AI Tool Profile
AppViewX Agent Identity Security: What It Does, Pricing, Use Cases, and Alternatives
AppViewX announced Agent Identity Security in private preview for discovering, governing, securing, and monitoring enterprise AI agents, credentials, MCP connections, models, and access paths.
Verification & Sources
- Evidence state
- Recheck due
- Source links
- 2
- Freshness
- Needs recheck: checked July 16, 2026
- Last updated
- July 16, 2026
What this evidence state means
- Definition
- The claim was previously checked, but its review window expired or a material change may have invalidated it.
- Required provenance
- The prior evidence and check date are retained, together with the expiry or change signal that triggered recheck.
- Owner
- Kingy freshness queue owner and assigned editorial reviewer
- Freshness rule
- This is already outside its freshness rule. It must not be presented as current until reviewed against current evidence.
- Disputes and corrections
- Use “Suggest a correction” on the record. Kingy editorial reviews the cited evidence, records material corrections, and changes or removes the state when it is not supported.
Key source checks
Suggest a correction
AppViewX Agent Identity Security: What It Does, Pricing, Use Cases, and Alternatives
Last updated: 2026-07-16
TL;DR
AppViewX Agent Identity Security is a private-preview enterprise product for discovering AI agents, governing their identities and access, and responding to policy violations.
What is AppViewX Agent Identity Security?
Agent Identity Security extends the AppViewX machine-identity platform to AI agents. AppViewX says the product discovers agents and maps their owners, credentials, MCP servers, models, and access relationships into an AI Bill of Materials.
The product is designed to apply lifecycle governance, task-based access rules, allowlists and denylists, runtime monitoring, and response controls to enterprise agent deployments.
What launched?
AppViewX announced Agent Identity Security on June 16, 2026. The company describes it as available in private preview for qualified enterprises, not as a generally available self-service product.
Key capabilities
- Discover managed and shadow agents across supported enterprise environments.
- Build an inventory of agent owners, credentials, MCP connections, models, and access paths.
- Apply task-based, least-privilege policies to agent actions and resource access.
- Monitor policy violations and anomalous behavior at runtime.
- Use response controls, including session termination, when an agent exceeds its approved access.
Pricing and availability
AppViewX does not publish a numeric list price for Agent Identity Security. Its official pricing page offers a custom quote based on the customer’s environment, scale, integration needs, and roadmap.
Access is through a demo or private-preview process for qualified enterprises. That availability constraint should be evaluated before treating the product as a near-term deployment option.
Who should consider it?
The intended audience includes CISOs, identity-security teams, PKI and machine-identity teams, and AI platform owners that need inventory, least-privilege governance, runtime controls, and audit evidence for enterprise agents.
What remains unproven?
Private-preview status means buyers still need to validate platform coverage, deployment effort, policy-enforcement depth, false-positive handling, incident response, and commercial terms in their own environment.
Official sources
- Agent Identity Security product page
- Official AppViewX announcement
- Official custom-quote pricing page
- AppViewX demo request
FAQ
What does Agent Identity Security do?
It discovers enterprise agents and their access relationships, then applies identity lifecycle controls, least-privilege policies, monitoring, and response controls.
Is it generally available?
No. AppViewX announced the product as a private preview for qualified enterprises.
How much does it cost?
AppViewX provides a custom quote based on environment, scale, integration requirements, and roadmap. No public numeric list price is published.
Related Kingy AI resources
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Tool Links
Launch History
AppViewX Agent Identity Security
AppViewX announced Agent Identity Security in private preview for discovering, governing, securing, and monitoring enterprise AI agents, credentials, MCP connections, models, and access paths.
- Launch readiness
- 6.6 / 10
- Demo evidence
- Not scored yet
- Creator-story fit
- Not scored yet
Score definitions and rubric
These are launch-record readiness heuristics, not product ratings.
Launch readiness
How complete and reviewable the launch record is, not the quality of the product.
Inputs and weights: Launch date 15%; qualifying source 10%; what launched 10%; demo 15%; category 10%; audience 10%; editorial assessment 10%; traction evidence 10%; creator or audience fit 10%.
Evidence inputs: Reviewed launch metadata, public source links, demo links, taxonomy, audience, editorial notes, and recorded traction signals.
Demo evidence
Whether the record contains useful, reviewable demonstration evidence; it is not a rating of product output quality.
Inputs and weights: Working demo URL 45%; video walkthrough 25%; clear description of what launched 10%; audience 10%; editorial assessment 10%.
Evidence inputs: Demo and video URLs plus the reviewed launch description, audience, and editorial notes.
Creator-story fit
Whether a launch has enough demonstrable evidence and audience relevance for a useful creator story; it does not predict views or guarantee coverage.
Inputs and weights: Demo evidence 25%; visual creator category 15%; audience 15%; editorial assessment 15%; traction evidence 10%; pricing clarity 10%; API or open-weight evidence 10%.
Evidence inputs: Reviewed demo, category, audience, editorial, traction, pricing, API, and open-weight fields.
- Scale
- 0.0–10.0. A present qualifying input receives its published weight; a missing input receives zero. Scores are rounded to one decimal.
- Assigned by
- Suggested by the deterministic field-completeness helper and assigned or approved by a Kingy editorial reviewer.
- Rubric and check date
- Rubric version P0-2026-08-10. The record’s “Last verified” date is the score check date. Checked: 2026-07-16.
- Confidence and missing data
- Confidence depends on source completeness. “Not scored yet” means no reviewed value; “Needs review” means the value or score set failed validation.
- Freshness
- Recalculate after a material launch, source, demo, pricing, audience, or traction change and during the record freshness review.
- Disputes
- Use “Suggest a correction” on the record and cite the relevant evidence. Commercial relationships cannot buy or alter a score.
AppViewX announced Agent Identity Security in private preview — discovering, governing, securing, and monitoring enterprise AI agents, credentials, MCP connections, models, and access paths…