Supportiyo, co-founded by Ashar Ahmad, is an applied AI startup creating a digital workforce specifically for home service businesses. While most AI tools cater to enterprises or technical users, Supportiyo bridges the gap for small businesses that want outcomes, not complex tools.
Supportiyo is essentially a vertical AI phone agent for home service businesses. It answers calls instantly, understands trade-specific language, handles customer objections, and books jobs directly into company calendars — solving one of the biggest revenue leaks in the trades: missed calls. Ahmad, an AI engineer, partnered with trades business owner Ahmad M.S. to create a solution born from real operational pain points.
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In an exclusive interview, co-founder and CEO Ashar Ahmad explains how Supportiyo is revolutionizing operations for small businesses through applied AI.
The American Bazaar: For those new to Supportiyo, how would you describe the company’s mission and core purpose?
Ashar Ahmad: Supportiyo is an applied AI company building a digital workforce for home service businesses.
Today, most advanced AI and automation tools are built for enterprises, engineers, or power users. Small business owners don’t want tools, workflows, or configuration platforms. They want work to get done.
The purpose of Supportiyo is to take existing AI capabilities and turn them into autonomous AI workers that take ownership of real business functions. These aren’t tools that merely assist people. they’re systems designed to actively perform work inside a business.
We identify core workflows in home service businesses and create AI workers that can handle those responsibilities end to end. The result is real ROI without forcing business owners to learn new software or change their operations.
What inspired you to build Supportiyo? What gap in the market were you trying to fill?
Supportiyo started with a very specific problem: missed calls.
As a builder and AI engineer, I saw how much capability already existed and how poorly it translated into real outcomes for small businesses. When Ahmad, who was running a home service business at the time, became our first customer, the problem became very concrete. His business was losing revenue simply because calls were missed while technicians were in the field.
As we looked deeper, it became clear that home services were the most underserved sector. Hospitality, banking, education, and corporate environments already had solutions. Home services did not.
The gap wasn’t just voice. It was the absence of systems that actually help owners run their businesses. Supportiyo exists to close the gap between modern technology and practical execution.
What makes Supportiyo uniquely suited to trades businesses compared to generic call-handling solutions?
Supportiyo is built from a combination of deep technical capability and real domain expertise.
I come from a hacking and AI engineering background, focused on building systems that work reliably in production. Ahmad joined as a cofounder after being our first customer, bringing firsthand insight from running a trades business.
Most platforms give businesses ingredients. Tools, workflows, prompts, and integrations that owners are expected to assemble themselves. That approach assumes technical time and skill most owners do not have.
We take a different approach. Supportiyo provides prebuilt, industry-specific AI workers that already understand trade language, objections, scheduling logic, and operational edge cases. Instead of giving businesses a kitchen, we give them a trained team member.
That’s the difference between automation and an AI workforce.
What’s been the feedback from early adopters or pilot users?
Feedback consistently centers around relief and trust.
An HVAC business owner with a small team shared that handling calls while working in the field was one of his biggest challenges. After deploying Supportiyo, every customer is attended to and scheduled promptly, and he only steps in when needed.
A local food business told us that language had previously been a barrier. Supportiyo learned their full menu and preferences and now handles customer conversations smoothly, allowing the team to focus on their core work.
Another service business owner told us Supportiyo now handles close to 80% of inbound calls, giving him more time and space to focus on growth.
Owners often describe Supportiyo not as software, but as an extra worker they can rely on.
How does the AI handle objections or nuanced customer queries, and what sets its conversational ability apart?
The AI operates with full business context rather than scripts or hardcoded prompts.
Each AI worker understands the specific business it represents, including services, pricing logic, availability, and policies. When customers raise objections or ask nuanced questions, the AI responds based on real business rules and past outcomes.
What sets it apart is accountability. The AI is designed to resolve intent correctly, not just hold a conversation. Whether that means booking a job, qualifying a lead, or escalating to a human, the system owns the outcome.
This is the difference between a chatbot and a worker.
What challenges have you faced building Supportiyo, and how have you overcome them?
One of the biggest challenges has been our audience.
We are working in one of the most advanced fields today, artificial intelligence, but building it for a sector that is not traditionally software driven. That means education comes before selling. We first have to explain what AI can realistically do, what it replaces, and what outcomes owners should expect.
Another challenge is trust. AI as a category has been hurt by flashy products that fail in real operations. We address this by focusing on reliability, narrow responsibilities, and tight feedback loops with customers.
Trust is built when AI consistently works and delivers real outcomes, not through polished demos or marketing promises.
Can you walk us through a typical customer journey from missed call to booked job?
Early on, onboarding was very hands on. My cofounder Ahmad and I worked directly with customers to understand their workflows and configure the AI workers accordingly.
Today, onboarding is fast and simple. A customer creates an account, selects their industry, connects their website, and activates an AI worker. Within minutes, calls are being handled.
For customers who want guidance, assisted onboarding allows them to go live in under ten minutes.
The core principle is that the AI adapts to the business. The business does not adapt to the AI.
What is your long-term vision for Supportiyo? Where do you see the company in five years?
In five years, I see Supportiyo becoming the default AI workforce for home service businesses.
Platforms like Jobber and ServiceTitan helped move the industry from paper to software. Supportiyo moves it from software to autonomous AI workers.
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The goal is not to replace people, but to remove operational burden so humans can focus on judgment, relationships, and growth.
Home services are just the beginning. The mission stays the same as we expand: applied AI that takes responsibility for real work and delivers measurable impact.