Why UBIX DataSpace: Great AI Requires Realtime Access to All Data

Let’s face it, we are all drowning in digital data with 149 zetabytes created in 2024 alone. So much so, that we need a team of specialized data scientists and analysts as well as a myriad of specialized business intelligence and analytic tools to even make simple decisions, let alone proper future-state modeling. Now we have the promise of AI to help sort this mess, but that requires reading the fine print. Specifically, where is the data coming from, how can the model ingest, contextualize and repurpose it, as well as mitigate model bias and ensure governance guardrails?

UBIX connects to data in source systems and data stores using a library of over 500 connectors. Built using lessons of consumer usability, DataSpace enables you to create live connectors with sources of data. Every connector uses UBIX’s data ingestion service that loads and simultaneously profiles data. The profile learns the data structure and data types, generates data shape statistics, and gains an understanding of the relationships between datasets, making it easy to understand and work within UBIX.

Enjoy user-friendly setup, advanced monitoring, and seamless instance management for data-driven success while simplifying and streamlining data storage, engines, and libraries with Kubernetes deployment.

Structured Versus Unstructured Data

In addition to generating profiles for structured data, UBIX profiles unstructured data such as text, audio, and video. These sources are automatically transcribed, object identified and then grouped and loaded into UBIX’s vector database through a RAG process to make all data immediately conversational.

Structured data ingested through connectors has already trained UBIX’s chat experience. The structure and context of each connector has been learned so questions can be asked of the data to generate reports, providing conversational generative analytics immediately.

APIs within the source systems are expressed as Action Agents within each connector. Action Agents – which enable recommendations to be communicated back to source systems – are accessible within AgenticSpace to drive automated workflow and intelligent automation.

DataSpace also has an MCP server that registers external systems and agents using MCP and A2A protocols to link external systems and agents to UBIX to be included in AgenticSpace automation.

The UBIX Difference

DataSpace integrates enterprise and external data into a big data analytics store that is optimized for analytics, enabling data in movement. DataSpace is a live data system that is constantly updated with changes from the source systems.

The Intelligent Cloud

• Manages the data volumes automatically.
• Replicating data across zones providing great redundancy and high availability.
• Enabling powerful two-way communication capability.

Entirely no-code interface gets to value faster

• Control data security for each connector and enable the use of varying policies and permissions.
• Democratize the data to enable roles, groups, or individuals to securely innovate using it without violating any security or privacy policies. These rights flow through all spaces of UBIX.
• User-friendly setup, advanced monitoring, and seamless instance management for data-driven success.

Instead of continuing down the path of proprietary solutions that require dedicated tools and resources, many are now evaluating an data intelligence cloud solution that leverages new advancements in GenAI, Reinforcement Learning and AgenticAI.

Deliver value in days or even minutes instead of months or years

A data intelligence cloud is a cloud computing platform that leverages to power of GenAI, Reinforcement Learning and AgenticAI to enhance its capabilities and transform data into usable information accessible by the average person starts with ensuring you have the right data to the right person at the right time in the right format. Starting with UBIX DataSpace makes that a reality.

UBIX provides the ability for an average business executive to “converse” with a machine using natural language (NLP) to get the analytics they need to gain actionable insights and make better decisions by inspecting hundreds of variables instantaneously from across all systems within the enterprise and combine that with data that is publicly available. 

Learning how GenAI and emerging advancements like Reinforcement Learning and AgenticAI can deliver on the promise of a data intelligence cloud for increasing levels of autonomy and enterprise impact. Download our free eBook titled “Solving the Problem of Data and Decision Making” to help better understand the nuances of emerging AI and AgenticAI concepts/technologies and offer a set of best practices for consideration to ensure digital transformation and business-led AI success. Or if you can spare 22 minutes for a mini–AgenticAI Readiness Workshop, you can contact one of our AI experts today.