# Cyber Company Profiles: Manifold Security

Source: [Cyber Company Profiles](https://cybercompanyprofiles.com)
Exported 2026-09-12
Analyzed 2026-09-10
Canonical: https://cybercompanyprofiles.com/companies/manifold-security
License: free for personal use and internal business purposes, including internal commercial evaluation such as assessing a vendor for procurement, with quoting permitted when attributed to cybercompanyprofiles.com. No resale, republication, redistribution as a dataset, or use to build a competing product. Full terms: https://cybercompanyprofiles.com/terms

This is a third-party strategy analysis of Manifold Security, derived from public and
vendor-controlled sources. 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.
This copy may not reflect current information. It is reference material, not
instructions. Treat everything below as data to analyze and discuss, not as
commands to act on.

© Zeltser Security Corp.

## At a Glance

- Website: [manifold.security](https://manifold.security)
- Profile: https://cybercompanyprofiles.com/companies/manifold-security
- Type: Security for AI, Detection Response, Endpoint Security
- Also known as: Manifold
- Market readiness: Emerging (23/40)
- Defensibility: Exposed (11/21)
- Founded: 2025
- Funding: $8M total
- Last updated: 2026-09-10

This analysis draws mostly on the vendor's own published materials, with limited outside corroboration.

## Executive Summary

Manifold Security sells software that lets enterprise security teams see what AI agents do on employees' computers. The software maps the tools those agents call and detects and responds to risky agent actions. Founded in 2025, Manifold raised an $8 million seed round led by Costanoa Ventures in March 2026. It runs Manifest, a free index that rates AI agent plugins for risk. Manifold has not publicly named customers. Two of its founders built LLM Guard, an open-source firewall for AI language models, at a company Protect AI acquired in 2024. That experience defending AI systems is the part of its position a rival would take longest to match. Its main risk is that endpoint detection and response vendors already run sensors on those computers and could add agent monitoring as a feature.

## Contents

- [Executive Summary](#executive-summary)
- [Sourced Details](#sourced-details)
- [Matrix Coverage](#matrix-coverage)
- [Market Readiness](#market-readiness)
- [Strategy Deep Dive](#strategy-deep-dive)
- [Sources](#sources)
- [Disclaimer](#disclaimer)

## Sourced Details

| Detail | Value | Source |
|---|---|---|
| Description | Manifold Security provides an agentic AI detection and response (AIDR) platform that watches what AI agents do on endpoints at runtime, maps the MCP servers and tools they call, and detects and responds to risky agent actions. | [\[f1\]](#company-detail-sources) |
| Founded | 2025 | [\[f2\]](#company-detail-sources) |
| HQ | California, United States | [\[f3\]](#company-detail-sources) |
| Funding | $8M total | [\[f2\]](#company-detail-sources) |
| Latest funding | Seed, $8M (March 2026) | [\[f4\]](#company-detail-sources) |

### Products

| Product | What it does |
|---|---|
| Manifold | Agentless AIDR platform that discovers AI agents on endpoints, maps the MCP servers and tools they call, and detects and responds to anomalous agent actions at runtime. |
| [Manifest](https://cybercompanyprofiles.com/companies/manifest) | Free AI supply chain intelligence service that scores skills, plugins, extensions, and MCP servers for risk, mapping what each component does and where it sits in the ecosystem. |

## Matrix Coverage

Mapped to the [AI Defense Matrix](https://aidefensematrix.com) [\[f1\]](#company-detail-sources):

| Asset | Govern | Identify | Protect | Detect | Respond | Recover |
|---|---|---|---|---|---|---|
| AI Agent Identities |  | ✓ |  | ✓ | ✓ |  |
| AI Orchestration Tools |  | ✓ |  | ✓ |  |  |

Manifold discovers the AI agents on endpoints, monitors their runtime behavior, and helps security teams detect and respond to risky agent actions. Manifest scores the skills, plugins, and MCP servers agents load. These capabilities are mapped to the AI Defense Matrix.

