Black Forest Knowledge Infrastructure: The Platform Layer

Black Forest Knowledge Infrastructure™ (BFKI) is a multi modal engine and infrastructure baseline built on top of the core Black Forest technology. It exists for deployment efficiency, scalability and the integration of structured and unstructured data.

Think of Black Forest as an onion. Black Forest Database is the core, and BFKI is the layer around it. The database can be deployed on its own, but most organisations need data management, governance, access control and an architecture that is more than a database.

The platform is containerised and orchestrated with Docker, Kubernetes and Terraform, giving an enterprise baseline that is secure by design, edge deployable, single stack, scalable and fault tolerant.

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The layers of Black ForestCONSUMERSanalysts · applications · third party tools · AI models and agentsBFKI · PLATFORMIngest pipelinesFusionDashboardsOpen APIsSecurityCatalog and historianBFDB · the database coreO(1) index · graph, vector, time series, relationalZero trust foundation, secure by design and memory safe
Fused
Knowledge graph, vector, keyword and unstructured retrieval in one operation.
Single stack
Secure by design, edge deployable, scalable and fault tolerant.
Petabyte
Enterprise knowledge graphs and retrieval augmented generation at scale.

Fused Retrieval At Petabyte Scale

Answers rarely live in one place or one format. BFKI retrieves across knowledge graphs, vectors, keywords and unstructured content in a single fused operation.

Enhanced SPARQL query functionality serves knowledge graphs, external ingest pipelines bring in third party applications, and dedicated modules generate context for generative AI. This is what makes enterprise knowledge graphs and retrieval augmented generation practical at petabyte scale.

Around that sit the services an enterprise deployment needs: query scalers, tiered storage, a catalog and historian, enterprise management, and security models with searchable encryption inherited from the engine beneath.

Platform services
What BFKI adds above the database
The orchestrated layer that turns a database engine into an enterprise knowledge platform.
Enhanced SPARQL
External ingest pipelines
GenAI context modules
Query scalers
Tiered storage
Catalog and historian
Security models
Searchable encryption
Docker, Kubernetes and Terraform orchestration
Edge · Local · Cloud

Architecture

BFKI is built around the O(1) index. An ingest framework and gateway feeds the analytics query engine and API gateways, with a catalog and historian organising data in low cost blob storage such as S3, and open interfaces to client applications and third party tools throughout.

Orchestration uses Docker, Kubernetes and Terraform, with a microservice architecture that is fault tolerant and scales horizontally and vertically on commodity hardware. Deployment is at the edge, locally or in any cloud.

The foundation is zero trust, secure by design and memory safe, with encryption in transit and at rest, fine grained access control and searchable encryption inherited from the engine beneath.

See the database beneath BFKI
One platform, end to endData sourcesSensors · transactions · cyber telemetry · logistics · intelligence · real time and historicalBLACK FORESTIngest frameworkindexed on arrivalO(1) query engineconstant time at any scaleOpen APIsREST · SQL · SPARQLLow cost hyperscale storagepetabytes kept hot, without the server clusterPeople, applications and AIanalysts · dashboards · third party tools · AI models and agents
Inside The Platform
Fusion, visualisation and native AI integration, open at every interface.
Data integration
Black Forest Fusion
Fuses events of different types from different sources into a single connected picture as data arrives.
API rich endpoints with an open systems approach to both ingest and retrieval.
Adapters including Kafka and Spark, JDBC drivers, WebSockets, and interfaces for Scala, JavaScript, SQL and Python.
Data visualisation
BFKI Dashboards
Time series and knowledge graph visualisation, with real time streaming and historical data in the same view.
Client side chart generation with HTML5 display, so dashboards deploy across devices without a native client.
Customisation without programming skills, with embedded support for third party tools and SQL access.
Artificial intelligence
Native AI integration
Native AI plugins, with dedicated modules that generate context for generative AI rather than bulk retrieval.
Retrieval augmented generation across knowledge graphs, vectors, keywords and unstructured stores together.
Source attribution and provenance carried up from the data layer, so model outputs can be traced.
Discuss how Black Forest applies to your organisation
Talk to our team about your data, your environment and the decisions you need to make faster.
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