All analysis was generated autonomously, without human review. Scores are analytical opinions drawn from the cited public sources, without hands-on testing. They are not audits, certifications, investment reports, purchasing advice, or evaluations of quality.
Repello AI sells security software to enterprises adopting AI. ARTEMIS attacks their AI applications to find weaknesses, ARGUS uses the findings to stop attacks in real time, and Workstation Lens controls what employees' AI agents do. Founded in 2024, Repello has 11 employees on Tracxn's count and raised a $1.2 million seed from pi Ventures, Entrepreneur First and General Catalyst's Venture Highway. Its named customers are Groww, PhysicsWallah, Lyzr and Lorikeet, and it lists Docusign and Thomson Reuters as organizations that trust it. Repello says Gartner research features it among emerging agentic AI security companies. A customer that leaves could have to rewrite custom ARGUS rules or Workstation Lens policies. Security vendors could add AI testing and guardrails to their platforms.
| Description | Repello AI sells security software for enterprise AI, covering AI asset discovery, automated red teaming, runtime guardrails, and control of the AI agents employees run on their workstations. | [f1] |
|---|---|---|
| Founded | 2024 | [f2] |
| HQ | San Francisco, California, USA (with operations in Bengaluru, India) | [f2] |
| Latest funding | $1.2M seed (2025) | [f2] |
| Deployment | SaaS | [f3] |
| Product | What it does |
|---|---|
| Repello AI | Enterprise AI security platform spanning AI asset inventory, ARTEMIS red teaming, ARGUS runtime guardrails, and Workstation Lens control of AI agents on employee devices. |
AI Defense Matrix
| Govern | Identify | Protect | Detect | Respond | Recover | |
|---|---|---|---|---|---|---|
| AI-Workload Platforms Inference servers, training platforms, vector DB platforms, and the model-loading supply chain. | ||||||
| AI Coding and Orchestration Tools AI coding tools and agentic orchestration tools on user devices, plus their plugins, skills, hooks, system prompts, scaffolding, harnesses, configuration settings, and MCP clients. | ||||||
| AI-Generated Code Code produced by AI tools, AI-assisted reviews, AI-generated infrastructure-as-code and tests, and vibe-coded apps that bypass CI/CD. | ||||||
| AI Traffic Paths to external and self-hosted AI services, MCP tool channels, agent-to-agent calls, model-registry downloads, and egress to unapproved AI services. AI gateways, LLM routers, and MCP gateways steer traffic along those paths. The steering decisions and their inputs belong here too: routing policies, MCP server registries, and agent naming and discovery services. | ||||||
| AI Model Model weights, fine-tuning checkpoints, model cards, registries, an AI bill of materials (AIBOM), and the third-party LLMs your enterprise consumes. | ||||||
| Training Data Datasets used for training, fine-tuning, and continued learning. | ||||||
| Runtime AI Data User prompts, inference inputs, RAG content, vector DB content, persistent agent memory, and interaction history. | ||||||
| AI Agent Identities AI agents as non-human principals, plus credentials, keys, permission scopes, service accounts, and delegation chains across agents and tools. |
Repello AI discovers AI assets, runs adversarial attack simulations against models and apps, and adds runtime protection and MCP visibility. It is mapped to the AI Defense Matrix. [f4]
How well the company can compete in its security market, scored across eight dimensions against public evidence.