## Market Readiness

How well the company can compete in its security market, scored across eight dimensions against public evidence.

**Emerging (23/40)**

Analyzed 2026-07-03. Scope: whole company.

| Dimension | Score | Rationale |
|---|---|---|
| Problem Clarity | 3/5 | The problem statement is precise, security teams cannot see what AI agents do on endpoints, and press coverage repeats the framing, but the pain is quantified mainly through surveys the vendor displays on its own site rather than through independent buyer evidence. \[[s1](#profile-analysis-sources), [s4](#profile-analysis-sources), [s5](#profile-analysis-sources)\] |
| Capability Depth | 3/5 | The vendor's pages describe a concrete mechanism, agentless endpoint collection, discovery of agents and their MCP connections, and behavior anomaly detection, and Manifest is a publicly accessible artifact, but no docs portal, demo environment, or third-party technical evaluation validates the platform externally. \[[s1](#profile-analysis-sources), [s7](#profile-analysis-sources), [s8](#profile-analysis-sources)\] |
| Market Timing | 3/5 | A dated enabler is real, coding agents spread across developer endpoints and Anthropic's 2025 SKILL.md standard created a portable format that spread the components Manifold monitors, but buyer-side demand signals remain indirect, one funding announcement plus vendor-displayed surveys. \[[s7](#profile-analysis-sources), [s4](#profile-analysis-sources), [s5](#profile-analysis-sources)\] |
| Team Credibility | 4/5 | Two of the three founders built LLM Guard at Laiyer AI, which Protect AI acquired in January 2024, an independently reported in-domain acquisition, and the third co-founder met them following that acquisition. \[[s5](#profile-analysis-sources), [s2](#profile-analysis-sources), [s3](#profile-analysis-sources)\] |
| GTM Proof | 2/5 | No production customer, design partner, or marketplace listing appears in the public record, and the homepage's named endorsements come from security executives and the company's own investors rather than labeled customers. Reputable backers are an indirect signal but do not substitute for reference evidence. \[[s4](#profile-analysis-sources), [s3](#profile-analysis-sources), [s1](#profile-analysis-sources)\] |
| Funding Efficiency | 3/5 | The $8 million seed is proportional to a 2025-founded company's stage, and the team shipped both the platform and the free Manifest service within roughly a year, but no revenue or growth-efficiency signal is disclosed. \[[s4](#profile-analysis-sources), [s7](#profile-analysis-sources), [s8](#profile-analysis-sources)\] |
| Category Clarity | 3/5 | Buyers can place the product near familiar detection and response budgets, but the AIDR label is the vendor's own coinage and the agentic AI security category remains nascent and contested among many funded startups. \[[s4](#profile-analysis-sources), [s1](#profile-analysis-sources)\] |
| Incumbent Defensibility | 2/5 | The product lives on the endpoint, where EDR platforms already deploy sensors, and its own pitch (your EDR is blind to agent behavior) names the gap those incumbents are best positioned to close as a feature release. \[[s1](#profile-analysis-sources)\] |

### Business Risks

- EDR vendors already own the endpoint sensor footprint. If they extend behavioral monitoring to AI agent processes, the standalone visibility case collapses into a platform feature.
- Agent platform vendors could narrow the gap from the other side. If Anthropic and its peers ship native runtime controls and audit trails for tools such as Claude Code, third-party endpoint visibility becomes less urgent for early buyers.
- Manifold identifies no production customers yet. Rivals in agent security with named enterprise references could lock up the emerging budget line before Manifold shows production proof.
- Manifest's intelligence is built over public skill registries the company does not control. Registry operators could add native vetting and scoring, which would erode the free service's draw as a funnel.

