Certiv

Name: Certiv
Brand: Certiv

AI Native

AI Agent Assurance for Endpoints. Visibility and control over every AI agent, so you can move fast and stay safe.

Est 2025|Raised $4.2M

LinkedIn 234|Website|FTEs 9|HQ Seattle, WA

Published Sep 19, 2026

01Common complaints

- Company sizes or stages where this product is overkill or insufficient - Early-stage startups without compliance pressure or minimal agent usage may find the solution disproportionate to need. - Industries or use cases where competitors are clearly more appropriate - If primary needs are developer-level debugging and quality evaluation of a single instrumented agent application, an app-instrumentation observability tool may be more suitable. - Technical requirements that this product cannot meet - If endpoint agents cannot be deployed via MDM or if administrative permissions on endpoints cannot be obtained, an endpoint runtime approach is likely infeasible. - Budget constraints that make alternatives more appropriate - If budget is constrained, alternatives to consider include enhanced policy/procurement controls for AI tools, improved identity and secrets management, network egress controls/CASB approaches, or developer observability tooling for specific in-house applications. - Specific workflows or integrations where the product may fall short - If critical agent actions occur primarily in cloud-hosted runtimes rather than on endpoints, an endpoint interception approach may not capture the full chain of activity. - Red flags in the buying process - Lack of a publicly accessible trust center or audit artifacts (SOC 2 report, pen test summaries, subprocessor lists) can increase procurement friction for regulated enterprises. - Vendor statements of complete visibility or capture capabilities should be validated in a short POC; inability to validate such statements is a procurement risk. - Current limitations acknowledged by the vendor - No explicit "known issues" list was found in public materials. - Features on the roadmap (not yet available) - Roadmap details and delivery timelines were not publicly documented. - Scale limitations - Not publicly documented. - Security or compliance gaps - No public SOC 2, ISO certification artifacts, or trust center disclosures were found; buyers should assume additional diligence will be required. - Technical debt or architectural limitations mentioned in reviews - Not available due to lack of a public review corpus. - API limitations or integration constraints - Vendor statements reference integrations with IAM, SIEM, SOAR, CI/CD, and GRC systems but do not provide detailed public documentation of supported protocols or integration patterns.

Deal disqualifiers: what makes a POOR fit

Policies that prohibit centralized capture of prompts or sensitive text from endpoints
Heavy BYOD environments where endpoint sensors cannot be mandated
Cases where only developer observability for a single instrumented application is required (observability tooling may suffice)

02Why they buy

- Competitive advantages validated by customer feedback - Not available due to lack of a credible public customer review corpus. - Unique features and capabilities identified from vendor materials - Vendor materials emphasize an endpoint runtime interception layer intended to operate without per-application configuration and to enable pre-execution enforcement of agent actions. - Differentiation from competitors based on reviews - Not available. - Value propositions with evidence from case studies - Not available; most current examples are vendor-provided illustrations. - Areas where competitors clearly have advantages (balanced view) - Competitors with established trust centers and published compliance artifacts may reduce procurement friction. - Architectures that centralize credential management can reduce certain bypass vectors, depending on deployment models and workflow constraints.

03Field reports

- Important constraint / market reality - Certiv is a recently launched vendor. As of mid-2026, major review platforms contain limited or no review volume specific to Certiv. - Review platforms (attempted) - Gartner Peer Insights: no Certiv listing or reviews surfaced in accessible content. - G2 / TrustRadius / Capterra: publicly accessible profiles or customer reviews for Certiv were not identified. - Community/Social - No substantive, product-specific Reddit or Hacker News threads were identified in accessible sources. - Some search results reference unrelated projects with similar names; these are not product reviews for Certiv.ai. - Direct quotes (limitations) - Credible end-user review content for Certiv was not found, so direct customer quotes were not included. - Available statements are primarily vendor quotes and press coverage paraphrases. - What customers likely choose Certiv for (inferred from positioning and typical buyer needs) - Discovery of unmanaged AI agents and tools on endpoints. - Pre-execution controls for actions initiated by agents, rather than only post-execution monitoring. - Endpoint-based contextual data to support enforcement and audit, compared with network-only approaches. - Why some customers might avoid or leave (inferred risk factors) - Concerns about privacy and developer trust if prompts or reasoning are collected centrally. - Potential endpoint performance overhead or stability impacts from an endpoint sensor. - Change-management complexity associated with blocking or approval workflows. - Limited public validation due to vendor maturity and early-stage status.

