Knowledge Fabric · how it works

The estate is read in place — and becomes one knowledge graph.

What a data catalogue is to a warehouse — with two differences, and the second is the one that matters. The first: the catalogue makes no copy. A scheduled sync reads every asset in the platform and in the systems it is connected to where they live, samples their schemas, draws lineage between them, runs quality checks, snapshots the trend and raises alerts.

The second: a warehouse catalogue leaves the data flat — tables, columns, rows that only ever meet when someone writes a join. Here what those systems hold is resolved into one knowledge graph, and the same data becomes multi-dimensional: a customer, an account, a device, a wallet and a case are one object wherever they were read from, and that object now carries its relationships — the explicit ones the records state, and the inferred ones resolution and analysis derive, each with its basis and confidence. The estate stops being a list of assets and becomes a structure you can traverse: every screen — canvas, case, dialog, agency — reads that one graph. Human knowledge — descriptions, owners, tiers, domains, glossary terms, classifications — is layered on top and never overwritten.

The sync loop
1 · Discover

Assets

Workspaces → investigations → entity types; live graphs → sources; import datasets; evidence containers per case; the search index; every MCP server, hub category and enterprise connection.

2 · Sample

Schemas

Property schemas sampled from live nodes; field paths, types and sample values from streaming sources; tools as columns for connectors.

3 · Link

Lineage

Source streams live graph · import loads investigation · connector enriches investigation · evidence extracted into import · assets feed cases and graphs.

4 · Check

Quality

Built-in checks and your own read-only checks; the latest fail per asset is an incident with an owner; recent results kept for the trend.

5 · Record

Snapshot · alerts

A daily snapshot feeds the trend; alerts on quality failures or check errors go to a webhook or an inbox; assets that vanish are retired, never deleted.

Sync runs on a schedule under a lock and on demand from the page. Full-text search over every asset; the dialog can embed any Fabric section in a conversation.

The screens

Ten places, one estate.

Home · Explore · Lineage · Schema · MCP · Observability (data quality, incidents, alerts) · Insights · Domains · Govern (glossary, classifications, metrics) · Settings — every one of them reading the same state graph.

Home

The estate at a glance.

Data assets as cards, then estate statistics straight from the count store — entities, relationships, data size, connected systems, internal vs external, how many sources are access-controlled — each with a 14-day spark.

Underneath: overall data quality across the six dimensions, a status-of-connectivity grid with average latency and the sources that are offline, and requests to the knowledge graph per hour split by search, entity read, lineage and write.

KNOWLEDGE FABRIC · HOME
Home: requests to the knowledge graph per hour, by search, entity read, lineage and write.
Home. Load on the knowledge graph, hour by hour — search, entity reads, lineage and writes; Home also carries the data assets, estate statistics, quality by dimension and connectivity.
Explore

Every asset, its schema, its owner.

The left rail walks the estate by kind — sources, tables, datasets, feeds, containers, search indexes, APIs, pipelines, governance, domains, connectors — and the filter bar narrows by domain, owner, tags, tier, quality, service, source or parent.

Each card carries what the sync found (rows, freshness, a quality dot) and what a person added (description, owner, tier, domain, glossary terms) — human fields the sync never overwrites.

KNOWLEDGE FABRIC · EXPLORE
Explore.
Explore. Record imports, live feeds, containers and indexes with owners, rows and a freshness signal.
Lineage

Where a fact came from, hop by hop.

Lineage is discovered, not drawn. Feeds stream into monitoring graphs, record imports load investigations, connectors enrich subjects through proposals, evidence extractions become imports — each edge carrying what flowed and how much.

Pan, zoom and fit on a node canvas; follow a chain from a CSV that arrived this morning to the investigation it fed.

KNOWLEDGE FABRIC · LINEAGE
Lineage.
Lineage. Live feeds and record imports on the left, the datasets they produce in the middle, the knowledge graphs they load on the right.
Schema

The data model as it actually is.

Entity types with how many exist and the fields on their property form; relationship types from the count store; records and identifiers; and a schema graph of which type connects to which, sampled from the graph itself.

Built-in types and the ones your organization added in the Schema Builder sit side by side — add a type and its forms, canvas colours and agency tools follow.

