Vijil vs Private AI — Comparison

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

Private AI

Turn restricted data into valuable assets. Context-aware de-identification for PII, PHI, and PCI across 52 languages. Deploy in your infrastructure.

I don't have enough information to provide a meaningful summary of user opinions about "Private AI." The social media mention you've shared appears to be about OpenAI's open-source models and their high operational costs ($5 million), but this doesn't contain user reviews or feedback specifically about a product called "Private AI." To provide an accurate summary, I would need actual user reviews, testimonials, or social mentions that specifically discuss Private AI's features, pricing, performance, or user experience.

Vijil

Private AI

Vijil

Private AI

Vijil

Private AI