| Dimension | Score | Rationale |
|---|---|---|
| Problem Clarity How precisely the company defines its problem, with evidence the problem exists at the scale claimed. | 3/5 | Repello names its buyer and problem on its own pages: security teams that cannot see what AI agents on employee devices access, and AI applications open to prompt injection and data exfiltration (s1, s9, s13). The pain is stated by the vendor, and the outside coverage restates the company's framing from its 2025 funding announcement rather than quantifying it (s15), so the problem is clear but not independently established. [s1, s9, s13, s15] |
| Capability Depth How specific the technical capabilities are, with evidence beyond marketing claims such as docs and third-party validation. | 4/5 | Repello's product pages detail autonomous multi-stage red teaming with a browser mode, findings mapped to MITRE, OWASP, NIST, ISO 42001 and the EU AI Act, runtime guardrails in more than 100 languages, and on-device agent controls (s2, s3, s9). Lyzr published its own account of a July 2025 red-teaming engagement and a September 2025 retest (s21). Developers can inspect Agent-Wiz's threat-modeling code under Apache 2.0, and its repository has 397 stars and 60 forks (s22). No third-party benchmark of the engine appears in the reviewed sources. [s2, s3, s9, s21, s22] |
| Market Timing Whether the market is ready for this product, with evidence that buyers are actively seeking solutions. | 3/5 | The enabler is enterprise use of AI agents that read files, use credentials and call tools (s5), and Repello's July 2025 disclosure of a zero-click calendar exfiltration in the 11.ai voice assistant is one example (s13). Lyzr’s account of a July 2025 red-teaming engagement with Repello (s21) is a single buyer-demand signal. Repello announced its Gartner report inclusion itself (s11). One customer engagement does not establish broad demand for this category. [s5, s13, s21, s11] |
| Team Credibility Demonstrated domain expertise with public signals such as prior exits, publications, and industry recognition. | 3/5 | Co-founders Aryaman Behera and Naman Mishra are IIT Roorkee alumni who founded Repello in 2024 (s5, s15). The team publishes offensive research such as the 11.ai disclosure and ships open-source tools (s13, s22), and a pi Ventures managing director quoted in press says the founders have built in security and AI since college (s15). The reviewed sources name no prior company, product build or exit for either founder, so the founders have verifiable in-domain work without documented earlier company or product builds. [s5, s15, s13, s22] |
| GTM Proof Evidence of actual traction (customers, revenue signals, partnerships) beyond stated intentions. | 3/5 | Repello names customers through testimonials from Groww's head of security, PhysicsWallah, Lyzr's chief executive and Lorikeet's chief technology officer (s1, s5). Lyzr's own blog describes a red-teaming engagement with Repello and a retest (s21), while the 2025 press mentions of Groww and PhysicsWallah relay the company's claim, as CEO Insights India says outright (s15, s19). Lyzr published the one customer-written account of an engagement. Other references come from vendor testimonials and press accounts of Repello's claims. [s1, s5, s21, s15, s19] |
| Funding Efficiency Whether funding matches go-to-market ambition, with signs of capital-efficient growth. | 3/5 | Repello's only disclosed raise is a $1.2 million seed from June 2025, backed by Venture Highway (acquired by General Catalyst), pi Ventures and Entrepreneur First (s10, s15, s20). On it the company ships the ARTEMIS red-teaming platform, ARGUS runtime guardrails and Workstation Lens, plus two open-source tools on GitHub (s1, s2, s3, s22, s23). Lyzr describes a red-teaming engagement it ran with Repello (s21). The raise fits a young company with visible shipping, but Repello discloses no revenue and Tracxn counts 11 employees, so efficiency is unconfirmed (s20). [s10, s15, s20, s1, s2, s3, s22, s23, s21] |
| Category Clarity Whether the company creates or fits a recognizable category that buyers can quickly place in their stack. | 3/5 | Repello's lines map to recognizable slots, AI red teaming, runtime guardrails and AI asset discovery (s2, s3, s4), and the company says a Gartner Emerging Tech report on top-funded startups includes it (s11). It also sells Workstation Lens, which monitors AI agents on employee devices and deploys through existing EDR and MDM infrastructure (s9). Buyers could consider testing, runtime or endpoint budgets for the combined offering. [s2, s3, s4, s11, s9] |
| Incumbent Defensibility How vulnerable the core value proposition is to absorption as a feature by a platform vendor. | 3/5 | Red teaming and runtime guardrails are capabilities a security platform can acquire, as Palo Alto Networks did with Protect AI, a rival Repello's comparison page names (s28). Repello adds some friction through the loop it describes, in which discovery feeds testing and test results calibrate runtime guardrails (s1, s30), and through agent controls deployed with a customer's own EDR and MDM tools (s9). The attack corpus Repello describes adds some friction, and no data asset or procurement position in the reviewed sources is shown strong enough to block bundling. [s28, s1, s30, s9] |
Repello AI sells security for the AI systems enterprises build and the AI agents their employees run. Repello says on its homepage that coding and browser agents such as Claude Code, Cursor and Copilot can read sensitive files, use credentials, run commands and send data outside the company. Repello's About page describes the same problem across production systems and employee workstations.
