The industry pays $500,000/month for work AI now does for $85,000.
Nexoforma has built a purpose-engineered AI compliance system for the adult live-streaming industry. After studying the full operational reality of content moderation in this space — ID matching, violation flagging across 20+ categories, BOLO detection, escalation routing — we engineered SENTINEL-AI to automate 90%+ of the workload that human floors handle today. Here is what that means for any operator running a 500-seat compliance team.
// Projected Annual Savings
$4.98M
per year — every year
For a typical 500-seat operation running at $6M/year, a SENTINEL-AI deployment plus a skeleton 50-person QA team for edge cases and escalations delivers this saving — net of all infrastructure costs. Payback period: under 45 days.
The Math
Side by side. At industry scale.
Standard industry SOP targets 70 actions/hour per human agent. Our engine sustains 1,800/hour per GPU instance — 25× faster, with higher recall on the categories that carry the most legal and reputational exposure (underage detection, BOLO matches, prohibited acts).
Today500 agents, 24/7
Headcount500
Monthly cost$500,000
Annual cost$6,000,000
Throughput / hour35,000 rooms
Avg. decision time51 seconds
Human error / fatigue5–9%
Attrition & retrainingongoing
With NexoformaAI + 50-person QA
Headcount (QA only)50
Monthly cost$85,000
Annual cost$1,020,000
Throughput / hour180,000+ rooms
Avg. decision time0.4 seconds
Consistency99.4% recall
Scales on demandinstantly
83%
Reduction in monthly compliance spend — without sacrificing coverage.
5×
Throughput increase. You can moderate every single stream, not just a sampled portion.
<45d
Payback period on the full deployment, including integration and QA team ramp.
The Engine
How SENTINEL-AI replicates your SOP.
Live-stream moderation, at its core, is a high-volume classification problem — and modern vision-language models handle this workload natively. Nexoforma has purpose-trained SENTINEL-AI on the complete violation schema used across the industry, so it's production-ready from Day 1 of any deployment.
01
Ingest the compliance queue
Direct API integration with your existing compliance queue. No infrastructure change — the AI reads the same stream your human agents read today, via the same interface.
02
Multimodal frame + metadata analysis
Each room is analyzed on: video frames (visual violations), ID match (document vs. performer face), room subject, user chat log, and recent images — every input a human moderator uses, processed simultaneously.
03
Classify against all 22+ violation categories
Single inference call per room returns: approve / flag / escalate, with category, confidence score, and evidence frame. 99.4% recall on high-severity categories in our internal benchmarks.
04
Route to skeleton QA team for edge cases
Only ambiguous decisions (confidence < 85%), BOLO matches, and photo-verification requests reach a human reviewer. That's under 8% of queue volume — handled by a lean 50-person QA team, with final oversight by your US compliance leadership exactly as it works today.
05
Continuous audit trail + compliance reporting
Every decision is logged with the evidence frame and classification confidence. Compliance leadership gets a live dashboard with violation heatmaps, false-positive rates, and jurisdictional audit exports on demand.
Scope
Every violation category. Covered on Day 1.
We've mapped the full violation taxonomy used across the adult live-streaming industry and trained SENTINEL-AI against every category. Nothing bolt-on, nothing custom-built later. Production-ready now.
Underage (w/ & w/o nudity)
Abusive & harmful behavior
Fisting
Sexual props misuse
Oversized toys
Offline payment solicitation
3rd-party chat (Skype etc.)
Bestiality
Incest
Narcotics on cam
Excessive drinking
Pee / Poo / Blood
Service uniforms
Religious symbols
Broadcasting in public
Goatse displays
Sleeping on cam
Moving vehicle
>5 individuals on cam
Away > 30 min
Copyrighted media
ID mismatch / missing
BOLO account detection
Compliance photo verify
Risk Reduction
The compliance exposure you don't see today.
Human teams have a baseline miss rate. At your scale, that's thousands of missed violations monthly — and in the highest-severity categories, that's regulatory exposure. AI gives you auditable, zero-fatigue coverage.
Risk Vector
Today
With SENTINEL-AI
Missed underage detections
5–9% baseline miss
<0.3% (flagged + escalated)
Shift-end fatigue errors
Sharp rise hours 6–8
None. AI doesn't fatigue.
SOP drift across agents
Variable by individual
100% policy consistency
Audit trail for regulators
Manual, partial
Full evidence log, exportable
Attrition & retraining cost
Ongoing, 20–30%/yr
Near zero — model is static
Scale to 2× traffic spike
Weeks. Hire, train, deploy.
Minutes. Spin up GPU nodes.
30-day paid pilot. Your risk: zero.
We run SENTINEL-AI in parallel with your existing floor for 30 days on a sample slice of traffic of your choosing. We publish side-by-side accuracy and throughput numbers against your own QA team. If we don't beat them on both, you pay nothing.