Harmonic Security Pricing: Compare Explore and Guide with Command

Harmonic Security pricing is package-led but not rate-led. The public page reviewed on 8 November 2026 names Explore and Guide alongside Command, yet it displays no numeric license price or included user allowance. It also gives no overage rate or minimum term. Buyers can still make the quote comparable. The useful work is to pin each package to the exact workforce and agent surfaces it covers, then require the proposal to define the billable population and every paid add-on.

TL;DR

• Explore covers AI discovery, prompt-level visibility, usage intelligence, sensitive-data detection, application risk, and identity enrichment.
• Guide includes Explore, then adds desktop and IDE coverage, inline coaching or blocking, granular policies, and alert webhooks.
• Command includes Guide, then adds MCP discovery, agent permissions, agent-workflow data protection, and cross-surface intelligence.
• Harmonic publishes no numeric rate or commercial meter on the reviewed pricing page. Its quote must define users, devices, interactions, agents, MCP servers, support, and audit-log export.
• DeepInspect overlaps only on authenticated HTTP model traffic deliberately routed through its proxy, not Harmonic's wider browser, desktop, or MCP discovery surfaces.

Harmonic Security pricing has three named packages

The current Harmonic Security pricing page presents an ascending package structure. Explore establishes visibility into workforce AI use. Guide adds real-time controls across browser and desktop activity. Command extends the controls to agentic workflows. The page labels Command as the most popular package but supplies no currency amount beside any package.

The page omits the billable unit needed for a defensible cost calculation. It identifies neither a per-user or per-device meter nor a per-interaction or flat-platform meter. Published material also omits included quantities, overage rules, contract minimums, and renewal formulas. A buyer can describe the public commercial position as "three named packages, sales quote required." Calling the product free, usage-based, or per-seat would go beyond the source.

I would reject a comparison sheet that assigns a guessed annual figure to Harmonic. A blank rate cell with a retrieval date is more accurate than a polished estimate. Put the three package names down the left edge of a single printed sheet. Across the top, use entitlement and covered surface, billable unit and allowance, overage and support, plus retention and renewal. That physical layout makes gaps visible before a total obscures them.

Explore is the discovery and intelligence package

Explore promises prompt-level visibility across more than 1,000 applications and AI Usage Intelligence mapped to business use cases. It also promises contextual sensitive-data detection and a risk score for each application, along with identity enrichment through Entra, Okta, and Google Workspace. The package language emphasizes discovering tools and data flows, along with the reasons employees use AI.

The feature comparison adds detail by listing browser-based AI tools and discovery across more than 10,000 apps. Task-level use-case analysis sits beside departmental productivity insights, sensitive-data exposure, app-risk assessment, and corporate-versus-personal account tracking. Real-time sensitive-data detection and app categorization also appear. Those capabilities make Explore a visibility purchase first, even though detection appears in the package.

A quote should define what "prompt-level visibility" means for storage and access. Ask whether prompts are retained by default and whether full content can be omitted. Also ask which roles can retrieve it. Record the identity-sync prerequisite and treatment of personal accounts. Confirm whether the application counts describe the vendor catalog or a contractual coverage guarantee for the buyer's estate.

There is also a public-page ambiguity worth resolving in writing. The Explore card lists browser extension and OpenTelemetry under "Deployment," alongside desktop apps and AI agents. The comparison grid marks desktop AI apps and developer tools unavailable in Explore, and it also marks autonomous AI agents unavailable. The likely distinction may be deployment compatibility versus package entitlement, but the page does not explain it. Ask Harmonic to state which collectors can be installed under Explore. The response should also state which collected events are licensed and visible, as well as which are retained and actionable.

Guide adds endpoint control and interventions

Guide includes everything in Explore. Its card adds endpoint coverage for desktop apps and IDEs, as well as copilots. It also adds customizable inline coaching that can warn, nudge, or block, with a stated response time under 200 milliseconds. Granular policy can use data type and application plus user role, while alert webhooks support SIEM and SOAR integrations.

The comparison grid further assigns endpoint AI process inventory and warning banners, plus employee coaching and policy enforcement, to Guide and Command rather than Explore. Those packages also receive configurable employee groups and intervention messages, along with keyword detection and SIEM or SOAR integrations. Full prompt audit log streaming appears as an add-on for Guide and Command.

The distinction between an alert and a pre-submission action needs a test. Use synthetic data and attempt a paste or upload through one approved browser app and one personal AI account. Repeat it through one desktop client and one IDE assistant. Record whether Harmonic only observes or warns, or whether it redacts or blocks on each path. Repeat the test with an unmanaged device and with the extension disabled. The result should become an attachment to the quote because "endpoint coverage" does not identify the action available on every application.

