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database-saas

Interview with Rashid Khasanov, Founder Building $32K/Month From Simple Database SaaS Products

Roger Mendoza

• 8 min read

Table of Contents

🧱 Why boring database websites still win

What is the big idea behind these three businesses?

Rashid’s answer is refreshingly unglamorous: build a useful list for people with an expensive problem.

His portfolio generates roughly $32,000 in monthly recurring revenue, mostly through three database products that look structurally similar but serve adjacent business needs. Angel Match helps startup founders find investors. Investor Hunt is a simpler investor database. Journalist Hunt helps small businesses and media teams find journalists for press outreach.

This is not an AI-powered launch system for creators with fourteen automations, a dashboard full of purple gradients, and a pricing page designed by someone who fears plain language. It is a database, filters, useful contact information, and a reason for somebody to pay.

The underlying model is simple:

  • Find a business task people currently do manually.
  • Collect the relevant information in one searchable place.
  • Make the data useful enough to save time or produce revenue.
  • Charge recurring revenue for access, outreach capacity, or better workflow features.

The simplicity is the point. These businesses solve a painful operational problem instead of inventing a new category of software nobody requested.

What are the three products, and how do they make money?

Angel Match is the main product. It contains a database of around 125,000 angel investors and venture capital firms, focused on early-stage founders raising capital. The platform combines investor discovery with outreach tools, so founders can search, build lists, and begin pitching from one place.

Angel Match was generating about $29,000 MRR with 360 active subscribers. Its trial conversion rate was around 33%, and it received roughly 800 to 1,000 clicks per day across organic search, referrals, direct traffic, and some Facebook ads. Plans begin at $59 monthly, with higher tiers for people who need to contact more investors.

Investor Hunt serves a similar use case as a straightforward investor database. It was generating approximately $2,800 MRR, largely through SEO without active marketing. Its tiers were priced at $57, $97, and $297 per month.

Journalist Hunt is a database of approximately 200,000 journalists. It helps businesses identify relevant press contacts and organize media outreach. It was generating around $260 MRR, with core plans in the $49 to $99 monthly range.

The numbers are useful, but the more useful lesson is that the products share a repeatable structure. Rashid did not need three different galaxies of product logic. He built variations of the same information product for markets where access to the right people has financial value.

🔎 The problem came before the product

How did Angel Match start?

Rashid was not a technical founder. He studied finance and, during his final year of college, started building a fintech investment app with a college friend. They raised $100,000 from family and friends, maxed out credit cards, took personal loans, and eventually needed professional investors.

That created the real problem.

To raise money, they manually searched Google, LinkedIn, Twitter, VC websites, and investor pages to compile a list of people worth contacting. The process was slow, repetitive, and fairly terrible. It did help them get calls with notable investors and angels, but it also exposed the product opportunity hiding in plain sight.

Cold outreach could work. Finding the right contacts was the painful part.

So the team asked a practical question: if finding investors took this much time for them, would other early-stage founders pay to avoid it?

How was the idea validated without building a massive platform first?

The first version was a database of about 40,000 investors assembled manually with a small team. No mystical startup origin story required. Just collecting information people needed and putting it in a more usable format.

They launched the early Angel Match product on Product Hunt. That first month produced about $4,000 in revenue. More importantly, it produced a better signal than compliments, waitlist emails, or a founder’s friend saying, “This could be huge.” People paid.

That is the standard. A paying customer validates the direction. Everything else is mostly theater with better typography.

For solo builders using no-code startup tools or a more custom stack, the initial version does not need every possible field, filter, or enrichment workflow. It needs to solve one urgent job for one specific group.

🎯 Why these database products work

What makes a database product worth paying for?

Rashid comes back to the same principle: solve a painful problem for a clearly defined audience.

Angel Match worked partly because the founders understood the customer. They were early-stage founders trying to raise capital themselves. They knew the time sink, the uncertainty, and the cost of reaching out to the wrong people.

That made the positioning sharper. Angel Match was not “a big list of investors.” It was a shortcut for founders who needed relevant investor contacts and a practical way to start outreach.

A good database product typically has three ingredients:

  • A painful outcome: The buyer loses money, time, deals, attention, or opportunities without better information.
  • A narrow audience: A specific group should instantly recognize the problem as theirs.
  • Actionable data: The customer needs more than names. They need context that helps them decide who to contact, sponsor, hire, pitch, or partner with.

The most attractive markets tend to be B2B. Businesses can justify recurring spend when a database helps them win customers, close partnerships, raise capital, secure coverage, or reduce hours of manual research. A consumer directory may still work, but it is usually harder to charge $50 to $100 per month for a list of dog trainers or local magicians. The spreadsheet does not become valuable just because it has a search bar.

What adjacent database ideas stand out?

Rashid points to influencer databases categorized by location, audience size, and content niche. Brands and agencies need to find and reach relevant creators, and manual sourcing is tedious.

Another opportunity is a newsletter sponsorship database. There is growing demand for paid newsletter placements, but finding suitable newsletters, audience fit, sponsorship terms, and contact details can become a small unpaid internship in browser-tab management.

The pattern matters more than the examples. Look for a market where someone repeatedly asks:

  • Who are the right people to contact?
  • Which companies fit this profile?
  • Where can this inventory, channel, or audience be found?
  • How can the research be filtered before outreach begins?

📈 How SEO turned a small launch into a compounding channel

How did the portfolio grow from early traction to meaningful MRR?

At one point, Angel Match was receiving around 60 clicks a day. Rashid looked at the number and asked the only question worth asking: what happens if this traffic grows tenfold?

