KAI
- Company typePrivate
- Founded2026
- HeadquartersVersailles, France
- Headcount1–10
- GTM typeB2B
- OfferingSoftware
KAI firmographics
Firmographics- 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
KAI industry classification
Industry- 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
Where KAI is headquartered
LocationHeadquarters
- HQ city
- Versailles
- HQ country
- France
- HQ region
- Europe
Offices1 record
Markets served
KAI business model
Business model- GTM type
- B2B
- Offering type
- Software
- Cost components
- Personnel, Technology or R&D, Marketing or Sales, Operations, Infrastructure
Revenue model
- 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
| Model | Billing | Price |
|---|---|---|
| Subscription | Annual | Per instance and volume-based pricing |
Go-to-market motion1 record
Distribution channels5 records
Marketing channels6 records
KAI product offering
Product offeringCore 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
Companies that use KAI
Customer profileNamed customers11 records
Segments1 record
Ideal customer profiles2 records
KAI technology and API
TechnologyTechnology focussed Yes
API detail
- Has API
- Yes
- API docs
- API detail
Core technology
AI maturity
App detail
Integration11 records
AI capability3 records
Feature4 records
KAI partnerships and signals
Strategic signalPartnerships
Six partnerships are on record, tiered core and minor.
- SnowflakecoreSnowflake Marketplace partnership - K-AI available as Native App. Documents remain in customer's Snowflake account with zero data movement, preserving security and compliance.
- Microsoft AzurecoreAzure Marketplace listing for K-AI deployment. Customers deploy in their Azure tenant with integrated Microsoft Customer Agreement billing and native Azure security compliance.
- AWScoreAWS Marketplace availability for K-AI. Deployment on customer AWS account with consolidated EDP billing and access to AWS ecosystem scalability.
- WavestonecoreWavestone is a co-builder of K-AI's milestones and roadmap. Serves as implementation partner for enterprise deployments.
- DevoteamcoreDevoteam is a co-builder of K-AI's milestones and roadmap. Serves as implementation partner for enterprise deployments.
- SensoHubminorPartnership 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
KAI competitors and assessment
Company assessmentBroad 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
KAI social profiles
Digital presenceKAI compliance and trust
Trust signalCompliance2 records
KAI financial estimates
Financial estimateRevenue estimate
Valuation estimate
KAI leadership team
Management profileNumber of profiles
Profiles2 records
KAI funding detail
Funding detailFunding overview
Funding rounds1 record
Investors1 record
Funding detail is available on the Subscription and Enterprise plan.Contact sales →
KAI M&A and investment
M&A and investmentM&A
Investments
M&A and investment is available on the Subscription and Enterprise plan.Contact sales →
Frequently asked questions about KAI
What does KAI do?
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.
Is KAI a public or private company?
KAI is a private company. It is classified as venture growth investor backed and is currently operating.
When was KAI founded?
KAI was founded in 2026. It employs 1 to 10 people.
Where is KAI based?
KAI is headquartered in Versailles, France, in the Europe region.
How does KAI make money?
One revenue line is on record: saaS Subscription - K-AI Instances.
Who are KAI's main competitors?
Broad incumbents on record are Collibra, M-Files, Box, Alation, Microsoft SharePoint, Notion AI and Atlan. Glean is listed as a direct peer. Emerging players are Hebbia and Sana.
Does KAI have an API?
Yes. K-AI exposes its functions via Model Context Protocol (MCP). One MCP endpoint per K-AI instance with OAuth authentication and scopes mirrored on user rights. Compatible with Claude Desktop, Cursor, Copilot Studio, and in-house agents. The MCP server exposes tools for document auditing (audit.list_conflicts) and retrieval (kai.search), with full RBAC inheritance and ACL preservation at paragraph level. Developer documentation is at k-ai.gitbook.io/knowledge-ai.
What industry is KAI in?
KAI's product category is Enterprise AI Document Governance Software. Its primary akta.pro industry code is HDAAAMAA, AI Governance, Risk & Compliance (GRC) Platforms, with a secondary code of HDAAAKAL, Audit, Explainability & Accountability Tooling (traceability, reporting). Its NAICS code is 513210 and its SIC code is 7370.