AI data protectionAdditional if: Sensitive content enters AI flows · Sensitive content must be inspected or blocked in prompts, responses, files, retrieved information, or tool calls.Action-taking agent safeguardsDirectly addresses · Observe and govern agent plans, memory, tool use, delegated tasks, and actions while the agent runs.AI gateway and tool-connection controlsAdditional if: Model or tool traffic uses a security gateway · Model, tool, connector, API, or Model Context Protocol (MCP) traffic is routed through a security gateway.Coding-agent and developer workstation securityAdditional if: Coding agents reach developer systems · Coding agents can reach code editors, command-line tools, repositories, build systems, software packages, or developer workstations.
Vendor research
Harmonic Security
Review what this vendor says publicly, the security topics those statements may support, what remains unverified, and factual company context. This is not an assessment of product effectiveness or fit.
Use-case context
How this vendor relates to the selected use case
Related research availableBack to use case →
These links show approaches associated with this vendor. The relationship label describes how the approach maps to the use case—not product effectiveness, complete requirement coverage, or fit.
Company scale
Emerging?
EmergingAn early-stage provider with less than $25M in known funding, or 50 or fewer employees without at least $50M in known funding.This is a company-scale signal, not a product-quality rating.
?
EmergingAn early-stage provider with less than $25M in known funding, or 50 or fewer employees without at least $50M in known funding.This is a company-scale signal, not a product-quality rating.A descriptive band derived from retained public revenue, workforce, ownership, or funding signals.
Company scale is separate from product features, effectiveness, and suitability.
- $26M known funding
- <50 employees
- Founded 2023
Company context
Private, VC-backed
Founded by former Digital Shadows leadership; product timeline includes Model Context Protocol (MCP) Gateway launch in 2025
Research coverageCounts describe available public research, not product quality.View details
- Vendor statements
- 19 records
- Source-checked records
- 14
- Evaluation requirements
- 19 in this research model
- Unresolved requirements
- 5
Company intelligence
Who is behind the product
Company facts provide evaluation context. Each signal is kept separate because tenure, workforce, funding, and hiring answer different questions.
Founded2023
HeadquartersSan Francisco, California; London presence
OwnershipPrivate, VC-backed
Employees<50
Capital and scaleIndependent company
Harmonic Security
- Known funding
- $26M
- Operating scale
- Founded by former Digital Shadows leadership; product timeline includes MCP Gateway launch in 2025
- Backing context
- $17.5M Series A led by Next47; more than $26M secured since launch; seed led by Ten Eleven Ventures
Series A · $17.5M · 2024-10-02
Named investors
Next47 · Ten Eleven Ventures
Founders and leadership2 people listed
- Alastair PatersonCurrent role listed
CEO & Co-Founder
- Bryan Woolgar-O'NeilCurrent role listed
CTO & Co-Founder
Operating signalsRead each signal separately
There is no combined company rating. The company-scale label uses stated size thresholds; product features and effectiveness require separate evidence.
- Company tenure
- 2023
- Workforce scale
- <50
- Hiring activity
- 9 open positions · active
A hiring count is shown only when a clickable source is available.
Greenhouse careers board ↗Core company facts have supporting public sources.
Company sources and research limits4 linked public sources
Only company facts supported by retained public sources are shown. Missing values remain unknown, and company scale does not establish product effectiveness.
Company sourceHarmonic about pageHarmonic lists its 2023 founding, seed, Series A, and MCP Gateway timeline.Company sourceHarmonic Series A announcementHarmonic announced a $17.5M Series A led by Next47 and more than $26M total secured.Company information sourceStored company websiteSupports the company facts shown in this profile.Company information sourceGreenhouse careers boardSupports the company facts shown in this profile.
Solution areas
These areas describe how the vendor approaches enterprise AI security. They do not establish product quality or fit.
Buyer context
- Public claims are especially relevant to generative AI data loss prevention (DLP) and workforce AI control use cases.
- Buyer diligence should separate browser/desktop/Model Context Protocol (MCP) coverage from broader non-human identity (NHI) lifecycle capabilities.
Related frameworks
Where public vendor statements relate to framework requirements
11 related frameworks · expand when needed
Related frameworks
Where public vendor statements relate to framework requirements
These links show related requirements for further review. They do not establish framework compliance or control implementation. Open the full framework crosswalk →
Current referenceCSA AI Controls Matrix
- Requirements with public support
- 13
- Related requirements
- 14
- References
- 71
- Requirements with public support
- 13
- Related requirements
- 12
- References
- 35
- Requirements with public support
- 13
- Related requirements
- 12
- References
- 71
- Requirements with public support
- 13
- Related requirements
- 13
- References
- 39
- Requirements with public support
- 13
- Related requirements
- 12
- References
- 39
- Requirements with public support
- 13
- Related requirements
- 12
- References
- 31
- Requirements with public support
- 13
- Related requirements
- 13
- References
- 31
- Requirements with public support
- 13
- Related requirements
- 13
- References
- 25
- Requirements with public support
- 12
- Related requirements
- 11
- References
- 58
- Requirements with public support
- 12
- Related requirements
- 11
- References
- 27
- Requirements with public support
- 3
- Related requirements
- 3
- References
- 3
Evaluation questions
What to verify beyond public claims
These questions come from security requirements with some public support. Use them as starting points for demonstrations, documentation review, customer references, or a buyer-observed pilot.