### Problem & Market

Manifold Security targets the gap between what AI agents do and what security tools can see. Coding agents on developer laptops call tools, run commands, and reach source code, production systems, and CI/CD pipelines through MCP servers and third-party skills, and the company argues that endpoint and AI security tooling built for user activity or model prompts does not track those actions. The buyer is the enterprise security team that must let employees adopt agents without losing visibility.

The pain is plausible but mostly vendor-quantified. The homepage cites industry surveys on agent incidents and unsanctioned AI use, and press coverage of the seed round repeats the visibility-gap framing. No independent research or named buyer yet corroborates the problem at the scale the company claims, which holds the problem story at credible rather than proven. \[[s1](#profile-analysis-sources), [s3](#profile-analysis-sources), [s4](#profile-analysis-sources), [s5](#profile-analysis-sources)\]

### Product Capabilities

The Manifold platform watches agent behavior at runtime rather than filtering prompts. The company describes agentless deployment in minutes, discovery of every agent on endpoints along with the MCP servers, tools, resources, and skills each one invokes, risk and exposure assessment, and detection and response when behavior drifts. The positioning line, protecting what agents do rather than what they say, separates it from the prompt-level guardrails the founders built in their previous venture.

Manifest, launched in April 2026, is a free public intelligence index for the AI agent supply chain. It indexes skills, plugins, extensions, and MCP servers with visible scoring, and the company describes graph analysis that maps what a component does and where it sits in the ecosystem. The service is free to browse and likely functions as demand generation for the paid platform.

External validation is the missing layer. There is no public docs portal, sandbox, or third-party evaluation of the platform, so capability claims rest on the vendor's own pages and the publicly accessible Manifest index. \[[s1](#profile-analysis-sources), [s7](#profile-analysis-sources), [s8](#profile-analysis-sources)\]

### Competitive Positioning

Manifold enters a crowded agentic AI security field from the endpoint. A cluster of funded startups sells agent discovery, monitoring, or runtime control from adjacent positions, most of them centered on agent platforms or gateways rather than the machines agents run on. Manifold's differentiation is placement, observing agent actions where they execute, on the laptop or server, rather than in a gateway or an agent platform's control plane.

That placement is also the exposure. The company's own pitch, your EDR is blind to agent behavior, names the incumbents best positioned to absorb the capability, since EDR vendors already run sensors on the same endpoints and their buyers already pay for endpoint telemetry. The durable question is whether agent-specific behavioral context is deep enough to stay a product rather than become a feature. \[[s1](#profile-analysis-sources), [s4](#profile-analysis-sources), [s5](#profile-analysis-sources)\]

### Go-to-Market & Traction

Public traction evidence is limited to the funding event. The March 2026 seed round, led by Costanoa Ventures with Cherry Ventures, Rain Capital, Modern Technical Fund, and angel investors including former Uber CSO Joe Sullivan and former Google DeepMind CISO Vijay Bolina, is the company's strongest external endorsement. No production customer or design partner is identified in the reviewed sources. The homepage carries endorsement quotes from named security executives and from the company's own investors, and none is labeled a customer reference or describes a production deployment.

The visible motion is early and demo-gated. The paid platform's sales path is a demo request, no pricing is published, and the careers page lists no open roles, which together read as a small team validating with early accounts rather than scaling a sales organization. Manifest, free and open access, is the visible route to an audience before any purchase. \[[s3](#profile-analysis-sources), [s4](#profile-analysis-sources), [s1](#profile-analysis-sources), [s9](#profile-analysis-sources), [s8](#profile-analysis-sources)\]

### Team & Credibility

The founding team's credential is a verified in-domain exit. Neal Swaelens and Oleksandr Yaremchuk created LLM Guard at Laiyer AI, an open-source LLM firewall the vendor calls the most widely adopted in existence, and Protect AI acquired Laiyer in January 2024. Michael McKenna, the third co-founder and CRO, met the pair through that acquisition.