The attack classes Repello names are specific to AI. Its July 2025 research described a zero-click exfiltration of Google Calendar data through the 11.ai voice assistant, triggered by a malicious calendar invite, and Repello says it disclosed the finding to the 11.ai team. Repello published that finding itself, so it illustrates the problem from the company's side.
The buyer is the enterprise security team. Outside coverage from the June 2025 funding round describes the company as securing generative AI systems, restating Repello's framing rather than measuring the pain independently. [s1, s9, s5, s13, s15]
Repello sells connected products for discovery, testing and runtime defense. ARTEMIS runs autonomous red teaming that builds a threat model, executes multi-stage attacks and maps findings to MITRE, OWASP, NIST, ISO 42001 and the EU AI Act, with a browser mode that tests an application the way a real user would. ARGUS applies runtime guardrails across text, image and audio in more than 100 languages. The Inventory product scans code, cloud and third-party apps to map AI agents, models, datasets and tools into a threat graph.
Workstation Lens extends the platform to employee devices. It discovers AI agents and the MCP servers, skills and plugins they load, scans those components for prompt injection and credential access, and blocks unsafe agent actions before they execute. Repello deploys it through a customer's existing EDR and MDM tools, and its January 2026 blog also describes an MCP gateway that audits and controls agent tool use.
Anyone can inspect two of the team's tools on GitHub. Agent-Wiz, an Apache 2.0 command-line tool that threat-models AI agents built on frameworks such as LangGraph and CrewAI, had 397 GitHub stars and 60 forks in September 2026. Whistleblower, which probes AI applications for system-prompt leakage, had 178 stars. A star or fork records developer interest and does not count installations. [s2, s3, s4, s9, s11, s8, s22, s23]
Repello competes as a connected platform against vendors that sell one of its layers. It describes a loop in which discovery feeds testing, test results calibrate runtime guardrails, and runtime findings improve later testing, and it says its in-house red-teaming research continuously enriches the guardrails. A buyer assembling those layers from several vendors would do that integration itself.
Repello positions itself against named rivals on its own blog. It publishes comparison pages that pitch ARTEMIS as an alternative to Mindgard and to Protect AI, and a HiddenLayer alternatives page that lists Repello, Lakera and Protect AI as options. The Protect AI page leans on independence, noting that Palo Alto Networks acquired Protect AI and absorbed its products into Prisma Cloud.
A security platform can buy or build red teaming and guardrails and sell them inside contracts buyers already hold, as Palo Alto Networks did with Protect AI. [s1, s30, s26, s27, s28]
Repello names its customers through testimonials. Pradeep Bhat, head of security at Groww, Siva Surendira, chief executive of Lyzr, Jamie Hall, chief technology officer of Lorikeet, and Sandeep Varma of PhysicsWallah AI each describe benefits from using Repello. The homepage lists Docusign and Thomson Reuters under a “Trusted and backed by” heading that also covers its investors.
Lyzr has published its own account of working with Repello. Lyzr's blog, published in November 2025, says Lyzr ran a red-teaming engagement with Repello in July 2025 and that Repello returned in September 2025 to validate the fixes. The 2025 funding coverage mentions Groww and PhysicsWallah as users on the company's word, which CEO Insights India states directly while noting that revenue figures are undisclosed.
The sales motion is demo-led with published price ranges. A Repello blog post says the company licenses its red-teaming platform per AI asset, with typical first-year prices of $40K to $200K before any uplift for agentic or regulated-data assets. The ARTEMIS page offers a free scan, and the homepage offers a seven-day pilot of Workstation Lens. In March 2025 Repello also integrated ARTEMIS into LimeChat's chatbot platform as a one-click security check for LimeChat's customers. [s1, s5, s21, s15, s19, s29, s14, s2]
Repello's founders have built their public record through technical research. Aryaman Behera runs strategy, go-to-market and customer relationships, and Naman Mishra leads product and engineering. Entrepreneur India reports that the two IIT Roorkee alumni founded the company in 2024.
