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Tools/Vijil vs LLM Guard
Vijil

Vijil

security
vs
LLM Guard

LLM Guard

security

Vijil vs LLM Guard — Comparison

Overview
What each tool does and who it's for

Vijil

Cut time-to-trust in AI agents from 6 months to 6 weeks. Vijil makes agents reliable, secure & safe for enterprises with testing & protection.

To help enterprises use AI agents that are verifiably reliable, secure, and safe by providing trust as infrastructure for agent development, operations, and continuous improvement. Previously GM Director of Engineering at Amazon SageMaker. 30y across AI/ML, Data, Cloud, OS, Security; 11 AWS AI services, 30 products, 10 patents, 5 papers. AWS AI senior leader; 20y in ML systems and graphics; led PyTorch, TensorFlow, and AWS SageMaker Training teams. Previously COO at Astronomer; helped scale Lacework from $1M to $100M ARR; 20y GTM strategy partnerships for cybersecurity; consulting and investment banking; Harvard. Assistant Professor of Statistical Sciences at the University of Toronto, a Faculty Member at the Vector Institute for Artificial Intelligence, and a Faculty Affiliate at the Schwartz Reisman Institute for Technology and Society. Responsible AI leader; 10y+ in data science; co-author Trustworthy ML (O'Reilly book); 40 papers, 20 patents; key contributor to OSS (Garak, AVID, AI Village). Previously at Amazon Music,Oracle, and Viiv Labs; co-founder CTO of Adya (acquired by Qualys). Passionate about designing and building large-scale ML systems with a focus on NLP/LLMs. Enjoys reading, hiking, cooking, doing nothing. Previously at Riva Health, Viiv Labs, Solvvy, and Polycom. Over 20 years of software engineering experience. Most recently, led threat modeling and cybersecurity analysis of medical device to prepare for FDA approval. University of California, Berkeley. Previously at CapitalOne, evaluating LLMs for company-wide use. Working in the field of responsible AI since 2019, including building explainability solutions, establishing responsible AI processes, and publishing interdisciplinary research at venues like FAccT. Tries to spend at least one week a year walking in the mountains. UX/UI design and front-end developer, previously at bitlogic.io. Based in Cordoba, Argentina. Instituto Superior Politécnico de Córdoba. Previously at Amazon, Oracle, and Accenture. Working on AI/ML security engineering since 2019. Most recently, led red-teaming for Amazon AI models. Indiana University. Cloud infrastructure engineer. Most recently at MIST (acquired by Juniper), built the conversational interface to Marvis Virtual Network Assistant, designed to diagnose and resolve networking issues. University of Illinois at Urbana-Champaign. Previously at Microsoft. Research interest in trustworthy AI, ML for human safety, and autonomous vehicles. University of Michigan. Senior Applied Scientist. Previously at Lorica Cybersecurity, designed and deployed privacy-preserving machine learning products; expertise in the use of fully-homomorphic encryption and trusted execution environment for LLMs.  University of Toronto. At intersection of algorithmic fairness auditing and collective action. PhD UIUC, MS Harvard, BS Caltech. Previously at Goldman Sachs, with internships at Instacart and Snap. Previously postdoc in game theory and r

LLM Guard

Key Metrics
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Avg Rating
—
0
Mentions (30d)
0
—
GitHub Stars
—
—
GitHub Forks
—
—
npm Downloads/wk
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—
PyPI Downloads/mo
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Community Sentiment
How developers feel about each tool based on mentions and reviews

Vijil

0% positive100% neutral0% negative

LLM Guard

0% positive100% neutral0% negative
Pricing

Vijil

tiered

LLM Guard

Use Cases
When to use each tool

Vijil (2)

Enterprise-readyTrustworthiness
Features

Only in Vijil (8)

Tests your entire agent system (LLM, tools, MCP gateway, delegated agents)Generates custom tests based on YOUR users, policies, and workflowsRuns continuously—during development AND in productionDeploys on-premises to keep your prompts and data privateVIJIL DEPOTVIJIL DIAMONDVIJIL DOMEVIJIL DARWIN
Developer Ecosystem
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GitHub Repos
—
—
GitHub Followers
—
—
npm Packages
3
—
HuggingFace Models
29
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SO Reputation
—
Product Screenshots

Vijil

Vijil screenshot 1Vijil screenshot 2Vijil screenshot 3Vijil screenshot 4

LLM Guard

No screenshots

Company Intel
information technology & services
Industry
—
27
Employees
—
$23.0M
Funding
—
Series A
Stage
—
Supported Languages & Categories

Vijil

AI/MLDevOpsSecurityAnalyticsDeveloper Tools

LLM Guard

View Vijil Profile View LLM Guard Profile