IOblend
Agentic AI
inside ETL pipelines
Enrich structured data with unstructured information on the fly using Agentic AI
Embed AI agents directly into the ETL data pipeline.
Invoke a stored procedure that makes a specific LLM call to find and analyse an unstructured documents (e.g. PDF, emails, text messages, etc).
Extract relevant structured data and validate the output on the fly. Automatically quarantine exceptions for further processing and review.
Automatically plug the results into an ETL pipeline to perform transformations and enrichment.
All of this is event based and runs CDC.
IOblend by design allows implementation of all sorts of stored procedures, including AI Agents, using a templated Python script.
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See what makes IOblend so easy to work with your data
Our powerful in-built data management capabilities allow for robust processing of data.
Improve productivity, analyse more of your information and get to the insights faster
Data in never uniform or readily served
Data often does not come in a well-structured and organised shape. Data formats, quality, provenance and sources can be a maze to navigate before you can extract any useful insights from it.
You need to extract, transform and load it (ETL) in one way or the other to make useful decisions based on the data. Whether you do it in-warehouse or in-flight, you still need to bring the data together.
Processing of a vast amount of unstructured data is a daunting process on its own.
Improved insights with the power of GenAI
GenAI is all the rage now. Its capabilities are truly powerful and unlock a wide range productivity improvements, especially in the field of data analytics.
With IOblend, you can harness the power of any LLM model directly from the tool.
With a single tool, you can now mine unstructured documents for structured data, validate it on the fly and combine the data with other data on-the-fly. Automatically.
Gain better insights faster with IOblend
Save your SMEs many work hours of sifting through the contract information.
The AI models can validate the output in multiple steps all within the same pipeline. Any abnormalities will be flagged and quarantined for an SME to investigate.
IOblend improves security of the document handling as the access will now be more strictly controlled.
The information from the unstructured documents can be combined with the structured data from databases, etc. on-the-fly, removing the need for post processing in a staging layer.
This process can save significantly on manual processing, validations and ETL, while improving the reliability of the output. All automatically.
Would you like to learn more?
Let us help you bring your data together quickly and cost-effectively.
