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Lasso Security Pricing (2026): Public Pricing, AWS Marketplace Costs and Quote-Based Plans

Enterprise teams evaluating AI security platforms face a significant challenge: understanding what they will actually pay before committing to lengthy sales cycles. Lasso Security, an Israeli AI security startup founded in 2023, operates in a market where public pricing remains limited across much of the market, making cost comparisons difficult without direct vendor engagement. For organizations seeking predictable pricing for their AI agent governance infrastructure, understanding Lasso's quote-based approach and publicly available pricing anchors is essential for informed procurement decisions.

This article breaks down Lasso Security's pricing structure, documents the publicly available pricing anchors, explains what to clarify during the quote process, and provides practical guidance for enterprise teams evaluating AI security solutions in 2026.

Key Takeaways​

  • Lasso Security uses quote-based enterprise pricing with zero published rates on its website, requiring custom quotes based on deployment scope and requirements
  • AWS Marketplace reveals product-specific pricing: $50,000/year for Secured Gateway for LLMs, with additional usage fees at $0.01/unit, and $20,000/year for Lasso for Employees, with no additional per-unit fee listed
  • Public pricing remains limited across much of the AI security market, while Lasso provides product-specific pricing through AWS Marketplace despite not publishing dollar amounts on its primary website
  • Enterprise procurement requires sales-led demos and may include proof-of-value periods before contract finalization, with no self-service trial publicly documented
  • Lasso announced a $30 million funding round in September 2026 after previously raising a $6 million seed round in 2023; the company also reported more than 500% revenue growth without disclosing absolute revenue figures
  • Organizations evaluating AI governance costs should compare how vendors structure quotes, usage fees, trials, contract terms, and scaling costs rather than assuming all platforms publish fixed pricing tiers

Understanding Lasso Security's Pricing Model​

Lasso Security does not publish dollar amounts on its primary website. Its current platform is organized around a Discover, Assess, and Protect lifecycle spanning AI asset discovery, posture management, automated red teaming, runtime enforcement, and AI detection and response. Public sources do not disclose Lasso's complete quote formula or establish that these capabilities are priced as an all-or-nothing package.

What This Means for Buyers​

  • No self-service pricing calculator or estimator exists
  • Budget planning requires direct sales engagement
  • Cost comparisons across vendors demand parallel procurement processes
  • Initial budget approval may need placeholder estimates

The National Institute of Standards and Technology published the AI Risk Management Framework outlining governance considerations that inform how enterprises should evaluate security platforms. Understanding vendor pricing models is a critical component of this risk assessment.

Quote-Based Model Implications​

This approach creates both advantages and limitations:

Advantages:

  • Pricing tailored to specific deployment scope
  • Negotiation opportunities for larger commitments
  • Flexibility for unique enterprise requirements

Limitations:

  • Higher entry barriers for organizations wanting to start small
  • Extended procurement cycles before cost certainty
  • Difficulty benchmarking against market rates without multiple quotes

Public AWS Marketplace Pricing​

Lasso has multiple publicly listed AWS Marketplace offers. "Lasso for Secured Gateway for LLMs" is listed at $50,000 for a 12-month contract, with additional usage priced at $0.01 per unit. A separate "Lasso for Employees" listing is priced at $20,000 for a 12-month contract. These figures are product-specific AWS Marketplace prices rather than a universal entry price for the full Lasso platform.

Understanding the Usage Fees​

The $0.01 per unit additional charge compounds on top of the base subscription. For organizations processing significant AI traffic, this variable component can substantially increase total costs. Without published definitions of what constitutes a "unit," teams should clarify this metric during procurement.

What AWS Marketplace Listings Include​

AWS Marketplace patterns increasingly show vendors keeping their own marketing sites free of dollar amounts but listing prices where procurement teams search. This creates a two-tier transparency system where marketplace buyers see more pricing detail than direct website visitors.

Factors to Clarify During a Lasso Quote​

Lasso does not publicly document the formula used to generate private enterprise quotes. Buyers should clarify which product or workload is being priced, what usage is included in the annual commitment, how additional usage is measured, and whether deployment, support, or other services affect the quote. AWS Marketplace confirms a base-plus-overage model for the Secured Gateway for LLMs SKU, but it does not disclose Lasso's complete enterprise pricing formula.

Key Questions for Procurement​

Deployment scope:

  • Which product components are included in the quote?
  • What geographic or endpoint coverage is provided?
  • Are integration or professional services separate line items?
  • Does the quote cover cloud-only or hybrid deployment?

Usage metrics:

  • How is a "unit" defined for overage calculation?
  • What usage volume is included in the base commitment?
  • How are overages billed and invoiced?
  • What happens if usage significantly exceeds estimates?