Public case studies

No public customer case studies with named customers and independently verifiable outcomes were found in accessible sources.

Vendor-published illustrative metrics and examples

The vendor’s product pages include illustrative environment metrics and a sample incident flow demonstrating pre-execution blocking of a simulated data exfiltration. These are presented as product examples and screenshots.

Critical evaluation

- Vendor statements, including claims of high visibility and capture of internal reasoning, should be treated as vendor claims until validated in a proof of concept (POC). Buyers should consider: - Coverage testing against both sanctioned and unsanctioned agents - Validation that any capture of sensitive reasoning aligns with applicable privacy and legal guidelines - Measurement of false positive and false negative rates for risky action detection

04Best fit

Company sizes: specific employee counts and revenue ranges

Likely best fit
- Mid-market to large enterprise organizations, or smaller firms with significant IP or regulatory exposure.
Less clear fit
- Very small startups unless operating under specific regulatory or customer requirements.

Industries and verticals where adoption is likely strongest

Likely verticals based on risk profile include:
- Financial services
- SaaS companies serving enterprise customers
- Healthcare organizations that must handle protected health information (would require HIPAA validation)
- Regulated or sensitive industries where endpoint governance is mandated (vendor materials reference critical infrastructure in broad terms; no proof was provided)

Roles and personas: decision makers AND end users

Decision makers
- CISO, Head of Security/GRC
- Head of IT / Endpoint Management
- VP Engineering / CTO for enablement and adoption considerations
End users
- Security engineers and detection/response teams
- IT endpoint administrators
- Developers affected by policy enforcement and monitoring

Pain points and challenges the product addresses

Unmanaged or shadow AI agent sprawl on endpoints
Lack of unified audit trails for agent actions and tool usage
Need to enforce least privilege and prevent agent-driven misuse or data exfiltration
Increasing audit workload as AI tools proliferate

Qualification criteria: what makes a GOOD fit

Large, heterogeneous endpoint fleets with widespread AI tool usage
A demonstrated need for runtime controls rather than log-only monitoring
Organizational willingness to deploy an endpoint sensor and manage associated change control

05The pitch

What the product does (core value proposition in objective terms)

- Certiv describes its offering as an AI agent assurance layer for employee endpoints (workstations). The platform is intended to provide: - Discovery/inventory of AI agents and AI tools on endpoints, including unmanaged or "shadow" AI tools. - Runtime monitoring and observability of agent activity, including the vendor-stated ability to correlate prompts, reasoning steps, and tool calls. - Pre-execution policy enforcement to allow, deny, or reroute actions before they execute on an endpoint or against downstream systems. - Audit and compliance evidence generation aligned to common frameworks. - The vendor describes an endpoint runtime-layer approach positioned between applications and the operating system, delivered via an endpoint component described as a sensor that mediates agent actions prior to execution.

Target market and market positioning

- Target buyers appear to be: - Security leadership (CISO / security engineering / GRC) responsible for governing agentic automation and reducing risk exposure. - Engineering leaders who require visibility into AI tool adoption, spend, and risk without significant friction to developer workflows. - IT teams responsible for endpoint fleet management (MDM-driven deployment and installed tool governance). - Positioning: - Vendor materials frame the offering as a category focused on "AI agent assurance" or runtime assurance for endpoints, adjacent to endpoint detection and response (EDR) and cloud access security brokers (CASB).

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