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
Credal
Give every department their own AI agents connected to their knowledge, without ever losing visibility or control.
Coming from Dashworks? Import your data to Credal Join us for a hands-on agent building webinar in Credal on September 17th - register here! Give every department their own AI agents connected to their knowledge, without ever losing visibility or control. Set rules once, enforce everywhere. Define what each person can do, from building to invoking. Manage who can use, edit, and orchestrate each agent. Govern every action and integration your agents can reach. Full visibility into every agent action, with automated risk detection built in. Credal infrastructure is SOC 2 Type 2 compliant, tested and verified. Cloud and on-premise deployments supported. Credal inherits permissions across all connected source systems. When a user queries an agent, the response only pulls from sources that user has permission to access. Sync permissions from Google Drive, Slack, Confluence, SharePoint, Salesforce, and 50+ sources Automatically update permissions cache in real-time, synced with SSO Granular and configurable access controls, no data leakage across permission boundaries Build agents that reason across your data and take action in Salesforce, Jira, Slack, and every system your teams rely on. Every action or skill can be precisely scoped or given free reign. Build agents with permissioned access to data, context, tools, and MCP servers Connect agents to hundreds of approved actions across your tech stack Stitch together complex workflows with specialized agents that work collaboratively Read, write, and update across 50+ systems. Create tickets, update records, send messages, and more Enforceable human-in-the-loop approval, audit logging, and access controls on every action Add tools from third-party MCP servers with full Credal governance applied automatically See how AI agents get built to automate workflows using your company's own data and tools. Ravin from Credal.ai discussed the company s agent registry and Model Context Protocol (MCP) with representatives from Customer X, including Joe from the security team. The conversation covered Credal s capabilities around agent management, security, and integration with Customer X s existing systems, leading to an agreement to explore a proof-of-concept collaboration within the next couple of weeks, pending the signing of an NDA. From chat surfaces to workflow tools, Credal agents meet your teams where they already work, without adding extra platforms to manage. Deploy to chat interfaces like Claude, ChatGPT, Cursor, or any MCP-compatible surface, Slack or API Inherits enterprise context so tool calls are always accurate without redefinition Eliminate agent sprawl with one unified registry We are getting massive productivity ROI from Credal...I expected some usage from the agents, but I didn't expect to see people jump on it so quickly - even our non-technical teams have everything built on top of Credal. It's rare to find an AI tool that actually delivers immediate business impact,
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