Why we started Fask

I spent over 12 years at Amazon, eventually becoming a Principal Engineer leading mission-critical payment systems — processing over $800 billion annually across all of Amazon's businesses. These were the systems that powered the movement of money to deliver goods and services to customers worldwide.

But what I remember most clearly? We were constantly firefighting.

We had 2,400+ high-severity tickets a year. Engineers were being woken up every night. Refund issues, double charges, payment processors glitching at scale. Data was siloed across dozens of systems, and getting a single customer view required stitching together fragments from multiple services. It felt like we were duct-taping a rocket ship mid-flight.

The engineers were some of the brightest people I've worked with. But instead of solving high-leverage problems, we were chasing log files, debugging repetitive operational issues, and answering the same customer queries over and over.

After Amazon, I spent two years building an AI startup. That experience taught me what's actually possible with modern AI — and what's still missing from the tools businesses use every day.

Meeting George — The Same Problem, Different Angle

My co-founder George Koshy spent years as an SDE and engineering manager at Amazon and Coinbase. At Amazon, he worked in payments and fintech — the same world I lived in. At Coinbase, he led RevOps engineering, building the systems that powered customer-facing operations at scale.

His frustration matched mine: "We had thousands of tickets pouring in, and the tools to handle them were fragmented, slow, and dumb. Customers were waiting hours or days for responses that should have taken seconds. The data was there — it was just trapped in silos."

George had seen it from both the engineering and revenue operations side — customer experience suffering because the tools that were supposed to help were too disconnected, too manual, and too slow.

When we started talking, we realized we were looking at the same problem from two complementary angles. I saw it from the infrastructure and payments side — smart people drowning in repetitive tasks and data silos generating thousands of tickets. George saw it from the RevOps and customer-facing side — experienced teams held back by tools that couldn't keep up.

The conclusion was the same: businesses need intelligent agents that can communicate with customers instantly, across every channel, without humans in the loop.

Why Existing Tools Fall Short

We ran dozens of conversations with decision-makers across our networks.

Their pain points were consistent and loud:

• "Our customers wait hours for a response to simple questions."
• "We're using five different tools for phone, email, SMS, and forms — and none of them talk to each other."
• "I need agents that can actually do things — qualify leads, send quotes, onboard customers — not just answer FAQs."
• "Every new tool we add requires weeks of integration work and custom workflows that break."

They weren't asking for "AI." They were asking for outcomes — faster response times, fewer tools, less manual work, and agents that actually get things done.

The tools they had — Quo, OpenPhone, legacy IVRs, clunky ticketing systems — were built for a world where humans handle every interaction. That world is over.

What Makes Fask Different

We didn't build another chatbot or another workflow builder.

We built a 1-click AI agent platform — where AI agents communicate with your customers across phone, SMS, email, and web forms. No workflows to build. No drag-and-drop. Just tell your agents what to do in plain English.

Here's what that looks like:

• Every channel: Agents handle phone calls, SMS conversations, email threads, and form submissions — all from one platform.
• Agentic tasks: Agents don't just respond — they qualify leads, send quotes, onboard customers, update CRMs, and escalate when needed.
• Swarm architecture: Multiple agents collaborate on complex tasks. One qualifies the lead, another sends the quote, another updates the CRM — all autonomously.
• 1,000s of integrations: Connect your CRM, ERP, and tools via OAuth. Agents work across your entire stack, zero config.
• Multi-tenant platform: Serve multiple clients from one platform. Each tenant gets isolated, secure agent access.
• Enterprise security: OAuth-based auth, multi-tenant isolation, cloud-native infrastructure. Your data stays yours.

My engineering background — building systems at Amazon-scale — means we can compete on the technical depth of platforms like OpenClaw. George's RevOps expertise and his firsthand experience with the pain of fragmented customer communication means we're building something that teams will actually love to use.

The Future We're Building

We believe the era of manually handling customer communication across disconnected tools is ending. AI agents should talk to your customers on every channel, handle the work, and keep your systems in sync — while your team focuses on relationships, strategy, and the work only humans can do.

We're not adding AI to old tools. We're replacing the old paradigm entirely.

And this is just the beginning.

If you're tired of juggling five tools to talk to your customers — let's talk. We're building the AI agents that will handle your customer communication, 24/7, across every channel.