Trust & Safety
Contexa Overview
Score, Log, and Act on Policy-Violating Content — Without Drowning Legitimate Speech in False Positives
Turn moderation from a manual, inconsistent chore into an auditable, real-time pipeline.
Hate speech, harassment, and coded slang keep mutating faster than keyword filters can keep up, while manual review teams can't keep pace with volume — and every blocking decision needs a defensible paper trail. Off-the-shelf classifiers make it worse in one specific way: they flag the token, not the context, so quotes, satire, counter-speech, and reclaimed language get blocked right alongside the violations they were quoting.
Contexa, our AI Trust & Safety Platform, analyzes posts, comments, chat, nicknames, and profile text across your community surfaces, scores policy-violation risk in real time, and routes each decision — allow, monitor, review, or block — into a fully logged evidence trail your moderators and legal team can actually stand behind.
Capability Matrix
| Product Capabilities | Core Functions | Business Impact |
|---|---|---|
| Context-Aware Classifier | Rule engine + AI classifier + LLM context analyzer for quotes, satire, and counter-speech. | Fewer false positives, less over-blocking of legitimate speech. |
| Multi-Category Risk Scoring | Eight policy categories scored 0–100, from hate speech to self-harm risk. | Consistent, explainable thresholds instead of per-moderator judgment calls. |
| Automated Decision Routing | Allow / monitor / review-queue / auto-block based on risk tier. | Cuts manual review load and speeds up response time. |
| Evidence & Trust Score Ledger | Full detection history, moderator actions, and per-user trust scores. | Defensible audit trail for disputes and compliance review. |
Key Value Propositions
🎯 1. Context Over Keywords
Keyword filters and off-the-shelf classifiers score tokens, not meaning — so quotes, satire, counter-speech, and reclaimed language get blocked alongside real violations.
- Layered Detection: A rule engine for known terms and evasion patterns (character-splitting, initialisms, lookalike substitution) feeds a KoBERT-class classifier, refined by an LLM context analyzer for the cases that need judgment.
- Multi-Category Scoring: Every piece of content is scored across eight policy categories — hate speech, harassment, extremist content, misinformation, toxic behavior, sexual content, self-harm risk, and community-specific rulesets — with per-category confidence, not a single pass/fail flag.
- Dynamic Rulesets: Moderators register new slang, evasions, and community-specific terms as they emerge, without waiting on a model retrain.
⚖️ 2. Real-Time Risk Scoring & Automated Action
Every piece of content resolves to a single 0–100 risk score, blending content risk with the author's violation history — and routes straight to the right action.
- Four-Tier Decisioning: Low risk is allowed, medium is monitored, high goes to a moderator review queue, and critical is auto-blocked — with the same thresholds applied consistently, every time.
- User Trust Scoring: Accounts carry a trust score that degrades on violations and recovers over time, so repeat offenders get stricter scrutiny without penalizing a single bad day.
- Sub-Second Targets: Built for a real-time posting experience — sub-second scoring latency so moderation doesn't become the bottleneck in your comment or chat flow.
🗂️ 3. Evidence Logging & Defensible Moderation
Every detection and every moderator action is written to an evidence log — because when a user disputes a block, "the AI flagged it" isn't a defense.
- Full Audit Trail: Original text, detection timestamp, matched rules, per-category AI scores, final risk score, and the resulting decision are all retained and searchable.
- Feedback Loop: Moderator overrides and false-positive reports feed directly back into training data, so the classifier improves on your community's actual edge cases over time.
📊 4. Operator Dashboard & RBAC
Give admins, moderators, and read-only stakeholders exactly the access they need, backed by a live view of what's happening across your platform.
- Live Detection Feed & Review Queue: Real-time violation stream, risk distribution, repeat-offender rankings, and an approve / remove / block / permanently-block queue for anything routed to human review.
- Role-Based Access: Admins manage policy and retraining triggers, moderators work the queue, and viewers get read-only analytics — with every admin action captured in an audit log.
Target Customer Profiles
Community & Social Platforms
Boards, comment sections, and open chat rooms that need real-time moderation at volume without a manual review team reading every post.
Game & Live Chat Operators
In-game chat and open-chat services where harassment and toxic behavior spike fast and slang evolves faster than static filters can track.
Trust & Safety Teams
Teams that need an auditable, explainable decision trail for every block — not just a flag — to stand behind moderation decisions when they're challenged.