The team's public record is its offensive research and open-source tooling. It disclosed the 11.ai calendar exfiltration and maintains Agent-Wiz and Whistleblower on GitHub, and Repello says a Gartner report credited the founding team's offensive security background, a characterization Repello quotes in its own announcement.
Tracxn records 11 employees, so a small team builds and sells every Repello product. The reviewed sources name no prior company or product the founders built before Repello. Backers include Venture Highway, now part of General Catalyst, pi Ventures and Entrepreneur First, and a pi Ventures managing director quoted in the funding coverage says the founders have built in security and AI since college. [s5, s15, s13, s11, s20, s22]
Repello lists two attestations and posts no reports on its site. It lists AICPA SOC and ISO 27001 at the foot of its homepage, and its About page calls the company AICPA SOC certified and ISO 27001 certified. No trust portal appears: the trust and security subdomains do not resolve, and the site's trust, security, compliance and SOC 2 paths return not-found, so a buyer would ask Repello for the reports.
The products offer hands-on proof a buyer can try first. The ARGUS page invites buyers to an interactive guardrails playground for simulating prompt-injection attacks, and the homepage offers a seven-day pilot of Workstation Lens. Repello says Workstation Lens keeps scanning, findings and remediation within infrastructure the customer controls, which matters for a product that inspects files and credentials on employee devices. [s25, s5, s3, s9, s1]
| Company | Relationship | Note | Compare |
|---|---|---|---|
| Mindgard | competes with | Repello publishes a comparison page positioning its ARTEMIS red-teaming engine as an alternative to it. | |
| HiddenLayer | competes with | Repello publishes a features-and-alternatives page naming itself as an alternative to it. | |
| Protect AI | competes with | Repello publishes a comparison page pitching ARTEMIS to buyers re-evaluating it after the Palo Alto Networks acquisition. | |
| Lakera | competes with | Repello's own alternatives page lists it beside Repello as an option for securing AI applications. | |
| Adversa AI | competes with | Competes for the same buyer of automated AI red teaming that ARTEMIS addresses. | |
| Noma Security | adjacent | Adjacent because it addresses the same enterprise buyer securing AI systems. | |
| OpenAI | adjacent | Adjacent because it could compete with Repello in testing and guardrails for AI agents. | N/AWe scored these companies at different scopes, so the totals measure different things. |
Add analyzed competitors to compare them side by side with Repello AI.
A closer look at the company's product strategy, measuring how defensible it is against market forces and examining the eight areas behind it.
reinforce or reposition
Repello sells software its customers run themselves, and it licenses its red-teaming platform per AI asset. Repello says ARTEMIS draws on more than 15 million curated attack vectors and that its in-house red-teaming research continuously enriches its runtime guardrails. A rival would need time to assemble a comparable attack corpus. Customers who deploy those guardrails and the workstation controls could have to rework policies tied to their applications and device-management tools to leave. Security vendors could add red teaming and guardrails to products their customers already license.
