OPENAI MODERATION ALTERNATIVE
OpenAI Moderation API vs Sentiqra
Get multilingual coverage across 12 production analyzers, 2,680 indicators, and versioned, hash-verifiable outputs - with a sub-500ms p95 latency target.
Feature-by-feature comparison
Last verified September 26, 2026 · omni-moderation-latest (13 categories with per-category category_scores, text + image) · Source: OpenAI Moderation guide
| Feature | Sentiqra | OpenAI Moderation API |
|---|---|---|
| Languages | Varies by domain | ~95 (variable quality) |
| Indicators/Categories | Domain-specific | 13 categories |
| Per-indicator signal score | Yes | No |
| Structured taxonomy | Yes (groups + concepts) | No |
| Deterministic output | Yes | Model-versioned (behavior can change on omni-moderation-latest updates) |
| Semantic version identity | Explicit (configuration ID per response) | Varies |
| Drift surface | Analyzer/configuration change only | Provider model + taxonomy changes |
| Reproducible audit trail | Yes (pinned config) | No |
| Custom taxonomy | Yes (Enterprise) | No |
| Custom thresholds & policy logic | Yes - all plans (customer-side) | Customer-side only |
| Product domains | 12 production analyzers | 1 (T&S only) |
When is OpenAI Moderation API the right choice?
OpenAI Moderation is an excellent, free tool for basic English-language safety filtering. If your platform primarily handles English text, fits neatly into OpenAI's 11 broad categories, and you do not require strict SLA guarantees or granular policy mapping, it is often the best starting point.
Where OpenAI Moderation API works
- Free for OpenAI API users
- Low latency
- Good English accuracy
- Easy to integrate
- Predefined safety categories
Where OpenAI Moderation API falls short
- Limited multilingual accuracy
- Broad categories only - per-category scores returned, but no per-indicator granularity
- No structured taxonomy beyond predefined categories
- No custom taxonomy
- No deterministic outputs
When to switch from OpenAI Moderation API
While OpenAI Moderation API is free, scaling platforms often outgrow its capabilities. Switch to Sentiqra when you need multilingual coverage, a structured taxonomy for complex policy mapping, or deterministic outputs for audit trails.
Languages platform-wide; 8-41 per analyzer. View benchmark evidence.
Indicators across the production analyzer catalog for granular policy mapping.
Broad categories to granular signals in the T&S analyzer alone - threshold each independently.
Beyond 11 Categories
OpenAI Moderation maps content to 11 broad categories. Sentiqra provides 2,680 granular indicators, allowing you to map directly to your specific policies rather than relying on generic flags.
The True Cost of "Free"
OpenAI Moderation is free, making it highly attractive for early-stage projects. However, for enterprise workloads, the hidden costs of English-centric limitations and manual review overhead quickly outweigh API savings.
Migration is real work, and it's worth it
OpenAI Moderation returns 11 broad category flags. Sentiqra returns 2,680 granular signals with per-indicator confidence. Migrating means remapping your policy logic from category-level rules (if hate = true, block) to signal-level rules (if hate_identity_attack > 0.85, block; if insults_derogation > 0.85, warn). Typical migration is 1-3 weeks of policy engineering work. In exchange, your policy team gets signals granular enough to reason about - and every decision carries a signed receipt your appeals team can replay.
// OpenAI Moderation
const response = await openai.moderations.create({ input: "Sample text" });
// Sentiqra - one call, named analyzers, max 2 per request
const response = await fetch("https://sentiqra.tech/v1/analyze", {
method: "POST",
headers: { "Authorization": "Bearer $KEY", "Content-Type": "application/json" },
body: JSON.stringify({ text: "Sample text", analyzers: ["trust-safety"] })
});OpenAI categories → Sentiqra signal groups
Each OpenAI category maps to one or more Sentiqra signal groups in the Trust & Safety analyzer - and each group carries 10 granular signals you can threshold independently.
| OpenAI category | Sentiqra signal group(s) | Granularity |
|---|---|---|
| hate | hate_identity_attack, identity_discrimination, dehumanization_exclusionary_harm | 30 signals |
| hate/threatening | threats_intimidation, incitement_violence | 20 signals |
| harassment | harassment_targeting, bullying_exclusion, insults_derogation | 30 signals |
| harassment/threatening | threats_intimidation | 10 signals |
| self-harm, self-harm/intent | self_harm_encouragement, self_harm_ideation | 20 signals |
| self-harm/instructions | self_harm_encouragement, self_harm_ideation, dangerous_behavior_encouragement | 30 signals |
| sexual | sexual_harassment_abuse | 10 signals |
| sexual/minors | child_safety_predatory_language | 10 signals |
| violence, violence/graphic | incitement_violence, violent_extremism | 20 signals |
| illicit, illicit/violent | scams_fraud_impersonation, evasion_coded_abuse | 20 signals |
Full taxonomy: Indicator Dictionary. Your existing score > 0.7 rules translate to per-signal thresholds - the evaluation checklist walks through calibrating them on your labeled set.
Frequently Asked Questions
Is Sentiqra free like OpenAI Moderation?
Sentiqra offers a free tier for testing and development, but production usage is paid. While OpenAI Moderation is free, Sentiqra provides enterprise-grade SLAs, multilingual analyzer support, and 2,680 indicators that can reduce manual review costs.
How does language support compare?
OpenAI Moderation is primarily optimized for English. Sentiqra provides multilingual analyzer support with generated per-language benchmark evidence, making it suitable for global platforms.
How do I map OpenAI's 13 categories to Sentiqra?
Each OpenAI category maps to one or more Sentiqra signal groups - the full mapping table is published on this page above. hate maps to hate_identity_attack + identity_discrimination + dehumanization_exclusionary_harm; each group carries 10 granular signals with independent confidence thresholds.
What is the migration effort from OpenAI Moderation?
Migration is real work - typically 1-3 weeks of policy engineering to remap category-level rules to signal-level thresholds on your labeled set. In exchange you get granular signals, per-indicator confidence, and a signed receipt on every decision that your appeals team can replay.
Reference Architecture
See how a multilingual social platform could migrate from prompted LLM classification to Sentiqra's deterministic detection - with modeled economics and before/after pipeline diagrams.
View the reference architecture →When OpenAI Moderation API is still the right choice
If your platform is English-only, fits neatly into OpenAI's broad categories, and you don't need per-signal thresholds or audit receipts, OpenAI Moderation is a genuinely good - and free - starting point. Many teams outgrow it; few regret starting there.