KNOWLEDGE FABRIC · SCHEMA
Schema.
Schema. Entity types with counts and fields, relationship types, records and identifiers, the schema graph.
MCP

Connectors are assets too.

Connectors, tools exposed to the dialog and agencies, tools built into the hub and external servers — counted at the top, then every external MCP server with its status, tool filter, workspace scope and last check, and the built-in hub by category.

The enterprise connections you configure appear as assets with their host and family, never their secrets; lineage shows which investigations they have enriched.

KNOWLEDGE FABRIC · MCP
MCP.
MCP. External servers and the built-in hub, with tools, scope and status — keys held server-side.
Observability · data quality

Tests, not opinions.

Every check is a test case with its table, column, last run and status — run them all or add your own. The tiles count total tests, successes, aborts, failures, healthy assets and coverage; a failure becomes an incident that someone owns, and alerts fire to a webhook or an inbox.

Built-instale sources, unindexed evidence, import parity, orphan placeholders, freshness and completeness
Yoursany read-only query that returns a value, with a threshold
Incidentsnew → acknowledged → assigned → resolved, on the asset that failed
Alertson a quality failure or a check error, to a webhook or an inbox
KNOWLEDGE FABRIC · DATA QUALITY
Data quality: test cases with their table, column and last run.
Data quality. Test cases with their table, column and last run; above them, totals, failures, healthy assets and coverage.
Insights

Is the estate getting better?

Organization health at a glance — total assets, how many are described, owned and tiered — then the KPI charts with the days left to close each coverage target, and the total assets by kind over time from the daily snapshots.

Also app analytics: who is using which screens and which items are opened most, for the workspaces you manage.

KNOWLEDGE FABRIC · INSIGHTS
Insights.
Insights. Documentation and ownership coverage against their targets, and the estate's growth by kind.
Domains & Govern

Ownership, language, handling.

Domains are business groupings with owners, sub-domains, data products and the assets placed in them; coverage says how much of the estate has found a home. The glossary defines the terms your organization uses and links them to the assets that hold them, with an approval state on each.

Classifications are controlled tag sets — handling, PII, tier, provenance — and a classification ceiling on a connector withholds it from cases above that level, in the dialog and in agency runs alike.

KNOWLEDGE FABRIC · DOMAINS
Domains.
Domains. Business groupings with owners, sub-domains, data products and the assets placed in them.
Govern · glossary

One vocabulary, approved.

Terms with their description, synonyms, owner and approval state, and the activity feed of what changed. A term links to the assets that carry it, so "exhibit" or "live source" means the same thing to a person, a report and an agency.

KNOWLEDGE FABRIC · GLOSSARY
Glossary.
Glossary. Terms, synonyms, owners and approval state, linked to the assets that hold them.
Metrics

The health of the estate, as metrics you keep.

Each metric is a named check with a description, tags, glossary terms and an owner — "entities have a type", "evidence text extracted", "few placeholder nodes in live graphs", "import rows match records", "live feeds are fresh", "no stale duplicate candidates", "search index covers case records" — with its latest result.

Add your own; they run with the sync and feed the quality dimensions on Home.

KNOWLEDGE FABRIC · METRICS
Metrics.
Metrics. Named checks with description, tags, glossary terms, owner and the latest pass or warn.
Read in place

Named connections to the systems you already run.

PostgreSQL, MySQL, SQL Server, Oracle, Snowflake, BigQuery, Databricks, ClickHouse, Trino, Athena · MongoDB, OpenSearch, DynamoDB, CouchDB and graph databases · S3 and compatibles, Azure Blob, GCS, SFTP, HDFS, shares · Salesforce, ServiceNow, Jira, Zendesk, HubSpot, Dynamics, Entra, Google Workspace, Okta, Splunk, Datadog, Loki, Prometheus, Kafka, RabbitMQ, Airflow, GitHub, GitLab, Box, OData, REST — read-only tools over connections you name, plus a built-in hub of investigation tools and a catalogue of external MCP servers to register.

  • nothing migratedto catalogue them — queries run where the data lives, results are bounded. What AIState does keep is set out here.
  • one statementper call, read-only, comments and strings stripped before vetting
  • egress policyevery host checked; an air-gapped boundary still reaches private hosts
  • keys stay with youwrite-only, never shown again