handle entire categories of business operations autonomously.
For founders building in the AI agent space, Synthpop’s journey offers a critical lesson: the real value isn’t in building better conversational interfaces. It’s in building agents that can actually execute actions across a company’s full tech stack. That’s where automation becomes transformation.
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