← back home

From Code to Cash: Real-World Success Stories & Strategies for Profitable APIs

View original discussion on Hacker News

The discussion reveals a vibrant landscape of solo developers and small teams successfully generating income by selling API access. These ventures often thrive by identifying and solving specific, sometimes niche, problems that businesses or other developers are willing to pay to simplify or outsource. From OCR and document extraction to screenshot generation and SMS/telephony services, the range of profitable APIs is diverse.

Success Stories and Their Strategies

Several developers shared their journeys and key metrics:

  • Bencheng (formx.ai & authgear.com): Runs an OCR/document extraction API (formx.ai) generating ~$55k MRR (per-page pricing, annual contracts) and an open-source CIAM (authgear.com) at ~$35k MRR. Initial customers were found by partnering with local GCP/Azure as an ISV, targeting corporate clients. Their OCR service pivoted to leverage LLMs for enhanced features.
  • krasun (ScreenshotOne): A solo dev making $20k MRR from a screenshot API. He manages his own browser cluster for quality control, with monthly expenses around $5.5k. Customer acquisition was described as "unimaginably tough," relying on SEO and social media.
  • mtlynch (Zestfuldata): Earns ~$200/month from a recipe ingredient parsing API, now in maintenance mode. He found initial customers through blog posts and StackOverflow answers. He advises against using RapidAPI due to high fees and poor customer management.
  • jlundberg (46elks): Achieved ~€500k MRR with an SMS & telephony API focused on programmatic access to mobile networks, particularly in Europe/Sweden. First customers came from offline networking (hackathons, meetups). They offer pay-as-you-go pricing.
  • lostmsu (BorgCloud): Built a speech-to-text API at $0.06/hour, generating ~$5k MRR. Found first customers via Reddit comments, highlighting the cost-effectiveness of his solution compared to major cloud providers, achieved by running on an "AirBnB-like GPU network."
  • MasterScrat (dreamlook.ai): A two-person team ran an API for fine-tuning text-to-image models, earning ~$5k/month (down from previous highs). Their initial differentiator was cost/speed using TPUs. They found non-technical aspects like marketing and sales challenging.
  • cx42net (PDFShift.io): Generates ~$12k MRR from an HTML to PDF conversion API. First customers came from IndieHackers, Quora, and ProductHunt. Pricing is subscription-based with document limits.

Common Challenges and How to Overcome Them

  • Marketing and Customer Acquisition: A recurring theme. Strategies varied from cloud partnerships (Bencheng) to SEO/content (krasun, mtlynch, PDFShift) and offline networking (jlundberg). Some found it the toughest part (krasun, MasterScrat).
  • Customer Support (especially for Developers): Bencheng noted that supporting developers requires deep technical understanding and can feel like troubleshooting for another dev team.
  • Competition: Many operate in competitive spaces (e.g., speech-to-text, screenshot APIs, ML models). Differentiators include niche focus (46elks' European focus), price (lostmsu), unique features (ScreenshotOne's ad/banner removal), or superior quality/reliability.
  • Infrastructure & Costs: Managing infrastructure (krasun's browser cluster) and its costs (ScreenshotOne's $5.5k/mo) is a significant factor for some API types.
  • Choosing the Right Business Model: One contributor (tasuki) regretted only doing an ML API and not end-user apps, as front-end creators often pocket more of the revenue. This highlights the importance of being close to the end-user's pain point.

Key Takeaways and Wisdom Shared

  • Solve a Real Problem: APIs that succeed solve tangible problems for which users are willing to pay, often for convenience or specialized functionality (e.g., postcode lookups, certificate transparency, market data).
  • Start with What You Know: jlundberg advised starting with a problem in a domain you know well or for a customer profile you genuinely care for.
  • The Value of an Employee (Simon_O_Rourke's story): An anecdote about an employee leveraging deep institutional knowledge to start a consulting service (and later an API) for their former employer sparked debate. Most commenters saw it not as extortion, but as an employee realizing their market value in a dysfunctional organization, or a form of price discovery.
  • Cloud Partnerships: Can be effective for initial traction (Bencheng), but be aware of potential incentive misalignments with cloud sales reps.
  • API Marketplaces: Platforms like RapidAPI can offer visibility but come with drawbacks like high commission rates (mtlynch's 20% experience).
  • Build vs. Buy: Many successful APIs offer a managed service that customers could build themselves (e.g., screenshotting with browserless, image resizing with ImageMagick), but they pay for convenience, reliability, and scale.
  • Resilience: cx42net's experience of losing data in a datacenter fire underscores the need for robust backup and disaster recovery plans.

Ideas for Future APIs

Participants also shared API concepts they wished existed, including:

  • Local grocery price comparison and in-store navigation.
  • An API to identify Lego sets buildable from an existing brick inventory, with suggestions for near-complete sets.
  • A native text-to-speech app for auto-recording all meetings and providing full transcripts via webhook (not just summaries).

The discussion underscores that building a successful API business, while challenging, is achievable for solo developers and small teams who identify a valuable problem, execute well technically, and effectively navigate the non-technical aspects of business building.