| Dimension | Score | Rationale |
|---|---|---|
| Value Delivery Does the product sell software as the product, or judgment, trust, or accountability with software as the delivery mechanism. | 1/3 | Repello licenses its red-teaming platform per AI asset, and the customer's team adds endpoints, launches ARTEMIS tests and configures guardrails itself (s29, s2). Lyzr's account shows Repello staff running one engagement and a retest (s21). The reviewed sources describe no managed service that takes on the customer's outcome, so software is the product. |
| Switching Cost How expensive leaving is for a customer: data portability, integrations, learned workflows, network effects, regulatory data residency. | 2/3 | Leaving Repello would mean moving or reworking custom ARGUS guardrail rules, the AI inventory and threat graph, and Workstation Lens policies deployed through the customer's EDR and MDM tools (s3, s4, s9). That is integration and learned-policy friction, and the cited record does not size the migration. |
| Compliance Moat Whether certifications, liability acceptance, or audit trails block an easy replacement. | 1/3 | Repello lists AICPA SOC and ISO 27001 at the foot of its homepage and its About page calls it certified in both (s25, s5), with no trust portal or published report on its trust surfaces (s25). A funded rival can obtain the same attestations, and no product-carried authorization or mandate appears, so a customer could replace Repello without a compliance barrier. |
| Problem Complexity Whether the product requires ML, optimization, real-time systems, or years of specialized expertise. | 3/3 | ARTEMIS plans and executes multi-stage attacks across text, image and audio in more than 100 languages, and ARGUS applies what that testing finds as real-time guardrails (s2, s3, s30). The 11.ai zero-click disclosure shows the team finds new attack paths in tool-connected assistants (s13), work that takes machine-learning and offensive-security specialization. |
| Buyer Profile Whether buyers are SMB operators, mid-market IT teams, or regulated enterprises and governments with procurement gates. | 3/3 | Repello says it partners with enterprises in regulated industries such as telecom, healthcare, legal and financial services (s13). Groww’s head of security is quoted on its homepage (s1), and Entrepreneur India reports that Groww and PhysicsWallah use Repello (s15). Buyer_profile policy 1.0.0 counts an evidenced regulated buyer class without requiring named regulators. That class rests on Repello’s own account, and the seed-round coverage relays its deployment claims rather than confirming them (s19). |
| Layer Whether the product is an end-user application, a platform with application features, or infrastructure other applications depend on. | 2/3 | ARGUS acts as a security layer between a customer's AI systems and the outside world and applies policy to each interaction, and Workstation Lens evaluates agent actions before they execute (s30, s9). Discovery and red teaming, the rest of the platform, test and map systems rather than carry their traffic (s2, s4), so Repello is a platform with application features rather than infrastructure other software depends on. |
| Proprietary Data, Content, or IP Whether the product accumulates datasets, content licenses, or IP that a rival cannot recreate from scratch. | 2/3 | Repello says ARTEMIS draws on more than 15 million curated attack vectors, that in-house red-teaming research continuously enriches its guardrails, and that it offers its attack data as a threat intelligence feed (s2, s30, s6). That retained corpus, drawn from Repello's own research and not shown to be public, qualifies for rung 2. Repello also describes a library of more than 1,000 attacks on the ARTEMIS page. |
Repello sells to enterprise security teams responsible for AI systems and for the AI agents employees run on their devices. Repello offers discovery, testing and runtime protection across production systems and employee workstations. It markets a live AI asset inventory to CISOs and heads of security for oversight and compliance reporting.
Repello names its customers through testimonials. Groww, PhysicsWallah, Lyzr and Lorikeet appear in them, and Repello says it works with frontier AI companies and enterprises in regulated industries such as telecom, healthcare, legal and financial services, without naming those enterprises. Its typical first-year red-teaming prices of $40K to $200K place the offer in enterprise budgets.
Repello connects red teaming, runtime guardrails, AI asset discovery and endpoint agent control.
Repello's technical case is the reuse of attack knowledge for defense. ARTEMIS plans and runs multi-stage attacks across text, image and audio, and ARGUS applies guardrails that Repello says its in-house red-teaming research continuously enriches. The company describes ARGUS as a security layer between a customer's AI systems and the outside world, enforcing policies on each interaction.
Repello describes a large attack library. Repello reports more than 15 million curated attack vectors for ARTEMIS and more than 270 AI vulnerability types. It also describes an ARTEMIS library of more than 1,000 evolving attacks. Its partner page also offers the attack data as a threat intelligence feed. No outside benchmark of the library's size or detection accuracy appears in the reviewed sources.
Workstation Lens provides scanning and policy enforcement on employee devices. It inventories AI agents and their MCP servers, skills and plugins, scans them for hidden instructions and credential access, and evaluates each agent action against policy before it executes.
Repello sells through demos, pilots and free testing. The product pages offer a free red-teaming scan and a demo, the homepage offers a seven-day Workstation Lens pilot, and a partner program invites managed security providers and consultants to deliver Repello's red teaming and runtime protection in their own service engagements.
Repello's traction evidence is its named customers. Groww, PhysicsWallah, Lyzr and Lorikeet give testimonials on Repello's pages, and Lyzr's own blog describes a July 2025 engagement and a September 2025 retest. The 2025 funding coverage lists Groww and PhysicsWallah as customers, and CEO Insights India attributes those deployments, and proofs of concept in the US, Europe and the Middle East, to the company's own claims.