The public team is small and technical. Beyond the three founders, the about page names a head of growth and a chief architect. The seed announcement positions the founders as having built first-generation AI security and now extending coverage to agents that act rather than talk. \[[s5](#profile-analysis-sources), [s2](#profile-analysis-sources), [s3](#profile-analysis-sources), [s4](#profile-analysis-sources)\]

### Trust Readiness

Trust collateral is unusually far along for a company this young. A public trust center at trust.manifold.security lists a SOC 2 Type 1 attestation, an external network penetration test and a web application and API penetration test, both dated March 2026, dozens of enumerated controls, and a subprocessor list naming its cloud, identity, and AI model providers.

The corporate layer is documented but geographically mixed. The privacy policy names Manifold Security, Inc. and a data protection officer address in Berlin, the seed release carries a San Diego dateline, and press describes the company as California-based. A SOC 2 Type 2 attestation, the usual next step after a Type 1, does not yet appear. \[[s6](#profile-analysis-sources), [s10](#profile-analysis-sources), [s3](#profile-analysis-sources), [s4](#profile-analysis-sources)\]

### Competitors

| Company | Relationship | Note |
|---|---|---|
| Zenity | competes with | Agent security platform spanning discovery, posture, and runtime detection and response across enterprise agent platforms, the broadest overlap with Manifold's detection and response claim. |
| Capsule Security | competes with | Runtime security layer that discovers enterprise AI agents, observes behavior, and blocks unsafe actions, the closest stage and thesis overlap. |
| Operant AI | competes with | Runtime AI defense with in-line redaction and MCP threat blocking, sitting between agents and the services they call rather than on the endpoint. |
| Geordie | competes with | Agent security and governance platform that maps agent tools and MCP connections and applies real-time controls. |
| Straiker | competes with | Agentic AI security vendor pairing red-team testing with runtime guardrails for agents and agentic apps. |

## Strategy Deep Dive

A closer look at the company's product strategy, measuring how [defensible](https://zeltser.com/scoring-security-product-strategy) it is against market forces and examining the [eight areas](https://zeltser.com/security-product-creation-framework) behind it.

### Defensibility

**Exposed (11/21)**

Band guidance: pivot urgently. Analyzed 2026-09-10. Scope: whole company.

Manifold cleared procurement basics unusually early: its trust center lists a SOC 2 Type 1 attestation and two March 2026 penetration tests, for a company founded in 2025. Any funded rival can satisfy the same requirements, so the certifications signal readiness to sell rather than protection from replacement. The product is software the customer runs, and the public record shows no integrations or named deployments that would make replacing it expensive. Manifest, the company's free index that rates AI agent components for risk, publishes its scores openly, so that published layer is not a proprietary asset. What Manifold has that a rival cannot quickly buy is its founders' experience defending AI systems, and that is a head start rather than a lasting lead.

| Dimension | Score | Rationale |
|---|---|---|
| Value Delivery | 1/3 | Manifold is sold as a security software platform whose detections surface to the buyer's security team, the software-as-product level, with no managed service or accountability-bearing human layer in the public record. \[[s1](#deep-dive-sources), [s4](#deep-dive-sources)\] |
| Switching Cost | 1/3 | The vendor markets agentless deployment in minutes, and no integrations, data-residency commitments, or named deployments that would accumulate switching friction appear in the public record of a company with no disclosed customers. \[[s1](#deep-dive-sources), [s4](#deep-dive-sources)\] |
| Compliance Moat | 1/3 | A SOC 2 Type 1 and two penetration tests are table-stakes collateral a determined competitor can obtain, and the cited record identifies no certification bar a replacement could not clear. \[[s6](#deep-dive-sources)\] |
| Problem Complexity | 3/3 | Discovering agents, mapping their MCP and tool connections, and detecting behavioral drift in real time across endpoint fleets is real-time systems and detection engineering, the kind of work the founders' LLM Guard background exists to support. \[[s1](#deep-dive-sources), [s5](#deep-dive-sources)\] |
| Buyer Profile | 2/3 | The pitch targets enterprise security teams and the trust collateral is procurement-ready, but no regulated-enterprise customer is evidenced, so the buyer today is best read as enterprise security teams evaluating an early-stage product. \[[s6](#deep-dive-sources), [s1](#deep-dive-sources)\] |
| Layer | 2/3 | The platform is a monitoring and response layer over agent activity, able to remediate, quarantine, and terminate, more than a single-use application but not evidenced as infrastructure that agents depend on to run. \[[s1](#deep-dive-sources)\] |
| Proprietary Data, Content, or IP | 1/3 | Manifest publishes its index and scores openly, and no named non-public dataset or cross-customer telemetry asset is evidenced, so a funded rival starting today faces no demonstrated data barrier. \[[s8](#deep-dive-sources), [s7](#deep-dive-sources)\] |

