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Every system
you run,
connected once.

Core platforms, databases, code, documents, and BI, read where they sit and mapped into one knowledge graph.

Request a demoBrowse all connectors

69 systems · 9 groups · first scan within hours

CONTEXTBASEone connected mapCREDENTIAL BOUNDARY · READ-ONLYQNXTSQL SERVERSNOWFLAKESHAREPOINTDBTPOWER BI

Separate systems. One connected map.

01 · Connections

Read it where it sits. Move what has to move.

ContextBase reads your data and its meaning in place. Data Pipelines moves the feeds, and each run’s metadata comes back to the map.

Data/ 32

Read your data where it sits

Read-only, with SQL. Nothing moves.

  • QNXT
  • Facets
  • HealthEdge
  • SQL Server
  • Snowflake
  • Databricks

Context/ 31

Read where the meaning lives

Code, documents, ETL, and BI.

  • GitHub
  • SharePoint
  • Confluence
  • dbt
  • Jira
  • Power BI

Feeds/ 6

Move the feeds healthcare runs on

Between you and your partners, by Data Pipelines.

  • 834
  • 837
  • NCPDP
  • Accumulators
  • Prior auth
  • Rosters

ContextBase · one knowledge graph

claims.claim_line · 41,208 rows · read-only

02 · Boundary

Credentials stay where you keep them.

We never handle a raw credential when we can avoid it. ContextBase sees only what your grants allow, over the route your network team picks.

Network routeTypical setup

  1. IP allowlisting
  2. SSH bastion
  3. AWS PrivateLink
  4. Azure Private Endpoint
  5. GCP VPC peering
  6. Site-to-site VPN
  7. Zero Trust / BeyondCorp

ContextBase

SELECT claim_id, plan_paidFROM claims.claim_header …

No secret in the session

  • claims_dw · SQL ServerIn scope
  • analytics · SnowflakeIn scope
  • hr_payroll · OracleNot granted

Identity federation. No secret crosses the wire. Demo data.

claims_dw · SQL ServerValidation · Demo data

  1. 1Networkwaiting
  2. 2Authenticationwaiting
  3. 3Permissionswaiting
  4. 4Functional testwaiting

Functional testIf it fails: adjusted with you

A real read query returns the right shape.

Each step is logged and timestamped.

03 · Validated

Every connection is tested before production.

Four checks, in order. When one fails, it names whose fix it is, down to the GRANT command. Your team gets the report.

Read the connection guide

04 · Catalog

Every connector, searchable.

The systems the connection guide documents, from SQL Server on-prem to the 834 file. Each one opens its page in the docs: what we need, and how the connection is validated.

Showing 69 of 69

Databases, lakes, and warehouses/ 29

Where structured data lives. Read in place with SQL.

Code repositories/ 4

Where data logic lives: procedures, models, and transforms.

Documents and files/ 7

Where unstructured knowledge lives, and informs what the data means.

ETL, ELT, and orchestration/ 7

Where transformation logic lives.

Data catalogs/ 4

Where data documentation lives.

Decision and work tracking/ 5

Where data decisions get documented.

BI and analytics/ 4

Where data gets consumed, read back for reverse lineage.

Core administration/ 3

The legacy platforms that run a plan’s business.

  • QNXTCore administration platform
  • FacetsCore administration platform
  • HealthEdgeCore administration platform

Healthcare feeds/ 6

Moved by Data Pipelines, in production for years.

  • Eligibility · 834Enrollment files between plans and partners
  • Claims · 837Professional and institutional claims
  • Pharmacy · NCPDPPharmacy claims and PBM exchange
  • AccumulatorsDeductible and out-of-pocket, between plans and PBMs
  • Prior authorizationAuthorization data between systems
  • Provider rostersSFTP and CSV files

05 · Questions

What your team will ask.

What is the difference between data and context connections?

Data connections read your databases, warehouses, and lakes in place with SQL. Context connections read where the meaning lives: code repositories, documents, ETL, catalogs, tickets, and BI. ContextBase joins both into one knowledge graph, so an answer knows what a column holds and where it is set.

Does our data have to move first?

No. ContextBase reads your systems where they sit, so there is no migration or centralization to do before the first answer. Data Pipelines is there when you do want to move data between systems.

How are credentials handled?

In this order of preference: identity federation, so no secret crosses the wire; your own secrets manager, read at runtime; or a secure, ephemeral transfer into Flume’s secrets manager. The goal is to never handle raw credentials when avoidable.

How long does a connection take?

It depends on the network route your team picks, from 1 to 2 days for IP allowlisting to 1 to 2 weeks for a site-to-site VPN. Once connected, the first scan completes within hours.

What if our system is not listed?

Tell us which system it is. The connection guide covers what we need from your infrastructure and security teams for any source, and Data Pipelines moves data over any protocol.

Who decides what ContextBase can see?

You do. It reads through the grants you set, and every connection is checked against the agreed scope before production. Data access is approved for a set window, and every query lands on the audit trail.

Connect your first system.

Pick the one your hardest question needs. Its first scan completes within hours, and the map starts there.

Request a demoWhat the map becomes

Know. Build. Learn. Repeat.

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