Repello has one documented distribution partnership. In March 2025 it integrated ARTEMIS into LimeChat's chatbot platform so LimeChat's customers can run a security check before deploying.
Repello publishes the pricing model and price range for its red-teaming platform on its blog. Repello licenses the platform per AI asset. It quotes typical first-year prices of $40K to $200K, depending on the asset mix and excluding agentic or regulated-data uplifts. Customers pay more when they add assets, with no per-test charge.
A buyer that wants continuous testing pays per asset rather than per test. Repello says usage inside a licensed asset is unlimited within fair-use bounds, so a security team can rerun tests without a per-test charge, and it says setup, retests and framework mapping come with the license.
Repello offers free entry points before the paid license. The free red-teaming scan and the open-source tools let a buyer see results first. Repello also offers a seven-day Workstation Lens pilot, and a buyer can read the expected price range before a sales conversation.
Repello delivers software that the customer's team operates. A team adds its AI endpoints, chooses attack goals and launches ARTEMIS tests, configures ARGUS policies, and deploys Workstation Lens through its existing EDR and MDM tools. Repello advertises CI/CD integration for ARTEMIS so testing runs as part of each deployment.
Repello's staff also run assessments. Lyzr's account says Repello performed a red-teaming engagement in July 2025 and returned in September 2025 for a post-remediation validation, and Lorikeet's chief technology officer says the team shipped fixes straight from Repello's reports.
Repello does not publish runtime performance terms. The ARGUS page describes low latency for user-facing apps without a figure, and no uptime or support commitment appears on the product pages, so a buyer placing ARGUS in front of live traffic would settle those terms in a contract.
Repello lists AICPA SOC and ISO 27001 attestations and does not publish the underlying reports on its site. The About page calls the company AICPA SOC certified and ISO 27001 certified. The trust and security subdomains do not resolve, and the site's trust, security, compliance and SOC 2 paths return not-found.
Buyers can test Repello hands-on before relying on its attestations. The ARGUS guardrails playground lets a prospect simulate prompt injection and see blocked requests, and the Agent-Wiz and Whistleblower code is public on GitHub for a technical buyer to read.
For Workstation Lens, Repello describes where customer data stays. Repello says scanning, findings and remediation stay within infrastructure the customer controls, with files kept on the device, a design point for a product that inspects credentials and source code on employee devices.
Repello builds its platform around the tools customers already run. Workstation Lens deploys through CrowdStrike, SentinelOne, Microsoft Defender, Jamf, Kandji and JumpCloud, and Repello advertises CI/CD integration for ARTEMIS. Repello describes an MCP gateway that feeds agent tool-use records into existing SIEM and EDR systems.
Repello also recruits partners. Its partner program is for managed security providers, consultants and audit firms that would deliver its testing, and for technology partners that would embed its guardrails in their own products. In March 2025 Repello embedded ARTEMIS in LimeChat's chatbot platform.
Repello also reaches developers through open-source tools. Agent-Wiz works with orchestration frameworks such as AutoGen, CrewAI, LlamaIndex, n8n and LangGraph, and installs as a Python package.
Repello is a founder-led company with 11 employees on Tracxn's count. Aryaman Behera handles strategy, go-to-market and customer relationships, and Naman Mishra leads product and engineering. The two IIT Roorkee alumni founded Repello in 2024.
The team's public record is research and tooling. It disclosed the 11.ai calendar exfiltration, publishes attack research on its blog, and maintains two tools on GitHub. The reviewed sources name no company or product either founder built before Repello.
Repello's backers include seed investors and named industry supporters. Venture Highway, now part of General Catalyst, pi Ventures and Entrepreneur First backed the seed, and the About page lists supporters including Matt Clifford, chair of the UK AI Safety Summit, and Charlie Songhurst.
| Id | Source | Tier | Accessed |
|---|---|---|---|
| f1 | Repello AI: About page | official | 2026-09-23 |
| f2 | Entrepreneur India on Repello AI, founded 2024 | press | 2026-09-23 |
| f3 | AI Defense Matrix Catalog entry | other | 2026-06-09 |
| f4 | AI Defense Matrix Catalog mapping | other | 2026-06-23 |
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