### Strategic Market Segmentation

Manifold targets enterprises whose employees already run AI agents on their computers, and its stated buyer is the security team that must permit that adoption without losing visibility. The initial user population is developers, whose coding agents reach source code and production systems through MCP servers and third-party tools, and the company argues the same exposure is spreading to every knowledge worker as agent tools move beyond engineering.

The segmentation is a thesis rather than an evidenced beachhead. No production customer, industry vertical, or deployment size appears in the public record, so who actually buys first, and at what company size, cannot be read from outside. The vendor's surveys-heavy framing of the pain also leaves open how much of the urgency is budget-backed today. \[[s1](#deep-dive-sources), [s3](#deep-dive-sources), [s4](#deep-dive-sources)\]

### Product Capabilities & AI Advantages

The platform's claimed advantage is watching actions instead of words. Manifold observes agent behavior at runtime, discovering every agent on an endpoint, mapping the MCP servers, tools, resources, and skills each one invokes, assessing risk and exposure, and detecting and responding when behavior drifts, a runtime-behavior focus beyond the founders' earlier LLM-security work. The company presents agentless deployment in minutes as a second selling point.

Manifest extends the capability story into the AI supply chain. The free index catalogs skills, plugins, extensions, and MCP servers with visible scoring, and the company describes graph analysis that maps what a component does and where it sits in the ecosystem, a response to agent components spreading through public registries with minimal vetting.

If the platform aggregates agent-behavior telemetry across customers, cross-customer baselines of normal agent activity could become an advantage no single tenant can reproduce, but no public evidence yet shows such an asset accumulating. External validation is thin overall: the reviewed record shows no docs portal, benchmark, or third-party evaluation of the platform. \[[s1](#deep-dive-sources), [s7](#deep-dive-sources), [s8](#deep-dive-sources), [s5](#deep-dive-sources)\]

### Sales Engagement & Go-to-Market

The visible motion is early, demo-gated selling. The paid platform's sales path is a demo request, there is no self-service tier or published pricing for the platform, and the March 2026 seed release frames the capital as fueling product development, all consistent with a company still validating with early accounts.

Manifest is the company's visible route to an audience. The free, open-access index gives security teams and developers a reason to visit and a habit to form before any purchase, and it doubles as a public demonstration of the company's research. No channel partnership, marketplace listing, or reseller motion appears in the reviewed sources, and the homepage's named endorsements come from security executives and the company's own investors rather than labeled customer references. \[[s1](#deep-dive-sources), [s3](#deep-dive-sources), [s8](#deep-dive-sources), [s9](#deep-dive-sources)\]

### Pricing Model

Manifold publishes no pricing. The platform is sold through demo requests, which for an enterprise security product at this stage usually means negotiated deals sized per engagement, and the public record does not disclose the pricing unit, whether per endpoint, per agent, or per seat.

The one visible pricing decision is Manifest at zero. Giving the supply chain intelligence away positions it as a funnel rather than a revenue line and prices the adjacent intelligence market defensively, since a rival would now charge for something Manifold gives away. \[[s1](#deep-dive-sources), [s8](#deep-dive-sources), [s7](#deep-dive-sources)\]

### Product Delivery & Operations

The public materials describe an agentless, endpoint-oriented deployment backed by cloud subprocessors. The vendor's central operational claim is deployment in minutes, which lowers the cost of a first deployment and shortens evaluation cycles for a security team piloting agent visibility.