For commercial normalization, ask whether all licensed users receive the same controls. Define device limits and treatment of shared workstations. Add browser and operating-system support, along with MDM deployment and policy design. Include webhook volume and customer-success scope. If full prompt audit streaming is required, put the add-on on a separate line with destination and volume, plus retention and support assumptions.

The AI security vendor evaluation criteria provide a route-by-route test for identity and action, as well as failure behavior and evidence. Use those fields to keep a visible browser warning separate from an enforced block inside a desktop process.

Command adds the agent and MCP layer

Command includes everything in Guide, then adds MCP client and server discovery. It provides permissions for agent read and write actions, as well as execute actions. It also provides data protection inside agentic workflows and intelligence connecting human and agent activity. The pricing page lists prompt-injection detection and blocking as "coming soon." A buyer should preserve that status instead of scoring it as a generally available entitlement.

The Harmonic Command page describes a combined view of employee and agent AI use. Command also sets permissions for what agents may do across connected MCP servers, including reading, writing, and acting on connected systems.

Its commercial scope can depend on discovered MCP clients and MCP servers, tools and agent identities, plus connected systems and actions. Ask Harmonic which object is licensed and how ephemeral servers or development environments are counted. Confirm the supported MCP transports and client types, then separate discovery from enforcement. An inventory entry for a server is not proof that each tool call passes through a control point.

The proposal should name the enforcement location for read and write permissions, plus execute permissions. It should state what happens when the local component or policy service is unavailable, as well as when the identity provider is unavailable. Ask whether an action fails open or fails closed, or follows a cached policy. Include policy-version evidence and exception expiry, along with the record available after a blocked tool call.

Prompt-injection protection marked "coming soon" should carry no purchase credit until the order form supplies availability and supported surfaces, along with acceptance tests and remedy if delivery slips. A roadmap sentence is not an entitlement.

Normalize the quote around six operating populations

Start the normalization with the licensed population. Record employees and contractors separately from administrators and non-human identities. Add active-versus-provisioned treatment and joiner and leaver handling. Include seasonal workers and minimum quantities. If the vendor does not bill by user, the exercise still reveals the estate that must receive policy.

Next count managed devices and collectors. Separate browsers and desktop applications from IDEs and copilots. List OpenTelemetry sources and any agent-side component separately. State operating systems and deployment tooling. Record whether two devices used by one person consume one entitlement or two, but do not assume either answer.

The third population is AI interactions. Use realistic prompt and upload volume, not total web requests. Keep response inspection separate if it has a distinct event count. Add peak rate and retry behavior. Ask whether warnings and blocks affect consumption, and whether duplicate events do.

Fourth, inventory applications and accounts. Include sanctioned and unsanctioned tools, corporate and personal accounts, plus embedded copilots. Require the quote to identify any application-specific exclusions. The public catalog numbers help describe the platform, but only the signed coverage schedule can define the purchased scope.

Fifth, list agent and MCP objects. Include clients and servers, tools and connected systems, plus agent identities and tool calls. Record development and test separately from production. Ask how a renamed server or duplicate configuration changes the count, and how a short-lived local process changes it.

Sixth, price evidence and operations. Add the full prompt audit-log option and SIEM or SOAR export. Include retention and regional hosting, implementation and policy design, training and support, plus customer success and incident assistance. Finish with term and invoice schedule, taxes and renewal cap, plus termination export and deletion. The AI gateway architecture guide helps keep endpoint collection and model routing separate from MCP control in their actual positions.

A controlled trial should reconcile package claims

Run the trial with a ledger rather than a feature score. Each row should name the actor and device, application and account type, data fixture and action, expected policy and observed outcome, plus timestamp and retrieved evidence. Use fabricated records that cannot identify a real person or customer.

Test an approved browser AI tool and an unsanctioned personal account. Add a desktop app and an IDE copilot. For Command, install an approved MCP server and a disallowed one, then exercise read and write actions with synthetic content. Confirm whether the product observes the prompt and tool call, as well as the response and destination. Capture the exact policy and event record after each attempt.

Reconcile the event ledger with whatever quantity the quote uses. If a blocked prompt and its retry create two billed events, the worked invoice should show that rule. If one user appears through a browser and desktop app as well as an IDE, confirm whether those surfaces change the licensed count. Run one failure case with a collector offline and another with the policy service unavailable.

My preference is to make the vendor demonstrate one complete denied event, from identity through policy to retained record, before discussing a platform-wide rollout. That evidence exposes entitlement gaps faster than a long slide deck.

DeepInspect

DeepInspect evaluates authenticated HTTP requests deliberately routed from an application or agent to an LLM endpoint. It binds application-supplied identity and role to data class and model destination, plus policy version, then records the resulting per-request decision. Keep Harmonic's workforce and MCP package scope in its own quote, and price DeepInspect only against the governed model-request routes and evidence requirements it owns. Book a technical deep dive at deepinspect.ai.