From 23f007cacfc9ead86e8e263cb28545ab631c87e6 Mon Sep 17 00:00:00 2001 From: Nishant Gupta Date: Tue, 3 Dec 2024 16:47:44 +0530 Subject: [PATCH 1/2] intro file --- .../Querent RIAN/intro.md | 32 +++++++++++++++++++ 1 file changed, 32 insertions(+) create mode 100644 independent-publisher-connectors/Querent RIAN/intro.md diff --git a/independent-publisher-connectors/Querent RIAN/intro.md b/independent-publisher-connectors/Querent RIAN/intro.md new file mode 100644 index 0000000000..15a0eb3bad --- /dev/null +++ b/independent-publisher-connectors/Querent RIAN/intro.md @@ -0,0 +1,32 @@ +## RIAN Power Platform Connector +The Querent’s Real-Time Information Aggregation Network (RIAN) solution transforms large private data workloads into a Data Fabric - a compact, graph based representation. This connector ingests data from data source(s) to enable knowledge discovery by creating linkages between data for insights, such as similarity searches and graph-based statistics. + +## Publisher: Querent AI LLC + +## Prerequisites + +- A self-hosted RIAN instance running on a Docker container or a Kubernetes cluster on the user’s infrastructure. +- Refer to the [Installation Guide](https://docs.querent.xyz/docs/get-started/installation/) for detailed instructions. + +## Obtaining Credentials + Contact [contact@querent.xyz](mailto:contact@querent.xyz) to request a license key. + +## Supported Operations + +1. **Configure Data Collection**: + Set up collectors to ingest data from sources such as local folders, email, real-time data streams, and cloud storage. + +2. **Data Handling**: + Read and process data from multiple file formats, including txt, json, xml, html, ppt, doc, pptx, and more. + +3. **Insight Generation**: + Perform similarity searches, graph-based statistics, and discover hidden relationships within the Data Fabric. + + + +## Known Issues and Limitations +- No internet transmission: All data processing occurs within the user’s infrastructure, ensuring privacy but requiring local resources. +- Insight generation is limited to the capabilities of the deployed RIAN version. + +## Frequently Asked Questions +- Please refer to the official [faqs documentation](https://docs.querent.xyz/docs/faqs/). \ No newline at end of file From 132d63f08ece23b2a2c434e48ead35c4fa6df2bc Mon Sep 17 00:00:00 2001 From: Nishant Gupta Date: Thu, 5 Dec 2024 09:17:28 +0530 Subject: [PATCH 2/2] final changes to intro --- .../Querent RIAN/intro.md | 31 ++++++++++++++----- 1 file changed, 23 insertions(+), 8 deletions(-) diff --git a/independent-publisher-connectors/Querent RIAN/intro.md b/independent-publisher-connectors/Querent RIAN/intro.md index 15a0eb3bad..a2ff3f0d0c 100644 --- a/independent-publisher-connectors/Querent RIAN/intro.md +++ b/independent-publisher-connectors/Querent RIAN/intro.md @@ -1,5 +1,5 @@ ## RIAN Power Platform Connector -The Querent’s Real-Time Information Aggregation Network (RIAN) solution transforms large private data workloads into a Data Fabric - a compact, graph based representation. This connector ingests data from data source(s) to enable knowledge discovery by creating linkages between data for insights, such as similarity searches and graph-based statistics. +The Querent’s Real-Time Information Aggregation Network (RIAN) solution transforms vast volumes of data into a Data Fabric - a compact, graph based representation. This connector ingests heterogenous data from data source(s) to enable knowledge discovery by creating linkages between data. ## Publisher: Querent AI LLC @@ -9,24 +9,39 @@ The Querent’s Real-Time Information Aggregation Network (RIAN) solution transf - Refer to the [Installation Guide](https://docs.querent.xyz/docs/get-started/installation/) for detailed instructions. ## Obtaining Credentials - Contact [contact@querent.xyz](mailto:contact@querent.xyz) to request a license key. + Contact [contact@querent.xyz](mailto:contact@querent.xyz) to request a license key for enterprise production use-cases. For research and development purposes a license key can be obtained from [here](https://www.querent.xyz/rian/). ## Supported Operations 1. **Configure Data Collection**: - Set up collectors to ingest data from sources such as local folders, email, real-time data streams, and cloud storage. + Set up collectors to ingest heterogenous data from various sources such as local folders, email, real-time data streams, and cloud storage. 2. **Data Handling**: - Read and process data from multiple file formats, including txt, json, xml, html, ppt, doc, pptx, and more. + Process data from different file formats, including txt, json, xml, html, ppt, doc, pptx, and more. Apply data transformation techniques, including normalization, tokenization, and feature extraction, to prepare the data for downstream processing. -3. **Insight Generation**: - Perform similarity searches, graph-based statistics, and discover hidden relationships within the Data Fabric. +3. **Data Fabric Modeling**: + Generates a data fabric that models contextually enriched relationships between data entities using attention scores from locally saved transformer models, allowing for advanced natural language understanding and insight discovery. +4. **Data Fabric Traversal for Knowledge Discovery**: + Users can perform graph traversal queries on the data fabric. This includes identifying top connections, exploring second-order relationships, and discovering latent trends within their datasets. +5. **Anomaly Detection and Predictive Analytics**: + Use locally saved and trained transformer models to extract attention scores for detecting anomalies and predicting outcomes in time-series or structured data. + +6. **Interactive Graph Representations**: + Visualize data fabrics with nodes and edges, highlighting connections and contextual relationships for interpretation and validation. + +7. **Extensible Integration**: + Export data fabrics and insights seamlessly to third-party analytics platforms or integrate with existing workflows. Built-in APIs make it easy to customize operations for domain-specific use cases. + +8. **Cross-Domain Applicability**: + Applicable to any domain, enabling users to tackle domain-specific challenges while maintaining consistent performance and accuracy. + +9. **Data Warehousing, Knowledge Management, and Versioning**: + Enable scalable data warehousing, robust knowledge management, and seamless versioning of insights. The connector ensures that processed data and generated insights are stored efficiently, allowing for easy retrieval, comparison, and iterative refinement over time. ## Known Issues and Limitations -- No internet transmission: All data processing occurs within the user’s infrastructure, ensuring privacy but requiring local resources. -- Insight generation is limited to the capabilities of the deployed RIAN version. +- No known issues. ## Frequently Asked Questions - Please refer to the official [faqs documentation](https://docs.querent.xyz/docs/faqs/). \ No newline at end of file