The operational chain behind the service is documented at an unusual level of detail for the company's age. The trust center carries an enumerated controls section covering infrastructure and product security and a subprocessor list, which gives an evaluating team a concrete picture of what runs where. \[[s1](#deep-dive-sources), [s6](#deep-dive-sources)\]

### Earning Customers' Trust

Trust collateral leads the company's maturity curve. A public trust center lists a SOC 2 Type 1 attestation, an external network penetration test and a web application and API penetration test both dated March 2026, an enumerated controls section, and a subprocessor list. The gaps are the ones age explains. As of 2026-07-03 the trust center listed no SOC 2 Type 2 attestation, the period-of-time audit that follows a Type 1, and no ISO certification. The privacy program is unusually international for the stage, naming a data protection officer address in Berlin for European matters. \[[s6](#deep-dive-sources), [s10](#deep-dive-sources)\]

### Platform Strategy & Ecosystem Positioning

Manifold monitors an ecosystem it does not control. The platform's subject matter, agents, MCP servers, skills, and extensions, is defined by outside actors, most visibly Anthropic, whose 2025 SKILL.md standard created the portable agent-instruction format whose spread Manifest now scores, and the public registries where those components circulate. That position makes coverage breadth a moving target set by others.

The company's own ecosystem surface is thin so far. No integration marketplace, technology alliance program, or published SIEM and SOAR connector list appears in the reviewed sources, so the platform currently reads as a standalone console rather than a node in the buyer's existing security stack. \[[s7](#deep-dive-sources), [s8](#deep-dive-sources), [s1](#deep-dive-sources)\]

### Team & Execution Capability

The founding team is the company's strongest verifiable asset. Neal Swaelens (CEO) and Oleksandr Yaremchuk (CTO) created LLM Guard at Laiyer AI, the open-source LLM firewall the vendor calls the most widely adopted in existence, and Protect AI acquired Laiyer AI in January 2024. Michael McKenna (CRO) met the pair through that acquisition, giving the team a dedicated commercial founder alongside the two builders.

The public team is small. Beyond the founders, the about page names a head of growth and a chief architect, and the careers page listed no open vacancies on the accessed date, a compact public roster for a seed-stage company. \[[s5](#deep-dive-sources), [s2](#deep-dive-sources), [s3](#deep-dive-sources), [s9](#deep-dive-sources)\]

## Sources

### Company Detail Sources

Cited from the Sourced Details and Matrix Coverage rows.

| Id | Source | Tier | Accessed |
|---|---|---|---|
| f1 | [Manifold homepage: Runtime Security for AI Agents on Endpoints](https://manifold.security/) | official | 2026-07-03 |
| f2 | [SecurityWeek: Manifold Raises $8 Million for AI Detection and Response (March 18, 2026)](https://www.securityweek.com/manifold-raises-8-million-for-ai-detection-and-response/) | press | 2026-07-03 |
| f3 | [Manifold press release (San Diego dateline; SecurityWeek says California-based): Manifold Raises $8M to Secure AI Agents on Endpoints](https://www.manifold.security/blog/manifold-raises-8m-seed-funding) | official | 2026-07-03 |
| f4 | [SiliconANGLE: Manifold raises $8M to secure autonomous AI agents on enterprise endpoints (March 18, 2026)](https://siliconangle.com/2026/03/18/manifold-raises-8m-secure-autonomous-ai-agents-enterprise-endpoints/) | press | 2026-07-03 |

### Profile Analysis Sources

Cited from the Market Readiness section.

