ENTERPRISE CONTEXT LAYER

Make enterprise data agent-ready

Yarnit builds living, governed context layers that connect meaning, relationships, rules and evidence across the systems where your business runs.

Build Your Context Layer

Explore Contextual Intelligence

Trusted by marketing teams shipping across brands, markets and channels every week

WHY YARNIT

Built to solve the enterprise context problem

Yarnit brings together proprietary context technology, industry intelligence and hands-on engineering - the capabilities required to turn enterprise data into reliable context for AI.

Proprietary context technology

Yarnit Contextual Intelligence brings together Agentic RAG, Graph RAG, ontologies, context graphs and runtime context delivery as one foundation for enterprise AI.

Industry intelligence built in

Reusable vertical ontologies and domain models give us a strong starting point for entities, metrics, relationships and rules - then adapt to the language and operating model of each enterprise.

Forward deployed from data to agent

Our AI, data and product teams work alongside enterprise stakeholders to connect sources, build meaning, establish governance and put the context layer into use across real agents and applications.

HOW IT WORKS

How we make enterprise data ready for AI

Start with what the AI needs to accomplish, then give it the data, meaning and controls required to do so reliably.

Understand what the AI needs to know

Identify the questions, decisions and actions the AI must support. Establish the business terms, information, rules and evidence it needs to perform that work.

Diagram showing data flow from Agents, Developers, and Users into a container labeled with Developers Data, Agents Data, Users Data, and Resource Data.

Connect and enrich enterprise data

Bring together data from warehouses, databases, documents and enterprise applications. Use AI to add descriptions, classifications and other missing context.

Illustration of a document icon labeled 'Doc.x' surrounded by four circular icons with abstract symbols, all on a light background with browser window controls visible at the top left.

Teach AI the meaning and relationships

Define what important entities and metrics mean, how they connect and which sources are authoritative. This creates a shared understanding of the business across systems.

Browser window mockup showing a process with 'Searched' for 'Stripe founders' and 'Read' items including Reteropiea, Jhumpy, and Default media, with options for Competitors and Q1 Web Traffic.

Deliver trusted context when it is needed

For every request, assemble the right information, definitions, relationships, permissions and evidence. Continuously update the layer as data and business rules change.

Dashboard interface showing a data table with columns Title, Project, and Deadline, listing sample data testing, pro data example, data strategy, and analytics project with respective tags and due dates.

CORE CAPABILITIES

Everything required to make enterprise data agent-ready

Combine data enrichment, business meaning, connected relationships and runtime governance in one reusable layer.

AI-assisted data enrichment

Generate descriptions, tags, classifications, relationship candidates and structured metadata from databases, documents and existing usage patterns.

Business glossaries and vertical ontologies

Define the enterprise vocabulary, entities, properties, relationships and business rules agents require, accelerated by reusable industry ontologies.

Context graph engineering

Connect data, documents, entities, decisions and evidence into graphs that reveal how information relates across systems and domains.

MAKE ENTERPRISE CONTEXT REUSABLE

Give AI the operating context of your enterprise

Start with one priority agent, decision or workflow. Yarnit will help you transform the data, meaning and relationships behind it into a living, governed context layer.

Build Your Context Layer