Company context
Acuvity acquired by Proofpoint on February 12, 2026; Proofpoint is privately held
Proofpoint says it serves more than 80 of the Fortune 100 and more than 10,000 large enterprises
Vendor research
Proofpoint AI Security / Acuvity
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.
Company scale
Established?
EstablishedA provider with at least $1B in annual revenue, at least 1,000 employees, or backing from an established owner.This is a company-maturity signal, not a product-quality rating.
?
EstablishedA provider with at least $1B in annual revenue, at least 1,000 employees, or backing from an established owner.This is a company-maturity 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.
- $12.3B known funding
- 1000+ employees
Research coverageCounts describe available public research, not product quality.View details
- Vendor statements
- 16 records
- Source-checked records
- 11
- Evaluation requirements
- 16 in this research model
- Unresolved requirements
- 7
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.
FoundedProofpoint founded in 2002; Acuvity founding year was not stated on the reviewed Proofpoint page
HeadquartersSunnyvale, California
OwnershipAcuvity acquired by Proofpoint on February 12, 2026; Proofpoint is privately held
Employees1000+
Capital and scaleOwned business
Proofpoint
- Known funding
- $12.3B
- Operating scale
- Proofpoint says it serves more than 80 of the Fortune 100 and more than 10,000 large enterprises
- Backing context
- Proofpoint platform investment following its acquisition of Acuvity; transaction value was not disclosed on the reviewed announcement
BUYOUT · $12.3B · 2021-06-01
Founders and leadershipBackground context
Current leadership and public filings provide more useful context for this company than historical founder information.
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
- Proofpoint founded in 2002; Acuvity founding year was not stated on the reviewed Proofpoint page
- Workforce scale
- 1000+
- Hiring activity
- Not displayed
A current count requires a retained, clickable source URL.
Open research questions
- Latest annual revenue and reporting period are not yet supported by a retained public source.
- A current hiring source is not available, so the count is not shown.
Company sources and research limits3 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 sourceProofpoint Acuvity acquisition announcementProofpoint announced the completed Acuvity acquisition and described the combined AI security scope and enterprise scale.Company sourceProofpoint AI Security platformProofpoint now positions an intent-aware AI security platform for people, agents, MCP, models, applications, and enterprise data.Company information sourceStored company websiteSupports 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.
Employee AI access and usage controlsCore product focusAI data protectionCore product focusAI application runtime protectionCore product focusAction-taking agent safeguardsCore product focusBrowser and extension controlsRelated coverageEndpoint AI application controlsRelated coverageAI gateway and tool-connection controlsRelated coverageAI asset and configuration securityRelated coverage
Buyer context
- Record Acuvity as Proofpoint product lineage and evaluate the currently marketed Proofpoint AI Security platform.
- Public evidence spans employee AI usage, agent intent, endpoints, browsers, Model Context Protocol (MCP) servers, local AI tools, custom models, and applications.
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 referenceCIS Critical Security Controls
- Requirements with public support
- 11
- Related requirements
- 11
- References
- 58
- Requirements with public support
- 11
- Related requirements
- 14
- References
- 71
- Requirements with public support
- 11
- Related requirements
- 12
- References
- 35
- Requirements with public support
- 11
- Related requirements
- 12
- References
- 71
- Requirements with public support
- 11
- Related requirements
- 13
- References
- 39
- Requirements with public support
- 11
- Related requirements
- 12
- References
- 39
- Requirements with public support
- 11
- Related requirements
- 12
- References
- 31
- Requirements with public support
- 11
- Related requirements
- 11
- References
- 27
- Requirements with public support
- 11
- Related requirements
- 13
- References
- 31
- Requirements with public support
- 11
- Related requirements
- 13
- References
- 25
- Requirements with public support
- 2
- 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.
- 03Approved AI usage monitoring
Approved AI workspace activity appears with user, workspace or tenant, model or provider, and timestamp.
- 04Approved AI usage monitoring
Prompt, model, or admin activity can be exported or correlated for the selected approved AI platform.
- 05Controls for unapproved AI use
A policy blocks, coaches, redirects, or contains a test interaction with an unapproved AI destination.
- 06Controls for unapproved AI use
The control event records policy reason, user, destination, action, and timestamp.
- 07Sensitive-data protection for generative AI
Sensitive prompt, response, or file test data is detected and classified during an AI interaction.
- 08Sensitive-data protection for generative AI
A policy redacts, blocks, coaches, or records the sensitive data event before it leaves the approved path.
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
No supporting claim foundInventory 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
Strong 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
Strong 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
Strong public supportProtect 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
Limited public supportDiscover, 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
No supporting claim foundAuthorize, 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
No supporting claim foundDiscover 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
Research incompleteVisibility, 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
Research incompletePublicly 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 16 source records. Open additional records only when needed.
Proofpoint claims discovery of AI tools active in the enterprise environment.
discovers every AI tool active in your environment
Proofpoint materials reviewed did not provide a public claim for embedded AI discovery across the business-application environment.
No quoted source text is recorded for this claim.
Proofpoint claims runtime inspection and audit-ready evidence for employee interactions with enterprise AI.
produces audit-ready evidence of every employee interaction with AI
Proofpoint claims context-aware policy enforcement over employee AI interactions at runtime.
enforces context-aware policies
Proofpoint claims real-time inspection of prompts, outputs, and agent workflows to identify and block sensitive-data exposure.
Enterprises can reduce sensitive data exposure by inspecting prompts, outputs, and agent workflows in real time.
Proofpoint claims AI visibility and enforcement across endpoints and web browsers.
from endpoints and web browsers to emerging AI infrastructure
Show 10 additional evidence records
Proofpoint claims runtime protection for custom AI models and applications developed or deployed within the enterprise.
protecting custom AI models and applications developed or deployed within the enterprise
Proofpoint claims governance, policy, audit evidence, and runtime context for enterprise AI usage and agent behavior.
govern every interaction
Proofpoint materials reviewed did not provide a public claim for adversarial testing or release assurance for AI systems.
No quoted source text is recorded for this claim.
Proofpoint claims security-posture checks for services in the AI supply chain at the Model Context Protocol (MCP) boundary.
checks the security posture of every service in the AI supply chain
Proofpoint claims authentication, content inspection, and approved-server registry controls at the Model Context Protocol (MCP) boundary.
enforces authentication and content inspection at the MCP boundary
Proofpoint claims runtime observability, anomaly detection, and transaction reconstruction across multi-step agent workflows.
runtime observability across multi-step workflows
Proofpoint materials reviewed did not provide a public claim for trust or policy enforcement between agents.
No quoted source text is recorded for this claim.
Proofpoint materials reviewed did not provide a public claim for non-human identity, service-account, secret, or workload credential lifecycle controls.
No quoted source text is recorded for this claim.
Proofpoint claims Model Context Protocol (MCP) authentication and approved-server registry controls but does not establish full agent identity lifecycle management.
maintains a registry of approved servers
Proofpoint materials reviewed did not provide a public claim for coding-agent, integrated development environment (IDE), CLI, workstation, skill, hook, or package-action governance.
No quoted source text is recorded for this claim.