| Id | Source | Tier | Accessed |
|---|---|---|---|
| s1 | [Manifold homepage: Runtime Security for AI Agents on Endpoints (Discovery, Detection and Response, Risk and Exposure)](https://manifold.security/) “Agentless and deployed in minutes, Manifold reveals and protects what agents do, not what they say. Total runtime visibility, across every endpoint and first party application.” | official | 2026-07-03 |
| s2 | [Manifold about page: Our Story and team roster (Neal Swaelens CEO, Oleksandr Yaremchuk CTO, Michael McKenna CRO)](https://www.manifold.security/about) “Our founders created LLM Guard: the most widely adopted open-source LLM firewall in existence. Then took it to market, securing AI deployments across Fortune 500 enterprises at scale.” | official | 2026-07-03 |
| s3 | [Manifold press release: Manifold Raises $8M to Secure AI Agents on Endpoints (March 18, 2026, San Diego dateline)](https://www.manifold.security/blog/manifold-raises-8m-seed-funding) “today announced the close of an $8 million seed funding round. Costanoa Ventures led the round with participation from Cherry Ventures, Rain Capital and Modern Technical Fund, and notable angel investors including former Uber CSO Joe Sullivan, and former Google DeepMind CISO Vijay Bolina.” | official | 2026-07-03 |
| s4 | [SecurityWeek (Ionut Arghire): Manifold Raises $8 Million for AI Detection and Response (March 18, 2026, seed led by Costanoa Ventures)](https://www.securityweek.com/manifold-raises-8-million-for-ai-detection-and-response/) “Founded in 2025, California-based Manifold has built an agentic AI Detection and Response (AIDR) platform that provides runtime visibility into agents' activities.” | press | 2026-07-03 |
| s5 | [SiliconANGLE (Duncan Riley): Manifold raises $8M to secure autonomous AI agents on enterprise endpoints (March 18, 2026)](https://siliconangle.com/2026/03/18/manifold-raises-8m-secure-autonomous-ai-agents-enterprise-endpoints/) “founded by Neal Swaelens, Oleksandr Yaremchuk and Michael McKenna, who formerly worked on AI security technologies, including the LLM Guard project developed at Laiyer AI. Following Laiyer AI's acquisition by Protect AI Inc. in January 2024” | press | 2026-07-03 |
| s6 | [Manifold Security Trust Center (trust.manifold.security, agent-browser render, 2026-07-03)](https://trust.manifold.security/) “Manifold SOC 2 Type 1 External Network Penetration Test (March 2026) Wep App and API Penetration Test (March 2026)” | official | 2026-07-03 |
| s7 | [Manifold blog: Introducing Manifest, Supply Chain Intelligence for the AI Agent Ecosystem (April 14, 2026)](https://www.manifold.security/blog/manifest-ai-supply-chain-intelligence) “The SKILL.md standard, introduced by Anthropic in 2025, created a portable format for agent instructions that works across Claude Code, Cursor, Copilot, Windsurf, Codex, and dozens of other agents.” | official | 2026-07-03 |
| s8 | [Manifest (manifest.manifold.security): AI Supply Chain Intelligence by Manifold, live intelligence index](https://manifest.manifold.security) “We uncover risks in any AI component your employees rely on, skills, plugins, extensions, MCP servers, and more.” | official | 2026-07-03 |
| s9 | [Manifold careers page: current vacancies (accessed 2026-07-03)](https://www.manifold.security/careers) “Whilst we have no immediate vacancies, we're always on the lookout for exceptional talent and grit.” | official | 2026-07-03 |
| s10 | [Manifold privacy policy (last updated April 29, 2026): Manifold Security, Inc. legal entity](https://www.manifold.security/privacy) “For matters related to data protection in the European Economic Area, you may also write to our Data Protection Officer at: Manifold Security, Inc. Data Protection Officer Heidestrasse 34 Berlin, 10557 Germany” | official | 2026-07-03 |

### Deep-Dive Sources

Cited from the Strategy Deep Dive section.

