Hitting a 7-figure ARR within a year by building the first AI-native option in a crowded market

Madhu Nadig decided to build a solution to an issue he saw in one of the most difficult markets: financial compliance. And he pulled it off in a big way by being the first AI-native option.

In fact, Flagright hit a 7-figure ARR less than a year after launch.

Here's Madhu on how he did it. 👇

A fortuitous flagship customer

While working as a Software Development Engineer at AWS, I was approached by my cofounder who shared his frustration with the market's shortcomings.

As a Product Director at a financial institution, he had spent 18 exhausting months searching for a risk-based transaction monitoring tool with real-time capabilities, only to encounter providers who consistently overpromised and underdelivered. This gap in the market revealed a critical need for an advanced compliance technology that could actually meet the needs of today’s financial institutions.

The opportunity to reimagine compliance solutions became clear when we combined our complementary expertise — my cofounder brought extensive product leadership experience and firsthand understanding of compliance system inadequacies, while my background building large-scale systems at companies like Palantir and AWS provided the technical foundation.

Together, we envisioned Flagright as a solution built for the modern era that truly works as advertised.

Our breakthrough came through a fortuitous introduction to a large fintech company experiencing the exact pain points we aimed to solve. My cofounder's professional network connected us with this company, which became Flagright's pilot customer. This early collaboration provided crucial validation and traction, ultimately becoming instrumental in our acceptance into Y Combinator.

On a mission

Today, Flagright is a company on a mission to revolutionize AML compliance and help financial institutions effectively combat money laundering and financial crimes.

Our AI-native platform comprises several core solutions:

• Transaction monitoring with a no-code rule builder for real-time and batch monitoring

• Case management that provides a unified dashboard for centralized alert management across L1, L2, and L3 teams

• AML screening that leverages third-party data to prevent watchlisted individuals from transacting funds.

Complementing these offerings are our customer risk scoring solution — a dynamic engine that automates risk assessment for individuals and businesses—and AI Forensics, which features specialized AI agents that perform specific tasks in key areas of AML compliance and fraud prevention.

Together, these solutions form a comprehensive suite designed to strengthen compliance while enhancing operational efficiency.

We hit a 7-figure ARR less than a year after launch and have doubled every twelve months since.

Choosing an angle

I confidently told my cofounder I could build a solution over a weekend. While that initial burst of development laid the foundation, what started as a weekend project evolved into a continuous journey of innovation — one that I am still pursuing with my team every day.

Rather than building a use-case specific product, we tackled the problem from a data processing perspective. This strategic decision proved to be one of our best, creating a flexible, ever-evolving system capable of processing all types of money movements in high volumes and real-time, addressing both money laundering and fraud detection needs.

Integration experience was another area where we saw opportunity for significant improvement. We prioritized developer experience by designing our API to be simple, straightforward, and entity-driven. We've maintained just six API endpoints from our initial offering, even as our product capabilities have substantially expanded. This approach has resulted in integration times averaging just one week, with our fastest implementation completed in only two and a half days.

Being a second mover in the compliance space allowed us to embrace an AI-native approach from day one, quickly establishing a competitive advantage. By embedding artificial intelligence into our operational tooling from inception, we've been able to deliver exceptionally efficient compliance solutions.

Choosing a tech stack

Our tech stack is centered around Node.js, Python, and Go on the backend, powering a real-time infrastructure that supports our AI-native AML platform.

On the frontend, we use React with a fully custom design system built from scratch to ensure a seamless and intuitive user experience across complex compliance workflows. We’ve architected our infrastructure for performance and modularity, with stream processing, granular RBAC, and multi-tenant isolation baked in from the ground up.

The stack has evolved significantly as we’ve scaled — both in terms of customer volume and product breadth. We’re the only real-time AML provider on the market, which means we’re constantly pushing the boundaries of throughput and latency. You simply can’t move data faster than the speed of light, and maintaining sub-second latency while scaling transaction volumes and integrating new AI applications remains one of our most rewarding technical challenges.

A growth playbook

We launched in November 2021 with a laser focus on early-stage startups, the segment most neglected by big, enterprise-only AML vendors. Being fresh YC alumni gave us instant warm access: We DM’d founders inside Bookface, showed a 90-second Loom of our no-code rules engine, and offered usage-based pricing that matched their runway.

By the end of June 2022 we’d signed eight startup customers and could point to real-world numbers (sub-two-week integrations, 90%+ false-positive reduction) instead of promises.

With proof in hand, we treated growth like an engineering loop: tight ICP slices, small outbound batches, and weekly copy tweaks that turned every new go-live into social proof.

Content backed the motion, short teardown posts on fresh enforcement actions and webinars where our engineers walked through rule tuning live. Each asset answered one burning question practitioners actually Googled, so organic search began compounding without ad spend.