- 01Unapproved AI use discovery
An unmanaged AI app used by a test user appears in discovery inventory with user, app or domain, and timestamp.
- 02Unapproved AI use discovery
The test user's AI usage activity can be filtered or exported with AI-specific context.
- 03AI-feature discovery in business applications
A software as a service (SaaS) app with an embedded AI feature appears in the software as a service (SaaS) AI inventory with app, provider, and feature context.
- 04AI-feature discovery in business applications
The inventory shows which users, data classes, integrations, or providers are associated with the AI-enabled software as a service (SaaS) app.
- 05Approved AI usage monitoring
Approved AI workspace activity appears with user, workspace or tenant, model or provider, and timestamp.
- 06Approved AI usage monitoring
Prompt, model, or admin activity can be exported or correlated for the selected approved AI platform.
- 07Controls for unapproved AI use
A policy blocks, coaches, redirects, or contains a test interaction with an unapproved AI destination.
- 08Controls for unapproved AI use
The control event records policy reason, user, destination, action, and timestamp.
Detailed security-requirement research18 evaluation items · supporting evidence and open research are shown separatelyExpand
Security requirementPublic supportRelated frameworksWhat to verify
Unapproved AI use discovery
Strong public supportDiscover and monitor workforce AI tools, accounts, prompts, domains, models, users, and usage outside approved controls.
NIST AI RMF PlaybookNIST Cybersecurity Framework 2.0CIS Critical Security ControlsISO/IEC 42001OWASP GenAI Security Solutions Landscape
An unmanaged AI app used by a test user appears in discovery inventory with user, app or domain, and timestamp.
AI-feature discovery in business applications
Limited public supportInventory software as a service (SaaS) applications that embed AI features, expose enterprise data to AI capabilities, or create AI-driven data movement.
NIST AI RMF PlaybookNIST Cybersecurity Framework 2.0CIS Critical Security ControlsISO/IEC 42001OWASP GenAI Security Solutions Landscape
A software as a service (SaaS) app with an embedded AI feature appears in the software as a service (SaaS) AI inventory with app, provider, and feature context.
Approved AI usage monitoring
Limited public supportMonitor approved AI workspaces, tenants, gateways, and model platforms such as ChatGPT Enterprise, Claude Enterprise, Gemini, Microsoft Copilot, Vertex AI, Elvex, or internal AI gateways.
NIST AI RMF PlaybookNIST Cybersecurity Framework 2.0CIS Critical Security ControlsISO/IEC 42001OWASP GenAI Security Solutions Landscape
Approved AI workspace activity appears with user, workspace or tenant, model or provider, and timestamp.
Controls for unapproved AI use
Strong public supportBlock, coach, redirect, or contain non-approved AI use and policy-violating AI interactions.
NIST AI RMF PlaybookNIST Cybersecurity Framework 2.0CIS Critical Security ControlsISO/IEC 42001OWASP GenAI Security Solutions Landscape
A policy blocks, coaches, redirects, or contains a test interaction with an unapproved AI destination.
Sensitive-data protection for generative AI
Limited public supportDetect, classify, redact, or block sensitive data in prompts, responses, files, retrieval, memory, and AI-connected workflows.
NIST AI RMF PlaybookNIST Cybersecurity Framework 2.0CIS Critical Security ControlsISO/IEC 42001OWASP GenAI Security Solutions Landscape
Sensitive prompt, response, or file test data is detected and classified during an AI interaction.
Browser and business-application controls
Strong public supportApply session-level controls in browser and software as a service (SaaS) workflows, including uploads, downloads, copy/paste, sharing, and identity-aware access decisions.
NIST AI RMF PlaybookNIST Cybersecurity Framework 2.0CIS Critical Security ControlsISO/IEC 42001OWASP GenAI Security Solutions Landscape
A session-level policy controls upload, download, copy, paste, sharing, or form submission in a browser or software as a service (SaaS) workflow.
Generative AI application security
No supporting claim foundProtect enterprise-built large language model (LLM) applications, retrieval-augmented generation (RAG) systems, prompts, application programming interfaces (APIs), model calls, tools, and production runtime behavior.