Contract terms:

  • What is the minimum contract length?
  • Are multi-year discounts available?
  • What are renewal pricing protections?
  • How does pricing scale with organizational growth?

Enterprise Procurement Requirements​

Lasso does not publicly document a standard procurement timeline. Its website offers sales-led demos and a free targeted AI red-team assessment, while buyers should confirm directly whether a product trial, proof-of-value engagement, security review, or other procurement steps apply to their deployment.

Standard Enterprise SaaS Considerations​

Organizations should anticipate typical enterprise software procurement activities:

  • Initial discovery and requirements gathering
  • Technical evaluation and architecture review
  • Security questionnaire exchange
  • Legal review of MSA and DPA
  • Budget authority and approval process

This contrasts with platforms offering self-service trials or immediate deployment options. For organizations needing rapid deployment, extended procurement cycles represent a significant consideration.

Industry Context: AI Security Pricing Transparency​

Public pricing varies significantly across AI security vendors. Some disclose subscription prices and plan details on their websites, while others provide only marketplace pricing or require direct sales engagement. Lasso falls into the marketplace-disclosure category: AWS Marketplace publishes product-specific annual prices, but Lasso does not publish a comprehensive enterprise pricing structure on its primary website.

Market Consolidation Impact on Pricing​

The AI security market experienced significant consolidation in 2025, including four notable transactions:

  • Check Point acquired Lakera; the purchase price was not officially disclosed, although press reports estimated the deal at roughly $300 million
  • F5 acquired CalypsoAI for $180 million
  • SentinelOne acquired Prompt Security
  • Palo Alto Networks acquired Protect AI

This consolidation creates pressure on independent vendors to demonstrate pricing competitiveness without platform bundling advantages. Lasso's September 2026 funding positions them to remain independent, with reported enterprise traction despite pricing opacity.

For buyers, consolidation means acquired vendors may change pricing structures post-acquisition, independent vendors face pressure to prove standalone value, and platform bundling from large security vendors may offer cost advantages.

Total Cost of Ownership Considerations​

Beyond AWS Marketplace list prices, organizations should budget for several additional cost categories when evaluating total cost of ownership.

Implementation and Integration Costs​

Lasso does not publicly disclose standardized implementation fees, professional-services charges, or customer labor requirements. Buyers should request these items separately from subscription and usage pricing when calculating total cost of ownership.

Hidden Cost Factors​

Several factors can increase actual costs beyond initial quotes:

Usage overages:

  • Variable fees based on the $0.01/unit model
  • Unexpected AI adoption growth
  • Shadow AI discovery expanding scope

Feature additions:

  • On-premises deployment requirements
  • Additional endpoint coverage
  • Custom integration development

Compliance requirements:

  • Additional security certifications
  • Custom audit report generation
  • Framework-specific documentation

Alternative AI Governance Approaches​

For teams evaluating different pricing and deployment models, alternative approaches to AI agent governance offer different structures and timelines.

Pricing and Evaluation Models​

Pricing models vary across AI governance platforms. Some vendors use custom quotes based on team size and requirements with per-user licensing and platform fees that scale with usage and team size. Others may offer immediate access through trials that enable faster evaluation cycles.

Architecture Considerations​

Beyond pricing, organizations should evaluate architectural differences in how platforms deliver AI governance:

Gateway-based approaches:

  • Centralized management with access to a directory of 10,000+ MCP servers
  • SSO integration via Okta, Azure AD, Google Workspace
  • Tool-level permissions per role
  • SCIM group sync for access governance

Agent identity models:

Runtime security features:

Shadow AI Detection Approaches​

Different vendors use different methods for discovering unauthorized AI usage:

Lasso monitoring approach:

  • Covers browser-based AI usage as well as supported desktop and local agent environments
  • Supports monitoring and policy enforcement for tools including Claude Desktop, Claude Code, Cursor, Windsurf, MCP connections, and other supported AI applications
  • Uses multiple deployment and integration paths depending on the environment

Agent monitor approaches:

  • Hooks in Claude Code and Cursor report local activity
  • Captures file reads, bash commands, off-gateway MCP use
  • MDM-pushed configurations enable detect-and-block mode
  • Unified audit log across gateway and local activity

For organizations using coding assistants like Claude Code, Cursor, or GitHub Copilot, agent monitoring visibility beyond browser traffic becomes critical for comprehensive governance.

Compliance and Audit Requirements​

Enterprise compliance requires careful evaluation of vendor attestations and implementation details:

Baseline compliance considerations:

  • SOC 2 Type II attestation status
  • Framework support for HIPAA, GDPR, PCI-DSS
  • Data processing agreements and BAAs
  • Certification dates and renewal status

Advanced audit capabilities:

The Cybersecurity and Infrastructure Security Agency publishes AI security guidance that enterprises should reference when evaluating compliance alignment. Request specific documentation and verify certification dates rather than relying on compliance attestations alone.

