Lanai

Name: Lanai
Brand: Lanai

AI Native

The Enterprise AI Interaction Observability Platform

Est 2024|Raised $10M

LinkedIn 3K|Website|FTEs 17|HQ Palo Alto, California, US

01Competitive Landscape

Narrative analysis

Potential strengths: - If the product effectively groups interactions into workflow categories and maps adoption and outcome patterns, it could provide a reporting layer oriented toward executive stakeholders and procurement decisions. Competitor strengths: - Microsoft Purview: Suited to organizations prioritizing compliance, auditability, eDiscovery, and retention within the Microsoft ecosystem and connected data sources. - Zscaler: Suited to organizations that require consistent policy enforcement on traffic and app access, including generative AI usage, where SSE/SASE approaches are already in place. - LangSmith / Arize / Langfuse: These vendors are typically stronger for engineering teams needing developer-level tracing, evaluation, and debugging, and they often provide more transparent published pricing for developer-focused use cases.

Adoption trends (public signals)

Large enterprise vendors have publicly delivered AI governance and risk features within their compliance offerings.
Vendors focused on network and security controls have been marketing AI security suites to address visibility gaps; this suggests continued vendor investment in the market segment.

	Lanai (withlanai.com)	Microsoft Purview	Zscaler (AI security / GenAI controls)
Starting Price	Not publicly listed (sales-led)	Varies by licensing; typically requires enterprise licensing discussions	Not published in simple terms; typically part of SSE/SASE licensing
Appropriate Fit	Enterprises seeking cross-tool AI workflow visibility and executive-level reporting on AI usage and impact	Organizations centered on Microsoft infrastructure needing audit/compliance and eDiscovery controls	Organizations using SSE/SASE patterns that need shadow AI discovery and policy enforcement at the network/application edge
Key Strength	Vendor framing focuses on business workflows and reporting on AI usage and outcomes	Deep integration with Microsoft ecosystem and compliance/audit primitives	Policy enforcement at scale across web traffic and cloud applications; operational controls for traffic and access
Key Weakness	Limited publicly available third-party evidence and case studies; endpoint agent approach raises privacy and deployment considerations; pricing not published	Can be complex to configure and may require additional work to cover non-Microsoft AI tooling comprehensively	Can introduce performance and operational complexity; customers sometimes report manageability challenges

01Competitive Landscape

Narrative analysis

Potential strengths:

If the product effectively groups interactions into workflow categories and maps adoption and outcome patterns, it could provide a reporting layer oriented toward executive stakeholders and procurement decisions.

Competitor strengths:

Microsoft Purview: Suited to organizations prioritizing compliance, auditability, eDiscovery, and retention within the Microsoft ecosystem and connected data sources.
Zscaler: Suited to organizations that require consistent policy enforcement on traffic and app access, including generative AI usage, where SSE/SASE approaches are already in place.
LangSmith / Arize / Langfuse: These vendors are typically stronger for engineering teams needing developer-level tracing, evaluation, and debugging, and they often provide more transparent published pricing for developer-focused use cases.

Adoption trends (public signals)

Large enterprise vendors have publicly delivered AI governance and risk features within their compliance offerings.
Vendors focused on network and security controls have been marketing AI security suites to address visibility gaps; this suggests continued vendor investment in the market segment.

	Lanai (withlanai.com)	Microsoft Purview	Zscaler (AI security / GenAI controls)
Starting Price	Not publicly listed (sales-led)	Varies by licensing; typically requires enterprise licensing discussions	Not published in simple terms; typically part of SSE/SASE licensing
Appropriate Fit	Enterprises seeking cross-tool AI workflow visibility and executive-level reporting on AI usage and impact	Organizations centered on Microsoft infrastructure needing audit/compliance and eDiscovery controls	Organizations using SSE/SASE patterns that need shadow AI discovery and policy enforcement at the network/application edge
Key Strength	Vendor framing focuses on business workflows and reporting on AI usage and outcomes	Deep integration with Microsoft ecosystem and compliance/audit primitives	Policy enforcement at scale across web traffic and cloud applications; operational controls for traffic and access
Key Weakness	Limited publicly available third-party evidence and case studies; endpoint agent approach raises privacy and deployment considerations; pricing not published	Can be complex to configure and may require additional work to cover non-Microsoft AI tooling comprehensively	Can introduce performance and operational complexity; customers sometimes report manageability challenges

Lanai

01Competitive Landscape

Narrative analysis

Adoption trends (public signals)

02Market Map

01Competitive Landscape

Narrative analysis

Adoption trends (public signals)

02Market Map