KAI

Name

KAI

Legal name

K-AI

Website

https://k-ai.ai

Company type

Private

Founded year

2026

Operating status

Operating

Headcount range

1–10 employees

Ownership category

akta.pro rank

Product category

Enterprise AI Document Governance Software

NAICS

Software Publishers (513210), Software Publishers (51321), Software Publishers (5132)

SIC

Services-Computer Programming, Data Processing, Etc. (7370), Services-Computer Integrated Systems Design (7373)

akta.pro primary industry

AI Governance, Risk & Compliance (GRC) Platforms (HDAAAMAA)

akta.pro secondary industries

Audit, Explainability & Accountability Tooling (traceability, reporting) (HDAAAKAL), Responsible AI, Security & Privacy Platforms (Safety, Guardrails, PII) (HDAEANAG), Model Transparency, Explainability & Interpretability (XAI) (HDAAAMAB), Enterprise AI Governance, Risk & Compliance Platforms (Model Risk, Audit, Policies) (HDAEANAE)

Keywords

• Document knowledge platform
• Enterprise AI governance
• Semantic document audit
• RAG data quality
• Unstructured data cleansing

Headquarters

HQ city

Versailles

HQ country

France

HQ region

Europe

Offices1 record

Markets served

GTM type

B2B

Offering type

Software

Cost components

Personnel, Technology or R&D, Marketing or Sales, Operations, Infrastructure

Revenue model

1. SaaS Subscription - K-AI Instances: Pricing per K-AI instance (one domain knowledge base) and per audited volume. The logic is the inverse of classical ECM: customers do not pay to store, they pay to make documents activable. A typical deployment starts on one or two pilot domains, validates the KPIs, then expands by wave.

Pricing tiers

Go-to-market motion1 record

Distribution channels5 records

Marketing channels6 records

Core offering

K-AI provides a Document Knowledge Platform that sits between enterprise document sources (SharePoint, Confluence, ECM systems) and AI consumers, continuously auditing document estates for contradictions, duplicates and obsolescence. The platform uses a proprietary Neural Semantic Graph to detect cross-document conflicts that RAG and Data Catalogs cannot, exposing cleaned, RBAC-compliant knowledge via a Model Context Protocol server for AI agents.

Product overview

K-AI is a Document Knowledge Platform (DKP) — a new platform category that sits between document sources (SharePoint, Confluence, ECM) and AI consumers (teams, AI agents). The platform consists of three integrated products: K-AI Audit (document quality monitoring and conflict detection), K-AI Platform (RBAC administration and access control), and K-AI MCP (Model Context Protocol server for AI agent integration). Together, these products implement the DKP across three surfaces — Audit, Platform, and MCP — that operate five layers: Sources, Ingestion & Indexation, Semantic Document Layer (Neural Semantic Graph), Governance & Quality, and Exposition & Consumption. The platform is offered as a SaaS deployment, with native apps available on Snowflake, Azure, and AWS Marketplaces.

Differentiator

Problem solved

Functional benefit

Brands

• K-AI Audit: Continuously detects conflicts, duplicates and obsolescences across document bases.
• K-AI Platform
• K-AI MCP

Products and services

• K-AI Audit Continuous document audit console that detects conflicts, divergent duplicates, obsolescence and missing subjects across an enterprise's document base and equips Document Stewards to arbitrate with business experts. Used by enterprise document owners and stewards to monitor corpus quality.
• K-AI Platform Web RBAC administration console that composes the access model — groups, users, K-AI instances (knowledge bases) and business links between them — and ensures MCP retrieval fully inherits RBAC policy. Used by enterprise administrators to govern document access for humans and AI agents.
• K-AI MCP Model Context Protocol endpoint that exposes K-AI's document governance functions (audit and retrieval) as tools for AI agents and expert workflows, with OAuth authentication and scopes mirrored on user rights. Compatible with Claude Desktop, Cursor, Microsoft Copilot Studio and in-house agents. Used by AI engineers and AI agent builders.

Quantifiable outcome

• 32% of enterprise data is divergent duplicates - discovered in two weeks, resolved in six weeks
• +2 more outcomes

Named customers11 records

Segments1 record

Ideal customer profiles2 records

Technology focussed Yes

API detail

Has API

Yes

API docs

API detail

Core technology

AI maturity

App detail

Integration11 records

AI capability3 records

Feature4 records

Partnerships

Six partnerships are on record, tiered core and minor.