Once the startup beachhead felt repeatable, we expanded vertically, first neobanks and BaaS platforms, then crypto on/off-ramps, followed by traditional banks, insurers, unit-trust managers, and wealth-management RIAs.

We kept the same playbook: Find an ignored pocket, win three reference logos, publish their results (with permission), and let credibility ripple outward.

Today, we serve customers in 50+ countries and handle everything from real-time card rails in Switzerland to unit-trust redemptions in Malaysia.

Apply to Y Combinator

One of the most pivotal advantages for us was being part of Y Combinator. The community, the hands-on advice, and the network of builders and early customers were absolutely transformative. I always recommend founders apply — there’s no substitute for the speed and clarity YC forces onto your thinking. Another major tailwind was timing: The rise of generative AI and modern data infrastructure aligned almost perfectly with our roadmap. That allowed us to build the first truly AI-native AML platform just as the market began looking for something beyond legacy rule-based systems.

It was also helpful that OpenAI provided early access to YC startups. This opportunity enabled us to experiment with AI applications ahead of competitors, ultimately positioning Flagright as the first compliance vendor to deeply integrate generative AI throughout our platform.

Sales mechanics

One of the biggest challenges we faced as tech-heavy founders was learning the mechanics of sales and distribution. We initially over-indexed on building an exceptional product, but underestimated how critical go-to-market motion, branding, and positioning are — especially in regulated spaces like financial compliance.

We had to quickly upskill ourselves on defining clear Ideal Customer Profiles (ICPs) and focusing all efforts — product, marketing, and sales—around them. Early on, we also missed opportunities by being too broad in outreach and not crafting messaging that resonated deeply with our target personas.

If we were starting over, I’d think about distribution, marketing, and product-market fit from day one. Perfecting product-market fit for narrowly defined ICPs —rather than building for a generic "market" — has been a key takeaway. Today, every decision across product development and go-to-market is run through that lens.

Treat go-to-market like engineering

My top advice for indie hackers: Treat go-to-market like an engineering system.

Track it, measure it, optimize it — just like you would with code. Build feedback loops, test positioning, and iterate messaging like product features. It's not enough to have a great product; you need to get it in front of the right people, in the right way, at the right time.

The biggest mistake I see is people assuming PMF as this mystical thing that just happens.

Incorrect.

You need to engineer PMF into being — by being obsessively focused on the needs of your ICPs and and figuring out how to let them know you exactly solve their problems in the best possible way.

Modular plans

Flagright operates on a SaaS subscription model where most of our customers commit to two-year contracts with annual upfront payments. Our pricing structure is flexible and tailored to each client's specific needs, with factors including selected products and features, number of user seats, transaction volume, customer base size, and other variables that align with their compliance requirements. This approach ensures clients only pay for what they truly need while allowing us to build predictable revenue streams.

The modularity of our software platform has been instrumental in both our sales process and revenue growth. Customers appreciate the ability to select specific components that address their unique challenges rather than paying for a monolithic solution with unused features.

This flexibility not only makes the purchasing decision more straightforward but also embodies our core values of trust and being unreasonably customer-obsessed. Our team regularly advises clients on how to optimize their investment — sometimes even suggesting configurations that might reduce their initial costs — because we prioritize building long-term partnerships over maximizing short-term revenue.

This approach has driven strong customer loyalty, referrals, and expansion opportunities as clients grow and add additional modules to their solution stack.

What's next?

Flagright is focusing on three transformative goals this year, beginning with the full launch of our AI Forensics product suite. Having already demonstrated remarkable results with AI Forensics for Screening — where customers experienced a 90% reduction in false positives and 80% decrease in alert investigation time — we are expanding this success across the compliance workflow.

To meet growing global demand, we are strategically expanding our international presence. This includes doubling down on North America with new offices in New York and San Francisco to strengthen relationships with financial institutions across the region. We have already established our EMEA headquarters in London, complementing our existing offices in Berlin, Singapore, and Bangalore. This global footprint will ensure around-the-clock support for customers across all time zones while reinforcing Flagright's position as a global leader in AI-driven AML compliance.

Simultaneously, we are deepening our commitment to empowering fintech startups through the Flagright Startup Program. This initiative will provide accessible, easily implementable AML compliance and risk management tools to help fintech startups scale securely from day one. This program opens the door for eligible startups to leverage Flagright’s core products, including transaction monitoring, AML screening, risk scoring, and case management, along with its latest AI-driven innovations — AI Forensics for Monitoring and AI Copilot. To make compliance effortless and accessible under the program, Flagright will offer an unbeatable startup-friendly pricing model: free access in the first year, a 50% discount in the second, and a smooth transition to standard pricing in the third. Through this program, fintech startups can focus on growth while staying ahead of regulatory challenges — without breaking the bank.

You can follow along on our X and LinkedIn. And check out Flagright!