Context for Enterprise AI

Turn enterprise knowledge into trusted context.

Qontexta discovers, models and governs enterprise knowledge, creating trusted context for AI, agents and people.

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AI doesn’t create understanding. Context does.

Enterprise Knowledge

Qontexta

Reliable AI

Why context matters

Your business already knows the answers. Your systems don’t.

Critical knowledge lives across data platforms, semantic models, repositories, dashboards, documentation and people. Qontexta turns those fragments into governed business context.

ERPCRMWarehouseDashboardsGitHubDocuments

Enterprise Knowledge

Trusted Context

Reliable AI

How Qontexta works

From intention to implementation.

Tell Qontexta what the business needs. It discovers the context, generates the semantic implementation and asks you to approve it.

Understand

Qontexta asks about your sector, department and business objective.

Model

AI proposes Domains, Metrics, Entities and Policies.

Govern

Existing knowledge is mapped, reviewed and approved.

Implement

Cubes, Measures and Dimensions are generated automatically.

Consume

AI, agents, BI and applications use the same trusted context.

Perspective

The same knowledge. Two perspectives.

Business sees meaning. Engineering sees implementation. Qontexta keeps both aligned without duplicating the model.

DomainCube implementation

MetricMeasure

EntityDimension

PolicyPolicy

Business Perspective

Profitability Domain

Trusted

MetricsGross Margin · EBITDA · Net Profit

EntitiesBusiness Unit · Product · Customer

PoliciesCertified · Restricted access

StatusTrusted

AI-first context creation

You describe the business. Qontexta builds the context.

Qontexta asks about sector, department and objective, then proposes the Domains and maps them to your existing semantic environment.

Discovers or maps existing Domains
Proposes Metrics, Entities and Policies
Analyses your repository and Data Platform
Generates Cubes, Measures and Dimensions
Prepares the pull request for approval

Qontexta Intelligence

“I want trusted financial KPIs for our management team.”

Business intent understoodFinance · Management reporting

Domains proposedProfitability · Revenue · Cash Flow

Repository analysed4 existing Cubes found

Data Platform mapped18 tables · 11 relationships

Implementation ready3 Cubes · 14 Measures · 9 Dimensions

Context Studio

Built for enterprise knowledge.

A calm, precise workspace where teams review, refine and govern AI-generated business context.

Context Studio / Profitability

Domain

Profitability

How the organization understands margin, contribution and financial performance.

BusinessEngineering

Metrics7

Entities6

Policies2

Cubes3

Metrics

How profitability is measured

Gross MarginGoverned business definition

Trusted

Contribution MarginGoverned business definition

Review

EBITDAGoverned business definition

Trusted

Net ProfitGoverned business definition

Trusted

Qontexta Intelligence

3 opportunities found

Two Metrics have similar definitions.

One Cube does not expose Customer.

A Policy is missing an owner.

Built for Enterprise

Governed by design.

Qontexta combines business clarity with engineering discipline.

AI-first

Intent starts the workflow. The product does the modelling work.

Human approval

AI proposes. Humans approve. Every decision remains auditable.

Semantic by design

Business meaning and engineering implementation stay aligned.

Git-native

Every change is versioned, reviewed and prepared as a pull request.

Developers

One trusted context. Every interface.

REST, GraphQL, SQL and MCP expose the same governed meaning to AI systems, agents, BI tools and applications.

RESTGraphQLSQLMCPSDKCLI

{
  "domain": "profitability",
  "metric": "gross_margin",
  "entities": ["business_unit", "product"],
  "status": "trusted",
  "available_via": ["rest", "sql", "mcp"]
}

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