Repello AI
AI red-teaming startup running continuous automated adversarial testing and runtime guardrails against generative AI applications.
Visit Website ↗ + Add to CompareOverview
Repello AI builds automated red-teaming and runtime protection tools purpose-built for generative AI applications. Its ARTEMIS platform continuously runs adversarial tests — the company says millions of them — across text, image, and audio inputs to find prompt-injection, jailbreak, and data-leakage vulnerabilities in an organization’s AI applications before attackers do, shifting LLM security testing from a one-time exercise to an ongoing process. A companion product, Repello Guard, adds runtime monitoring and guardrails that detect AI-specific threats in production, such as unsafe outputs, competitor mentions, and system prompt leaks.
Founded in 2024 by IIT Roorkee alumni Aryaman Behera and Naman Mishra, Repello AI operates out of Bengaluru, India, with a presence in San Francisco. The company raised $1.2 million in seed funding from Venture Highway, pi Ventures, Entrepreneur First, and angel investors including Charles Songhurst, positioning it as an early-stage entrant in the fast-growing AI red-teaming and AI security testing space.
AI red-teaming is becoming a crowded category as generative AI adoption accelerates and buyers from AI labs to enterprises look for ways to test model and application security before deployment. Repello AI’s differentiation is combining automated, continuous adversarial testing with a runtime guardrail product in one company, but as a year-old, seed-stage startup it has not yet published named enterprise customers or independent test results to substantiate its efficacy claims.
Innovation Matrix Assessment
Shipped both an automated red-teaming platform (ARTEMIS) and a separate runtime guardrail product (Repello Guard) within roughly a year of founding, a fast pace for a seed-stage team.
Provides both pre-deployment adversarial testing and production runtime monitoring for AI applications, a genuinely deployable two-sided approach, though as a very early product its maturity and breadth of coverage are unproven at scale.
Raised a modest $1.2 million seed round in 2024 from a credible but early-stage investor group; real but limited traction so far for a company under two years old.
Automating continuous adversarial testing of generative AI applications (versus one-time manual red-teaming) is a genuine shift in testing methodology, though it now competes with a rapidly growing field of similarly-positioned AI red-teaming startups.
No named enterprise customers, independent benchmark results, or third-party evaluations were found; the 'millions of automated adversarial tests' figure is a vendor claim.
As organizations rapidly deploy LLM-based applications, testing them for prompt injection, jailbreaks, and data leakage before and after deployment is an increasingly recognized and urgent need.
Why CISOs Should Care
Provides a way to continuously stress-test generative AI applications for prompt-injection and jailbreak vulnerabilities before and after deployment, rather than relying on a one-time manual red-team engagement.
What Makes It Different
Pairs automated, continuous adversarial testing (ARTEMIS) with a separate runtime guardrail product (Repello Guard), covering both pre-deployment testing and production monitoring under one vendor.
The Matrix Verdict
50/100 — INCREMENTAL INNOVATOR
A fast-moving, credibly-funded early-stage entrant in the crowded AI red-teaming space; promising direction but too new to have independently verified efficacy evidence.
Editorial Note: Claims vs. Verified Findings
The seed funding amount ($1.2M) and investor list are independently reported by SecurityWeek-adjacent outlets (BW Disrupt, Dealroom, Tracxn). The 'millions of automated adversarial tests' capability claim and specific product performance are vendor-sourced and not independently verified.
Sources
Alternatives to Repello AI
Adaptive Security
AI-driven platform that simulates deepfake, voice, and multichannel social-engineering attacks to train and test organizations against next-generation phishing.
Quilr
Early-stage agentic AI security startup building a 'Service-as-Software' platform to guard against human-related breaches and secure AI agent…
Zenity
Governance and security platform for AI agents and low-code/no-code development, securing agent identity, permissions and behavior across the…
Tenzai
An agentic AI penetration testing startup building autonomous 'AI hackers' to find and validate exploitable vulnerabilities at a…
Reco
Reco secures the "agentic ecosystem" — mapping what AI agents can access across SaaS and enterprise apps, detecting…
Charm Security
Agentic AI workforce that investigates and intervenes on scams and fraud in real time, reading manipulation and intent…