• SnowflakecoreTechnology or Integration · 1 February 2026Snowflake Marketplace partnership - K-AI available as Native App. Documents remain in customer's Snowflake account with zero data movement, preserving security and compliance.
• Microsoft AzurecoreTechnology or IntegrationAzure Marketplace listing for K-AI deployment. Customers deploy in their Azure tenant with integrated Microsoft Customer Agreement billing and native Azure security compliance.
• AWScoreTechnology or IntegrationAWS Marketplace availability for K-AI. Deployment on customer AWS account with consolidated EDP billing and access to AWS ecosystem scalability.
• WavestonecoreImplementation/ SI/ Consulting PartnerWavestone is a co-builder of K-AI's milestones and roadmap. Serves as implementation partner for enterprise deployments.
• DevoteamcoreImplementation/ SI/ Consulting PartnerDevoteam is a co-builder of K-AI's milestones and roadmap. Serves as implementation partner for enterprise deployments.
• SensoHubminorStrategic or Co-development PartnerPartnership between SensoHub and KAI to develop satellite TDI sensors. This appears to be a different KAI entity (defense industry context).

Scale indicators3 records

Recent moves6 records

Expansion highlights6 records

Broad incumbents

• Collibra: Enterprise data catalog and governance platform extending into unstructured data. K-AI explicitly lists Collibra in its competitive landscape as addressing structured data only while unstructured extension is still underway. Competes for the same data governance budget but lacks active document-quality cleaning.
• M-Files: Document management system with metadata-driven organization and AI capabilities. Listed in K-AI's integration set as a document source and a broader ECM incumbent adding intelligence features.
• Box: Enterprise content management platform with AI features (Box AI) layered on top. Listed by K-AI as an ECM/DMS competitor. Brings storage, ACL, and versioning but lacks the semantic contradiction detection layer.
• Alation: Data catalog and intelligence platform primarily focused on structured data, with emerging unstructured capabilities. Named in K-AI's competitive landscape. Overlaps in metadata, lineage, and stewardship for the document estate.
• Microsoft SharePoint: Enterprise content management platform bundled with Microsoft 365 and integrated with Copilot. Most dangerous incumbent given distribution scale and bundle economics. K-AI explicitly identifies it as the document source it indexes but where semantic governance is absent.
• Notion AI: Workspace AI assistant that consumes enterprise knowledge bases. Named in K-AI's AI workplace assistant competitive set. Comparable consumer-side retrieval but without upstream document-quality cleaning.
• Atlan: Modern data catalog with active metadata, lineage, and collaboration features. Listed in K-AI's competitive set as another incumbent in the data governance stack beginning to extend toward unstructured documents.

Direct peers

• Glean: Enterprise AI search and assistant platform that indexes workplace documents (SharePoint, Confluence, Drive) to power AI answers. K-AI explicitly positions against Glean as the semantic-layer upstream, arguing Glean ingests documents as-is rather than cleaning them first. Most directly comparable competitor in AI document consumption.

Emerging players

• Hebbia: AI document intelligence platform for knowledge work, focused on financial and professional services workflows. Comparable to K-AI in applying AI to enterprise document estates, with similar ICP of large document-heavy enterprises needing reliability over RAG-as-is approaches.
• Sana: Enterprise AI knowledge platform that indexes and serves organizational knowledge to AI agents and humans. Comparable to K-AI in targeting the same document-to-agent workflow, though with less emphasis on contradiction detection and ACL preservation at the chunk level.

Market position

Strengths5 records

Weaknesses5 records

Competitive moat6 records

Key risks6 records

Key highlights7 records

Customer concentration

• LinkedInlinkedin.com/company/kai-knowledgeai

Compliance2 records

Revenue estimate

Valuation estimate

Number of profiles

Profiles2 records

Funding overview

Funding rounds1 record

Investors1 record

Funding detail is available on the Subscription and Enterprise plan.Contact sales →

M&A

Investments

M&A and investment is available on the Subscription and Enterprise plan.Contact sales →

Frequently asked questions about KAI