\n","children":[{"type":"text","text":""}]},{"type":"mdxJsxFlowElement","name":"YouTubeVideo","children":[{"type":"text","text":""}],"props":{"videoId":"Ecv8dAwD2u0"}},{"type":"p","children":[{"type":"text","text":"Businesses have actually been building Data Apps for a long time."}]},{"type":"p","children":[{"type":"text","text":"These data-intensive applications power business intelligence or drive automated\nprocesses."}]},{"type":"p","children":[{"type":"text","text":"As more businesses become data-driven, they rely on Data Apps to power marketing\nplatforms, perform data monitoring and alerting, and enable large data sets to\nbe analyzed and visualized. Data Apps allow enterprises to leverage their\ninternal data and transform it into data-driven services to their customers."}]},{"type":"p","children":[{"type":"text","text":"Modern Data Apps combine predictive data with reasoning over richly\ninterconnected data."}]},{"type":"p","children":[{"type":"text","text":"They define business and data integrity rules to model a business domain to\nenable reasoning and autonomous action. They incorporate computed knowledge that\nis automatically and incrementally maintained."}]},{"type":"p","children":[{"type":"text","text":"You might be building a modern Data App if you are combining structured and\nsemistructured data sources."}]},{"type":"p","children":[{"type":"text","text":"Or if you are using complex data sources that are opaque to typical SQL\ndatabases, but are rich with knowledge that can be extracted with machine\nlearning."}]},{"type":"p","children":[{"type":"text","text":"For example, we see as input: knowledge extracted from PDFs ranging from\nscholarly articles to legal contracts."}]},{"type":"p","children":[{"type":"text","text":"Or knowledge extracted from drone videos that monitor industrial settings or\nenvironmental conditions."}]},{"type":"p","children":[{"type":"text","text":"Or knowledge and business rules extracted from legacy Java or C# code."}]},{"type":"p","children":[{"type":"text","text":"You might also be building a modern Data App if you are combining predictive\nanalytics with reasoning over business rules."}]},{"type":"p","children":[{"type":"text","text":"And if your objective is to augment human decision-making, or to create a system\nthat takes autonomous action."}]},{"type":"p","children":[{"type":"text","text":"At RAI, we believe Knowledge Graphs are the best foundation for Modern Data\nApps."}]},{"type":"p","children":[{"type":"text","text":"People navigate and reason through life with relationships, and Knowledge Graphs\nput facts and relationships in context to enable understanding and analysis."}]},{"type":"p","children":[{"type":"text","text":"You might want to build your modern Data App on the RAI platform …"}]},{"type":"p","children":[{"type":"text","text":"if you are deploying Knowledge Graphs and Ontologies that may grow to enterprise\nscale. Our Relational Knowledge Graph architecture is based on Graph Normal\nForm, or GNF, for open-ended scalability and with dovetail JOIN for performance."}]},{"type":"p","children":[{"type":"text","text":"You might want to use RAI’s platform if you require advanced reasoning involving\nrecursive algorithms and reasoning over complexly inter-related entities. We\nhave an expressive language, called Rel, with which to model your business\nentities and define rules and recursive logic. With Rel, you can define logic\nfor computed knowledge that is automatically updated as the underlying data\nchanges."}]},{"type":"p","children":[{"type":"text","text":"And you might want to use RAI’s platform if you envision multiple workloads, for\nexample analytics and reporting, against a single copy of your data, without\nduplication and synchronization. GNF enables full schema flexibility so that you\ndon’t need to reorganize your data for each workload."}]},{"type":"p","children":[{"type":"text","text":"This brings us back to the question of Why RAI for your Data Apps."}]},{"type":"p","children":[{"type":"text","text":"Use Knowledge Graphs to model your business, not just your data."}]},{"type":"p","children":[{"type":"text","text":"This enables your developers to speak the same language as your business people."}]},{"type":"p","children":[{"type":"text","text":"And an RAI Knowledge Graph can include computed knowledge, incrementally\nmaintained for business decisions guided by the latest knowledge."}]},{"type":"p","children":[{"type":"text","text":"Combine predictive data with reasoning over richly interconnected data. 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Data Apps · RelationalAI
Check out highlights of RelationalAI at Snowflake's Data Cloud Summit 2024!
Businesses have actually been building Data Apps for a long time.
These data-intensive applications power business intelligence or drive automated
processes.
As more businesses become data-driven, they rely on Data Apps to power marketing
platforms, perform data monitoring and alerting, and enable large data sets to
be analyzed and visualized. Data Apps allow enterprises to leverage their
internal data and transform it into data-driven services to their customers.
Modern Data Apps combine predictive data with reasoning over richly
interconnected data.
They define business and data integrity rules to model a business domain to
enable reasoning and autonomous action. They incorporate computed knowledge that
is automatically and incrementally maintained.
You might be building a modern Data App if you are combining structured and
semistructured data sources.
Or if you are using complex data sources that are opaque to typical SQL
databases, but are rich with knowledge that can be extracted with machine
learning.
For example, we see as input: knowledge extracted from PDFs ranging from
scholarly articles to legal contracts.
Or knowledge extracted from drone videos that monitor industrial settings or
environmental conditions.
Or knowledge and business rules extracted from legacy Java or C# code.
You might also be building a modern Data App if you are combining predictive
analytics with reasoning over business rules.
And if your objective is to augment human decision-making, or to create a system
that takes autonomous action.
At RAI, we believe Knowledge Graphs are the best foundation for Modern Data
Apps.
People navigate and reason through life with relationships, and Knowledge Graphs
put facts and relationships in context to enable understanding and analysis.
You might want to build your modern Data App on the RAI platform …
if you are deploying Knowledge Graphs and Ontologies that may grow to enterprise
scale. Our Relational Knowledge Graph architecture is based on Graph Normal
Form, or GNF, for open-ended scalability and with dovetail JOIN for performance.
You might want to use RAI’s platform if you require advanced reasoning involving
recursive algorithms and reasoning over complexly inter-related entities. We
have an expressive language, called Rel, with which to model your business
entities and define rules and recursive logic. With Rel, you can define logic
for computed knowledge that is automatically updated as the underlying data
changes.
And you might want to use RAI’s platform if you envision multiple workloads, for
example analytics and reporting, against a single copy of your data, without
duplication and synchronization. GNF enables full schema flexibility so that you
don’t need to reorganize your data for each workload.
This brings us back to the question of Why RAI for your Data Apps.
Use Knowledge Graphs to model your business, not just your data.
This enables your developers to speak the same language as your business people.
And an RAI Knowledge Graph can include computed knowledge, incrementally
maintained for business decisions guided by the latest knowledge.
Combine predictive data with reasoning over richly interconnected data. Leverage
these relationships for better predictions and deeper insights.
Operate at any scale, from prototype to enterprise.