That led to SEO.

The team hired six content writers and published consistently. In parallel, the technical team built free tools and useful content assets for the same audience. These included resources such as fundraising email templates and investor outreach tools. The work continued for six to eight months before the traffic began to compound in a meaningful way.

That SEO effort helped grow the business from about $3,000 MRR to $20,000 MRR. Meta ads were added later, and Angel Match reached a high point of approximately $43,000 MRR.

For directory and database products, programmatic SEO is especially relevant because the product naturally contains structured information. A useful directory can create pages around categories, industries, locations, investor types, publications, or other searchable filters.

But the word “programmatic” has acquired the same magical aura as “AI funnel builder.” It is not magic. It is a method for creating useful, structured pages at scale. If the pages are thin, generic, or copied from another source, Google has seen that movie. If they help someone find a relevant investor, journalist, or partner, they can earn traffic.

What should a founder publish?

Rashid’s approach suggests building content around the surrounding job, not just the database itself. A founder raising money might search for:

  • Fundraising email templates
  • How to find seed investors
  • Late-stage startup examples
  • Investor lists by industry or geography
  • Funding strategy resources

The product should be the logical next step after the resource, not a trapdoor hidden under every paragraph. Helpful content creates trust, captures search demand, and gives the database more entry points than a homepage ever will.

🛠️ The database product playbook

If Rashid started over, what would he do first?

His playbook is compact enough to test without turning it into a six-week Notion operating system.

  1. Choose an idea that solves a particular problem. Do not begin with “I should make a directory.” Begin with a painful task that requires difficult research or outreach.
  2. Build the database. Data can be collected manually at first. More technical builders can create automated collection systems, but automation is not a prerequisite for proof.
  3. Launch and get real feedback. Put the product in front of the people with the problem. If people sign up and pay, there is a signal worth pursuing.
  4. Focus on SEO after launch. Rashid says programmatic SEO drives roughly half of the revenue for these products. Consistency matters more than publishing a small pile of articles and declaring search dead by Thursday.

What does this look like for a solo builder tonight?

A practical first test could be brutally small:

  • Pick one buyer with a repeatable research task.
  • Create a spreadsheet with 100 to 300 relevant entries.
  • Add the fields that make the data actually useful, such as location, niche, contact details, audience size, investment stage, or company type.
  • Create a simple gated page describing the outcome, not the database mechanics.
  • Ask potential customers to pay for access or commit to a trial.

This approach will not replace proper data quality, product design, or compliance work later. It is simply a sane way to learn whether anyone cares before building the aircraft carrier.

⚙️ The tech stack behind the boring machine

What stack does Rashid use to run these products?

The main products use Next.js on the front end, Nest.js on the back end, and PostgreSQL for the database. They are hosted on DigitalOcean.

The rest of the stack supports the operational parts that turn a directory into a usable SaaS product:

  • Nylas for email outreach capabilities inside Angel Match
  • Cloudflare for security and bot prevention
  • Klaviyo for email marketing and automated flows
  • Google Workspace for email
  • Ahrefs for SEO research and monitoring

Rashid’s broader point is not that everyone needs this exact solo builder tech stack. He is not technical himself and relied on developers to build the products. The point is that a founder does not need to personally write every line of code to understand the customer, validate the data, set the strategy, and build a real business.

Use the simplest stack that gets a credible version live. The architecture can become more impressive after the customer problem becomes more real.

🧠 The real talk: patience beats shiny-object economics

What advice would Rashid give to someone looking for a first idea?

Be patient, do the work, and do not give up too early.

Rashid saw other founders start around the same time, make more money faster, and later disappear because they quit. That is not a guarantee that persistence fixes a bad idea. It does not. But good businesses often compound quietly while the internet is busy applauding whatever category is currently wearing the AI hat.

These products did not need to chase a trend. They solved a recurring B2B problem, accumulated useful data, built search traffic, and kept improving the path from research to outreach.

That is the takeaway for anyone trying to launch with AI tools, no-code startup tools, or a custom-coded product: use the tools to reduce the build time, not to avoid the hard question. What expensive, tedious problem is this removing for a specific person?

An AI-powered launch system for creators can be useful if it helps creators get work done. So can a directory, a spreadsheet, or a plain database with good filters. The format is secondary. The pain is the business.

What should builders take away from Rashid’s model?

Start with an annoying reality you understand. Build a smaller version than seems respectable. Get data into a usable shape. Charge early. Publish useful search-driven resources. Then keep going long enough for the system to compound.

It may not make for the loudest startup story. It may, however, make for a business that survives after the trend cycle moves on to something else. That is usually the better deal.

❓ Frequently asked questions

What is a database SaaS product?

A database SaaS product organizes valuable information for a specific audience and charges for access, filtering, outreach tools, or workflow features. Angel Match, Investor Hunt, and Journalist Hunt are examples focused on investors and media contacts.

Why are B2B directories often easier to monetize?

B2B customers can justify recurring subscription costs when better information helps them raise capital, reach potential customers, secure press coverage, or save substantial research time. The database is tied to a business outcome rather than casual browsing.

How can a founder validate a database idea quickly?

Start with a focused manual database, put it in front of people who have the problem, and look for payments or serious signups. Rashid’s initial Angel Match launch produced revenue quickly, providing evidence that founders valued the investor research shortcut.

Does programmatic SEO work for database products?

It can work well when structured pages genuinely help people search for relevant contacts, categories, locations, or market segments. Rashid reports that programmatic SEO drives about half of the revenue for his directory products.

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