NIST AI RMF PlaybookNIST Cybersecurity Framework 2.0CIS Critical Security ControlsISO/IEC 42001OWASP GenAI Security Solutions Landscape
A test large language model (LLM) application event records prompt, application programming interface (API), model, retrieval, or tool interaction context.
AI governance, risk, and compliance
Limited public supportInventory AI systems and owners, translate policy and regulatory obligations into governed workflows, assess risk, manage approvals and exceptions, and retain audit evidence across the AI lifecycle.
NIST AI RMF PlaybookNIST Cybersecurity Framework 2.0CIS Critical Security ControlsISO/IEC 42001OWASP GenAI Security Solutions Landscape
A test AI system is registered with owner, intended use, risk tier, lifecycle state, and applicable obligations.
AI assurance and adversarial testing
No supporting claim foundTest models, applications, retrieval-augmented generation (RAG) systems, and agents before release and continuously thereafter using adversarial probes, evaluation suites, attack simulation, and security release gates.
NIST AI RMF PlaybookNIST Cybersecurity Framework 2.0CIS Critical Security ControlsISO/IEC 42001OWASP GenAI Security Solutions Landscape
A controlled test campaign exercises an AI model, application, or agent against named AI attack classes.
AI model and supply-chain security
No supporting claim foundDiscover, inventory, scan, validate, and monitor models, datasets, model artifacts, registries, dependencies, and AI development assets for tampering, unsafe serialization, provenance gaps, or malicious content.
NIST AI RMF PlaybookNIST Cybersecurity Framework 2.0CIS Critical Security ControlsISO/IEC 42001OWASP GenAI Security Solutions Landscape
A test model or AI artifact appears in inventory with origin, version, hash or provenance, and deployment context.
AI gateway, tool-connection, and runtime controls
Strong public supportMediate model, agent, tool, application programming interface (API), connector, and Model Context Protocol (MCP) traffic through an enforcement point that applies identity-aware policy, content controls, routing, rate limits, and auditable allow or deny decisions.
NIST AI RMF PlaybookNIST Cybersecurity Framework 2.0CIS Critical Security ControlsISO/IEC 42001OWASP GenAI Security Solutions Landscape
A model, agent, tool, or Model Context Protocol (MCP) request passes through a named policy enforcement point.
Action-taking agent monitoring
Strong public supportObserve and govern agent plans, memory, tool calls, delegated tasks, autonomy, runtime decisions, and outcomes.
NIST AI RMF PlaybookNIST Cybersecurity Framework 2.0CIS Critical Security ControlsISO/IEC 42001OWASP GenAI Security Solutions Landscape
A test agent run captures plan, steps, tool calls, outcome, and timestamps.
Agent-to-agent communication security
Limited public supportAuthorize, log, and control agent-to-agent, agent-to-tool, Model Context Protocol (MCP), connector, and tool-chain handoffs.
NIST AI RMF PlaybookNIST Cybersecurity Framework 2.0CIS Critical Security ControlsISO/IEC 42001OWASP GenAI Security Solutions Landscape
An agent, tool, connector, or Model Context Protocol (MCP) handoff logs source identity, destination, and authorization decision.
Non-human identity and service-account security
No supporting claim foundInventory, least privilege, credential hygiene, monitoring, and lifecycle management for non-human identities, workloads, service accounts, application programming interface (API) keys, and machine credentials.
NIST AI RMF PlaybookNIST Cybersecurity Framework 2.0CIS Critical Security ControlsISO/IEC 42001OWASP GenAI Security Solutions Landscape
A test service account, agent identity, or non-human identity appears in inventory with owner and privileges.
AI agent identity and permissions
Limited public supportRegister AI agents as accountable identities, bind them to owners and delegating users, authorize task- and tool-level access, issue short-lived credentials, review access, and revoke or suspend agent authority.
NIST AI RMF PlaybookNIST Cybersecurity Framework 2.0CIS Critical Security ControlsISO/IEC 42001OWASP GenAI Security Solutions Landscape
A test agent is registered with a unique identity, accountable owner, purpose, and permitted resources.
AI coding-agent and workstation security
Limited public supportDiscover and govern AI coding agents, integrated development environment (IDE) assistants, command-line agents, skills, hooks, extensions, Model Context Protocol (MCP) tools, filesystem access, commands, network activity, secrets, and software-supply-chain actions on developer workstations and build environments.
NIST AI RMF PlaybookNIST Cybersecurity Framework 2.0CIS Critical Security ControlsISO/IEC 42001OWASP GenAI Security Solutions Landscape
A test coding agent and its skills, hooks, extensions, or Model Context Protocol (MCP) tools appear in an attributable inventory.
AI cost and usage controls
Limited public supportVisibility, attribution, budgeting, rate limiting, anomaly detection, and optimization for AI usage and spend across models, agents, workflows, and owners.
