Operant AI

?? Silicon Valley's Operant AI enters Indian market to secure AI systems in real-time. The cybersecurity AI startup is bringing its Runtime AI Application Defense Platform to safeguard AI systems from threats like prompt injection, rogue agents, and data poisoning. With AI adoption soaring in fintech, healthcare, and enterprise software, Operant AI aims to engage with industry leaders in Bengaluru, Pune, and Ahmedabad, while expanding recruitment in Hyderabad and Delhi. Read more: https://lnkd.in/dASbshi7 By Bhuvana Kamath #Cybersecurity #AI #OperantAI #TechSecurity #IndiaTech #AIInnovation

Big thanks to everyone who joined us for our AI & Security Leadership dinner in Pune! Another evening of fantastic conversations, with the added bonus of all three Operant founders coming together across the world in Priyanka's native city to share thoughts about the cutting edge of AI innovation from Silicon Valley to India. Cheers to continued conversations! Vrajesh B. Priyanka Tembey Ashley Roof Mooshir Vahanvati Nupoora Udas Saurabh Sule Nikhil Mittal Devawrat Bhave Bhavesh S. Swanand Kulkarni

Check out our CEO, Vrajesh on CNBC-TV18 Startup Street last night, discussing the groundbreaking capabilities we're bringing to AI Security! #CNBC #AI #Security

Silicon Valley-based Operant AI, a leading AI cybersecurity startup, has officially launched its operations in India to address the growing demand for real-time AI security solutions. Backed by $13.5 million in Series A funding from Felicis and SineWave Ventures, the company offers its cutting-edge 3D Runtime Defense Platform to protect AI systems from sophisticated cyber threats like prompt injection, rogue agents, and data exfiltration. Co-founded by Ashley Roof, Vrajesh B., and Priyanka Tembey, Operant AI aims to support India’s expanding AI ecosystem across sectors such as fintech, healthcare, and enterprise software. With a focus on major hubs like Bengaluru, Pune, Mumbai, Hyderabad, and Delhi-NCR, the company plans to establish strong local partnerships and ensure businesses stay secure while scaling AI applications. Their in-line auto-redaction feature further safeguards sensitive data, making compliance seamless for regulated industries. As part of its expansion, Operant AI is actively hiring AI security, cloud infrastructure, and GTM professionals to drive growth and innovation. By aligning with the ‘Make in India’ initiative, the company is committed to empowering Indian enterprises with AI-native security. Ready to join a cybersecurity revolution? Apply now and be a part of Operant AI’s journey to make AI safe and secure!

Human X? More like Human YES! ?? Agentic AI was the word on everyone's lips – the energy was absolutely contagious. It's crystal clear that #securing #AI is top of mind, and the discussions were seriously insightful (my brain is still buzzing!). Beyond the sessions, the real party was in the connections. Chatting with peers, swapping ideas, and getting the scoop on all the cool stuff happening in the industry was pure gold. Even got to hang with the masterminds behind Synthesia and ElevenLabs! I'm leaving with a sky-high level of optimism and a mile-long to-do list. The future is BRIGHT for AI, and I'm so pumped to be part of the ride. #HumanX #AgenticAI #AISecurity #TechNetworking #FutureIsBright #AIFun Thanks to all my new connections I know the world of #AI is a better place because of you all. Marianna Bonanome Matthew Gee Jo?o Gra?a Mani Iyer Victor Riparbelli Deanna Emeny ?? Stephan Kletzl Christian Pecora Joshua Geist Aaron McReynolds Justin E. Murphy Dan Zheng Tam Le Maddy Mullins James Eaton Joseph Yoo Alex Moore Carolin Steurer Dan Adamson Michelle Julia N. Quinn Favret Stephen Schmidt Operant AI Ashley Roof Vrajesh B. Priyanka Tembey @

Isn't it great when the conversation flows so fluidly that the time just disappears? Loved the conversations at our AI and Security Leadership Dinner in Bangalore last night, from securing AI from the cloud to the edge to the potential for AI to enhance human creativity, the perspectives shared by this group were so thought-provoking! Big thank you and shout out to everyone who braved Bangalore traffic in the first rainy day of an early monsoon to join us! Vrajesh B. Ashley Roof Devendra Durgapal Shubham Raj Nishit Desai Kishore Amarnath Shailesh Patel Ashin Uday #AISec #SecureAI #IndiaAI #IndiaCyber

Runtime AI Security is looking be a wild and confusing messaging ride, here's what to look for: Your AI architecture should determine the relevant solution to you, I actually don't like creating a generic category for this. At the end of the day, your "AI App" is either a library, container, cloud service, or API. Runtime security solutions in these categories can easily adapt to your AI needs. While I'm sure it won't stop the messaging emphasis on runtime AI security (because that's what people will look for), there's actually not a lot new that's happening here. Types of Runtime AI Security: 1. Network based solutions doing API Security, or that flavor of "ADR" - these solutions will be great at securing traffic either between pods or to external services. A technical gap here is doing in-line "firewalling" or redaction (like Operant AI) versus pure visibility like more companies will offer. 2. Library based ADRs - these will secure any local LLM libraries like Pytorch that you're running locally to spot malicious exploits against them. This is Raven.io, Oligo Security, and Miggo Security. 3. Agent CDRs - depending on their maturity, these solutions will also catch dataflows at the network level, and different types of exploits that are out there. There are too many in this category to tag them without getting yelled at so I'll link to the site- https://lnkd.in/e4UutXxZ. But the closer it gets to the application layer, the harder it will be to spot the exploit. 4. In line protection - Pillar Security has the most in depth application security potential because the defense mechanisms are in your code itself. Eventually RASP and other players could get into this territory, but the focus just isn't as clear as it is with Pillar. Finally, the "AI Security" vendors offer different ways of doing "AI Firewalling" with their own tradeoffs, the most common are: 1. API Wrapper in your code 2. Reverse Proxy to intercept network requests 3. Local library in-line of the requests. As far as "which is the best" - as always, it depends on your architecture! If you're using simple API integrations, network & container approaches are probably fine. If you're running complex libraries and dedicated workloads, an ADR or in-line approach is best.

We're thrilled to announce that Operant AI has just been named as vendor in Gartner's Market Guide for AI Trust, Risk, and Security Management (TRiSM). We are proud to be at the forefront of this evolving frontier, when it matters most to ensure that the systems we all rely on to be safe and secure are able to stay that way even as they take advantage of the many benefits that AI application development promises the world. Read more on our blog and Gartner's full report: https://lnkd.in/g36qxtpW #AISec #RuntimeAIDefense #3DRuntimeDefense #ResponsibleAI #CosAI #SecureAI #AISecurity #Cybersecurity

On Data Privacy Day 2025, our CTO Priyanka Tembey shared her thoughts with VMblog alongside other industry experts on how we can all flourish in the Age of AI while supporting critical data privacy requirements. "In-line auto-redaction of sensitive data represents a crucial evolution in how we approach data privacy in the age of AI - moving from reactive protection to proactive, automated safeguards that support innovation without sacrificing privacy." Read the whole article here: https://lnkd.in/esNsRQpd #Dataprivacy #AIsecurity #AISec #DataSec #Datagovernance

Organizations must establish who is responsible for AI’s behavior, whether that means bridging the gap between CISOs, CIOs, and CTOs or hiring an entirely AI-focused executive. By Operant AI CEO & Co-Founder Vrajesh B. | #GenAI #AIAgent #Data