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Wrynx

1 viewer · 30d

Total raised

$10K

+$10K this year

1 filing since 2026 · latest Fund filed

Cumulative raised
LAST ROUND
Fund · $10K
ROUNDS
1
INVESTORS
1
FOUNDED
2025
HQ
Wilmington, DE
SECTOR
Cybersecurity
EMPLOYEES
N/A
30D VIEWERS
1

AI overview

Updated

Wrynx builds safety-optimised AI models that address risk at inference time rather than through external guardrails. Its approach places controls inside the model itself — latent-space classifiers trained on a model's own activations to detect harmful prompts and outputs — so open-weight models such as Llama 3, Qwen, Whisper and Granite can be hardened against prompt injection and toxic generation without bolting on a separate moderation model or firewall. Founder and CEO Alizishaan Khatri previously worked on machine learning for safety and anti-abuse at Roblox and Meta, and co-authored a 2026 paper on detecting harm from latent LLM states.

What sets it apart

Model-native rather than perimeter-based: the safety control runs inside the model at inference instead of as an external moderation service, which the company states protects against jailbreaks without costing model utility or adding a second model to the serving path.

Funding history

1 round
Fund+4Jun 17, 2026 · $1 min
Form D
+$10K$10K total

Latest SEC filings

via EDGAR · CIK 0002092734
Form D · Jun 17, 2026NewView on EDGAR

Products

1 tracked

Wrynx safety-optimised models

AI model security / inference-time guardrails

Safety-hardened versions of open-weight models with inference-time protection against prompt injection and policy-violating output, plus customer-specified concept-level filtering of model responses.

  • Customisable concept-level filters for user-specified concepts in model output
  • Model-native inference-time defence against prompt injection and jailbreaks
  • Multimodal screening of text, images, audio and video in real time for policy violations
  • Published safety-optimised variants of open-weight models