Commercial MetadataNIST AI RMF PlaybookNIST Cybersecurity Framework 2.0ISO/IEC 42001OWASP Agentic AI Security Solutions Landscape
A controlled AI usage event is attributed to user, team, model, workflow, or owner with cost or token metrics.
Licensing model
No supporting claim foundPublicly discoverable commercial model such as per user, per seat, per app, per token, per integration, or enterprise platform license.
The vendor can map the sourced commercial model to per-user, per-seat, per-app, per-token, per-integration, or platform packaging.
Public sources
Vendor statements and quoted evidence
Showing the first 6 of 19 source records. Open additional records only when needed.
Harmonic claims organization-wide AI discovery, interaction visibility, team-level intent analysis, unified policy for humans and agents, governance analytics, auditability, and real-time controls across browser, desktop, embedded, and Model Context Protocol (MCP) surfaces.
Every interaction visible. Every interaction governable.
Harmonic platform materials reviewed did not provide a public product claim for automated adversarial testing, repeatable attack suites, model or agent red teaming, or release-gate evaluation.
No quoted source text is recorded for this claim.
Harmonic platform materials reviewed did not establish model artifact scanning, provenance, signing, dependency analysis, Model Context Protocol (MCP) component risk scoring, tamper detection, or model-registry release controls.
No quoted source text is recorded for this claim.
Harmonic claims a locally installed Model Context Protocol (MCP) Gateway and endpoint controls that intercept Model Context Protocol (MCP) traffic, inspect prompt and tool interactions, block risky actions, prevent sensitive-data exfiltration, and apply intent-aware policy in under 200 milliseconds.
Transparently intercepts all MCP traffic enabling security teams to discover what clients and servers are in use, enforce granular policies to block risky actions.
Harmonic claims a common policy plane for agents and humans with contextual, team-based controls over agent tool and server actions.
Agents and humans on the same policy plane.
Harmonic claims device and Model Context Protocol (MCP) gateway controls for integrated development environment (IDE) coding assistants, local development environments, agent tool calls, source code, internal identifiers, infrastructure configuration, and sensitive-data flows.
The ability to apply policy controls at the point where the AI agent interacts with internal systems.
Show 13 additional evidence records
Harmonic claims organization-wide AI interaction and usage visibility that helps identify where AI drives productivity, where investments create value, and where budget is wasted.
where AI is driving productivity, where it's creating risk, and where the budget is being wasted.
Harmonic claims visibility across the full AI stack across vendors, including long-tail and agentic surfaces, beyond Microsoft-only coverage.
Purview gives you visibility inside Microsoft, on Microsoft tools, with Microsoft pattern matching. Real AI usage is not Microsoft-only. We see the full stack across vendors, including the long tail and the agentic surfaces, and we govern with intent classification rather than regex.
Harmonic claims coverage for AI running in browser tabs, desktop apps, employee-started agents, and embedded copilots inside software as a service (SaaS) tools.
AI does not live in one place. It runs in the browser tab your sales lead opened, the desktop app your developer installed, the agent your engineer kicked off, and the embedded copilot inside the SaaS tools you already pay for. Harmonic Security covers all four.
Harmonic claims it understands intent behind AI interactions across approved tools, shadow apps, and employee-created agents and governs those interactions in real time.
AI is everywhere your employees work: in approved tools, shadow apps, and the agents they're spinning up on their own. Harmonic Security sits at that layer, understands the intent behind every interaction, and governs it in real time.
Harmonic claims teams can block risky AI actions in real time, warn employees with context, or log silently for review.
You can block in real time, warn the employee with context about why the action is risky, or log silently for security team review.
Harmonic claims data classification and logging provide audit trails, data residency controls, and evidence that AI use stays within defined boundaries.
Our data classification and logging give you the audit trail, the data residency controls, and the ability to demonstrate that AI use in your organization operates within defined boundaries.
Harmonic Security claims it governs AI interactions across employees and agents, including browser, desktop, agent, and Model Context Protocol (MCP) surfaces.
Every interaction visible. Every interaction governable.
Harmonic Security claims coverage for agents, skills, Model Context Protocol (MCP), and CLI workflows, including tool calls, scopes, and destructive actions.
Tool calls, scopes, destructive actions.
No public claim found for this capability.
No quoted source text is recorded for this claim.
Harmonic Security claims real-time visibility and control across the browser and desktop.
Real-time visibility and control across the browser and desktop
No public claim found for this capability.
No quoted source text is recorded for this claim.
No public claim found for this capability.
No quoted source text is recorded for this claim.
Harmonic Security claims an Model Context Protocol (MCP) gateway and shared policy plane for agents and humans, adjacent to external AI gateway deployments.
Browser extension, desktop client, and MCP gateway in one deployment