Making Your Decision: Procurement Checklist​

Before committing to any AI security platform, use this checklist to ensure comprehensive evaluation:

Pricing clarity:

  • Documented base price or price range
  • Variable cost components defined
  • Usage metrics clearly specified
  • Scaling cost projections available
  • Contract term options documented

Deployment requirements:

  • Procurement timeline acceptable
  • Technical prerequisites understood
  • Integration complexity assessed
  • Resource requirements identified
  • Trial or POV period available

Feature coverage:

  • Shadow AI detection approach fits environment
  • Agent identity model meets security requirements
  • MCP data risk framework addressed
  • DLP integration compatible with existing tools
  • Audit capabilities meet compliance requirements

Vendor stability:

  • Funding and financial position evaluated
  • Customer references verified
  • Acquisition risk assessed
  • Support model understood
  • Roadmap alignment confirmed

A Modern Alternative: Mintive's AI Governance Platform​

Organizations seeking a different approach to AI governance should evaluate platforms that emphasize rapid deployment, clear evaluation paths, and architectural flexibility. Mintive offers an AI governance platform built around the MCP Gateway architecture, enabling enterprises to centrally manage AI agent access to tools and data while maintaining comprehensive security controls.

The platform provides several key capabilities that address common enterprise AI governance requirements:

Immediate evaluation and deployment:

  • 7-day trial with full feature access and no credit card required
  • Standard rollouts completing in 1 day to 3 weeks depending on policy complexity
  • Custom quotes based on team size with per-user licensing

Centralized AI agent management:

  • Directory of 10,000+ MCP servers for tool connectivity
  • SSO integration via Okta, Azure AD, and Google Workspace
  • Tool-level permissions configured per role with SCIM group sync
  • Per-agent credential management with OAuth 2.0 and independent rotation

Runtime security and monitoring:

  • Prompt injection detection and PII/secrets scanning via Mint Guard
  • Risky command blocking with configurable policies
  • DLP middleware integration for existing security tools
  • Agent monitor hooks capturing local activity in Claude Code, Cursor, and other coding assistants
  • Unified audit logging across gateway and local agent activity

Compliance and audit support:

  • SOC 2 Type II attested
  • SIEM export to Sentinel, Splunk, S3, and OTLP
  • Immutable logging with configurable retention
  • Cross-app access governance integration

For teams prioritizing rapid deployment, transparent evaluation processes, and architectural control over their AI governance infrastructure, Mintive provides an alternative approach to quote-based enterprise platforms. The platform addresses the full lifecycle of AI agent governance from discovery through enforcement while enabling organizations to maintain existing security tool investments through open integration architectures.

Frequently Asked Questions​

How does quote-based pricing compare to acquiring AI security through a larger platform vendor?​

Major security vendors increasingly bundle AI security into broader platform offerings that may provide cost advantages for organizations already using these platforms. Independent vendors maintain focus on AI security specifically, potentially offering deeper capabilities without platform bundling. The total cost comparison depends heavily on your existing security stack and whether consolidated vendor relationships provide strategic value beyond pure cost.

What happens to pricing if an AI security vendor is acquired?​

Post-acquisition pricing changes are common as acquiring companies rationalize product lines. Contract terms typically protect existing agreements through their term, but renewal pricing may change substantially. Organizations should negotiate multi-year contracts with pricing protections if acquisition risk concerns them and maintain awareness of alternative vendors as a procurement contingency.

Can enterprise AI security pricing be negotiated?​

Enterprise software pricing is generally negotiable, particularly for larger deployments or multi-year commitments. Factors that strengthen negotiation position include competitive alternatives under active evaluation, multi-year commitment willingness, reference customer potential, and significant deployment scale. Without published pricing tiers, assessing whether your negotiated price represents market value requires multiple vendor quotes.

How do usage-based fees compare to flat-rate subscription models?​

Usage-based pricing with per-unit fees creates variable cost exposure that flat-rate subscriptions avoid. For organizations with predictable AI usage, usage-based pricing may offer cost efficiency at lower volumes. For organizations experiencing rapid AI adoption growth, flat-rate models provide budget predictability. Model the usage component against expected AI traffic to understand total cost impact.

What compliance certifications should be verified before signing a contract?​

Request and verify SOC 2 Type II reports, review actual reports rather than just certification badges, obtain HIPAA Business Associate Agreements if handling PHI, confirm data processing agreements for GDPR compliance, and verify any industry-specific certifications your organization requires. Verify certification dates and ask about continuous monitoring practices during product updates or infrastructure changes.