| Id | Source | Tier | Accessed |
|---|---|---|---|
| s1 | [Manifold homepage: Runtime Security for AI Agents on Endpoints (Discovery, Detection and Response, Risk and Exposure)](https://manifold.security/) “Agentless and deployed in minutes, Manifold reveals and protects what agents do, not what they say. Total runtime visibility, across every endpoint and first party application.” | official | 2026-07-03 |
| s2 | [Manifold about page: Our Story and team roster (Neal Swaelens CEO, Oleksandr Yaremchuk CTO, Michael McKenna CRO)](https://www.manifold.security/about) “Our founders created LLM Guard: the most widely adopted open-source LLM firewall in existence. Then took it to market, securing AI deployments across Fortune 500 enterprises at scale.” | official | 2026-07-03 |
| s3 | [Manifold press release: Manifold Raises $8M to Secure AI Agents on Endpoints (March 18, 2026, San Diego dateline)](https://www.manifold.security/blog/manifold-raises-8m-seed-funding) “today announced the close of an $8 million seed funding round. Costanoa Ventures led the round with participation from Cherry Ventures, Rain Capital and Modern Technical Fund, and notable angel investors including former Uber CSO Joe Sullivan, and former Google DeepMind CISO Vijay Bolina.” | official | 2026-07-03 |
| s4 | [SecurityWeek (Ionut Arghire): Manifold Raises $8 Million for AI Detection and Response (March 18, 2026, seed led by Costanoa Ventures)](https://www.securityweek.com/manifold-raises-8-million-for-ai-detection-and-response/) “Founded in 2025, California-based Manifold has built an agentic AI Detection and Response (AIDR) platform that provides runtime visibility into agents' activities.” | press | 2026-07-03 |
| s5 | [SiliconANGLE (Duncan Riley): Manifold raises $8M to secure autonomous AI agents on enterprise endpoints (March 18, 2026)](https://siliconangle.com/2026/03/18/manifold-raises-8m-secure-autonomous-ai-agents-enterprise-endpoints/) “founded by Neal Swaelens, Oleksandr Yaremchuk and Michael McKenna, who formerly worked on AI security technologies, including the LLM Guard project developed at Laiyer AI. Following Laiyer AI's acquisition by Protect AI Inc. in January 2024” | press | 2026-07-03 |
| s6 | [Manifold Security Trust Center (trust.manifold.security, agent-browser render, 2026-07-03)](https://trust.manifold.security/) “Manifold SOC 2 Type 1 External Network Penetration Test (March 2026) Wep App and API Penetration Test (March 2026)” | official | 2026-07-03 |
| s7 | [Manifold blog: Introducing Manifest, Supply Chain Intelligence for the AI Agent Ecosystem (April 14, 2026)](https://www.manifold.security/blog/manifest-ai-supply-chain-intelligence) “The SKILL.md standard, introduced by Anthropic in 2025, created a portable format for agent instructions that works across Claude Code, Cursor, Copilot, Windsurf, Codex, and dozens of other agents.” | official | 2026-07-03 |
| s8 | [Manifest (manifest.manifold.security): AI Supply Chain Intelligence by Manifold, live intelligence index](https://manifest.manifold.security) “We uncover risks in any AI component your employees rely on, skills, plugins, extensions, MCP servers, and more.” | official | 2026-07-03 |
| s9 | [Manifold careers page: current vacancies (accessed 2026-07-03)](https://www.manifold.security/careers) “Whilst we have no immediate vacancies, we're always on the lookout for exceptional talent and grit.” | official | 2026-07-03 |
| s10 | [Manifold privacy policy (last updated April 29, 2026): Manifold Security, Inc. legal entity](https://www.manifold.security/privacy) “For matters related to data protection in the European Economic Area, you may also write to our Data Protection Officer at: Manifold Security, Inc. Data Protection Officer Heidestrasse 34 Berlin, 10557 Germany” | official | 2026-07-03 |

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