Build an AI Content Moderation API

1. 1

   Understand you are selling compliance capability, not a gadget

   The demand here is created by law, not fashion. Platforms hosting user content face the EU Digital Services Act, the UK Online Safety Act, and a legal mandate to scan for and report child sexual abuse material (CSAM), plus growing obligations under the EU AI Act, and most cannot build detection in-house. Your product is an API that classifies images, video, text, and audio for harmful content so those platforms can meet duties they cannot staff. Frame the business as compliance infrastructure, because that is what buyers are actually purchasing.

2. 2

   Pick your content types and harm categories

   Do not try to detect everything at once. Choose one or two content types (say images and text) and specific harm categories (nudity and sexual content, violence, hate speech, spam, self-harm, CSAM-adjacent signals) where you can achieve reliable, defensible accuracy. Companies like Hive built businesses on exactly this API-based classification model; the lesson is focus and reliability, not that you will match their scale.

3. 3

   Handle CSAM detection with extreme care and the right partners

   CSAM is a special legal and ethical category: detection typically relies on established hash-matching databases and reporting pipelines (such as those operated by recognized child-safety organizations and mandated reporting channels), and handling this material carries strict legal obligations. Do not improvise here. Partner with the established programs, follow mandated reporting law exactly, and get specialized legal counsel before you offer any CSAM-related capability, because getting it wrong is both illegal and harmful.

4. 4

   Build responsibly and measure honestly

   Moderation models make consequential errors in both directions: false positives censor legitimate content, false negatives leave harm up. Buyers and regulators care about accuracy, bias, and explainability, and the EU AI Act increasingly requires it. Measure precision and recall per category honestly, disclose limitations, keep humans in the loop for hard calls, and treat your model's failure modes as a core product concern, not a footnote.

5. 5

   Package as a clean, priced API

   Sell it the way developers buy: a well-documented API with clear endpoints, predictable latency, per-call or volume-tiered pricing, and easy integration. Your customers are platforms, apps, marketplaces, dating services, and communities that need to moderate at a scale humans alone cannot. Make it trivially easy to send content and get back a classification and confidence score, because integration friction loses deals in developer markets.

6. 6

   Know your lane versus the human services

   This is the automated-detection layer. A separate business (the human-in-the-loop managed moderation service, which has its own card in the bank) staffs trained reviewers to make judgment calls and enforce policy. The two are complementary: automated detection filters and prioritizes at scale, humans handle the ambiguous and appealed cases. Position your API as the software layer, and consider partnering with (rather than trying to replace) the human-review providers.

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