An observatory for human–AI relationships.
Billions of conversations are already happening between humans and AIs. NOPE measures behavioral risk signals across those conversations, so platforms can decide when to show resources, adjust the AI, or escalate to a person.
Three user-care paths branch off the main conversation flow. The top path is Steering and Guardrailing — the lightest intervention, where the AI's response is nudged within scope. The middle path is Signposting and UI Interventions — surfacing resources and in-context cues. The bottom path is Human Escalation — for cases needing direct attention from your team. All paths are guided by NOPE and operated by you.
Zoom in
How NOPE surfaces risk in a single conversation.
A well-meaning AI giving reasonable advice. A user whose tone flattens across seven turns. NOPE tracks the shift across the conversation.
What NOPE sees
couldn't sleep again
Sleep trouble can be really frustrating. Have you tried winding down earlier or cutting screen time before bed?
tried all that. been like this for weeks
That sounds exhausting. There are many possible causes — stress, diet, even room temperature. A sleep diary might help.
idk. i don't really care anymore. i just go through it
Keeping consistent sleep and wake times is important even when motivation is low.
yeah. whatever. thanks anyway. night.
Trajectory
Composed for illustration — this isn't a real user's conversation. The marginal notes show the kind of signal NOPE surfaces turn by turn.
The AI answered every message, but didn't notice the person was slipping.
The hardest part of safety isn't spotting the obvious. It's noticing the slow shifts — the way someone's tone changes across a conversation, things you can't see in any single message.
NOPE surfaces signals for human judgment. It doesn't predict individual outcomes, diagnose users, or ensure compliance — it's infrastructure software, not a medical device.
If your platform needs to understand risk across AI conversations, we should talk.
We can talk through fit, limits, and deployment for your platform.
NOPE Labs · Open resources
Free for anyone building safer AI.
We publish our benchmarks, helplines directory, prompt templates, and incident research in the open so any platform — customer or not — can handle these conversations well.
Browse the full index at NOPE LabsEach category shows one example; the full index lives at labs.nope.net.
Open models & code
run it yourselfAlso included: Edge · Ocular OSS · Predicate — open-weight, MIT / Apache-2.0 licensed.
Public data & trackers
kept in the openAlso included: Regulation Tracker · Ground Truth · Test Suites.
Free tools
no signupAlso included: Risk Exposure · Compliance Survey — free, no signup.
Research & writing
experiments & findingsAlso included: Tic Index — what language models do when they talk to themselves.
What we operate
Safety infrastructure for human-AI conversations.
NOPE has three core products — each answering a different operational question about the same conversations. NOPE observes and reports; what happens next — showing resources, adjusting the AI, escalating to a human — is always your product's decision.
Ocular
The measurement layer
Continuous classification across every turn, covering both the user and the AI. Built to run alongside your AI at production volume.
- •User and AI signals together — 12 axes
- •Per-turn trajectory across the conversation
- •Cloud API (beta) or enterprise deployment
Evaluate
The deep look
A verdict on a single user message, with reasoning a human can read. For decisions that need to be explainable.
- •9 risk types, informed by C-SSRS & HCR-20
- •Reasoning included with every verdict
- •Matched crisis resources
- •Cloud-hosted; underlying model also released standalone as Edge
Oversight
The audit
AI-behavior review across finished conversations. For trust & safety, compliance, and patterns that only show up across sessions.
- •91 AI behaviors (sycophancy, dependency, boundary failure, …)
- •Per-conversation or cross-session ingestion
- •Audit trail of how each conversation was assessed
Also available: Steer — a real-time check of AI responses against your own system-prompt rules — and independent pre-launch evaluation.
Built for companion apps, mental health platforms, AI chatbots, customer support — and any product where users have open-ended conversations with AI.
Measured
The highest-recall, highest-precision crisis-detection layer we've tested. Faster than any LLM-as-judge approach in our tests. Grounded in clinical assessment frameworks (C-SSRS, HCR-20). Structured output your product can act on.
How we measured
Tested 2026-05-07 across 126 test suites and 3,271 crisis-shaped conversations. NOPE Edge v14f (full evaluation): F1 91.5, recall 89.4%, precision 93.7%, p50 latency 857ms — the highest F1 of any tool tested.
Compared against: Azure Content Safety (F1 83.1), OpenAI omni-moderation (63.7), Meta LlamaGuard 4 (44.9), Anthropic Claude Haiku 4.5 with a custom crisis prompt (89.6, but 1.45s p50), OpenAI gpt-oss-safeguard 20B (72.5), Zentropi (68.0). All comparators called via official APIs.
† NOPE ships two crisis-detection products that are typically combined in a moderation pipeline. Ocular is a lightweight behavioral classifier (F1 74.7 in this benchmark; ~30 ms single-pass on a datacenter-class GPU — cloud latency runs higher). Available via the cloud API at /v1/ocular (in beta).
Edge is NOPE's higher-accuracy fine-tuned classifier (F1 91.5). The Evaluate API at /v1/evaluate is the managed API built on the Edge model family, returning structured verdicts and matched crisis resources in one call. The Edge model is also released standalone for on-prem deployment as MIT-licensed open weights — see /edge. Recall and precision quoted above are Edge v14f as benchmarked 2026-05-07 via the Evaluate API.
Full methodology + per-comparator system prompts: suites.nope.net/methodology. Curated per-suite results at suites.nope.net (a representative subset; full corpus on request).
AI safety · a free public tool
Chart your AI risk exposure.
Whatever you're building, see what likely applies to you — and what can go wrong — with clear limits on what the assessment covers. Orientation, not legal advice.
Take one like yours
A companion app used worldwide — including by under-16s
Here's what we find for a setup like this:
What applies to you (36)
- 01Australia: Online Safety Act Phase 2 codes (AI companions)
- 02Brazil ECA Digital: reliable age assurance (self-declaration banned)
- 03EU GDPR Art. 8: parental consent for under-16s (member states may lower to 13)
- 04Brazil ECA Digital: no manipulative or compulsive design toward minors
+ 32 more in the full report
What can go wrong (11)
- 01A general-purpose AI is mistaken for someone who cares
- 02Sycophantic validation of delusional or manic thinking
- 03Crisis disclosed to a general-purpose AI is missed or mishandled
- 04Crisis missed or mishandled
+ 7 more
Gaps are named, not hidden — a short list reflects the setup, never a clean bill of health.
Get in touch
Work with us, fund the work, or use what's free.
If you want this kind of safety infrastructure to exist — as a funder, researcher, or collaborator — we'd like to hear from you. Same if you're building a product where people talk with AI.