Simplifying AI Applications: Amazon Bedrock Data Automation

As AI technologies continue to evolve, organizations are confronted with increasing challenges around development and implementation. The sophisticated learning models (LMs) that Generative AI relies on demand massive amounts of data, computational resources, and significant time for training and fine-tuning.

Developers also face significant challenges when using foundation models (FMs), as the basis for LMs, to extract meaningful data from unstructured assets–which are more complex, diverse, and harder to process, requiring even more time invested to test and optimize.

According to The State of AI in Early 2024 report, 70% of respondents say they experienced difficulties capturing value from the technology due to challenges with data, including dealing with a lack of quality training data, defining processes for data governance, and integrating data into AI models at speed.

There also remains an overwhelming concern about accuracy, bias, and AI governance. Organizations recognize that AI applications must be responsible, legal, ethical, and appropriate for commercial use to mitigate privacy violations and brand reputational risk.

According to the AI Governance: Balancing Policy, Compliance and Commercial Value report from global law firm DLA Piper, establishing and maintaining strong AI governance was the leading challenge in implementing AI for decision-makers across various sectors.

It is no surprise, then, that AWS has launched Bedrock Data Automation, or BDA, as a solution for simplifying and reducing risk associated with the development of AI applications.

Amazon Bedrock Data Automation (BDA) is a feature of Amazon Bedrock that lets developers automatically generate relevant insights from unstructured multimodal content such as documents, images, video, and audio to build GenAI-based applications.

Extracting insights from unstructured multimodal content traditionally required stringing together AI technologies, for example, natural language processing (NLP) for text, computer vision for images and video, and speech recognition for audio. This process also demanded significant time and resources to prepare and transform the data and pipelines to integrate diverse data types.

Today, solutions like Amazon Bedrock Data Automation massively simplify this process by automating the injection, transformation, and extraction of data and relevant insights.

In simple terms, Amazon Bedrock Data Automation takes a number of existing and new AI services, often in combination with new and existing learning & foundation models, to automate their application for key use cases. This eliminates much of the upfront setup, configuration, integration, and fine-tuning that implementing and scaling AI for advanced and customized use cases requires. 

Examples of relevant insights that can be extracted include “standard outputs,” like summaries of key moments in a video, the detection of explicit content in images or audio, explanations of graph or chart data, and more. 

Additionally, there is the option of “custom outputs,” which leverage customer-defined templates (including a list of fields to extra, data format, and other instructions) that specify output requirements using natural language or a schema editor. This empowers organizations with full control over output and makes integration of Amazon Bedrock Data Automation into existing applications simpler.

Amazon Bedrock Data Automation is the latest innovation in a long line of AI developments from AWS, designed to remove the complexities behind the application of AI in business functions across industries. By offering a variety of service and LM combinations, Amazon Bedrock Data Automation significantly reduces complexity and effort for partners like Tenovos and our mutual clients, enabling faster, more efficient adoption of AI-driven solutions.

Faster Time to Implementation

Amazon Bedrock Data Automation’s unified experience for developers streamlines the process of building and launching GenAI applications through automating the extraction, transformation and generation of insights for unstructured content. This ease of use means far less time and resources spent on data preparation, prompt engineering and more, and the ability to implement solutions–and deliver business value–faster.

Customization Capabilities 

“Custom outputs” allow developers to tailor the insights generated and extracted in the formats required by their systems and existing applications. Amazon Bedrock Data Automation makes customization simple and intuitive, ensuring that insights are aligned with specific organizational needs minimizing the manual effort and optimization traditionally required when customizing and scaling AI applications.

Cost Efficiency Without Compromising Accuracy 

Amazon Bedrock Data Automation provides top-tier accuracy at an industry-leading price point. Features such as visual grounding with confidence scores and hallucination mitigation ensure reliable insights. Reduced effort to manage multiple models, build data pipelines and optimize prompt engineering, BDA reduces both upfront and ongoing operational costs. 

By automating the generation and extraction of insights from unstructured multimodal content—including text, images, video, and audio—Amazon Bedrock Data Automation empowers organizations to seamlessly build innovative, more scalable, generative AI-based applications.

As with any added automation comes some reduced flexibility. More advanced AI applications seeking the use of custom LMs will require direct integration via more traditional approaches. 

Nevertheless, Amazon Bedrock Data Automation brings unprecedented promise in the simplification of AI applications. The ability to handle unstructured multimodal content with precision and efficiency makes it an ideal solution for businesses looking to expand their AI capabilities without increasing complexity.

Tenovos as a Amazon Bedrock Data Automation Launch Partner

Digital Asset Management (DAM) plays a critical role in the content supply chain and naturally serves as a system of record to help organizations organize and manage the content that feeds AI services like Amazon Bedrock Data Automation. A modern, extensible and highly performant DAM, such as Tenovos, is essential to support Generative AI / AI use cases and can be part of your process for prompt engineering and training via an intuitive user interface. 

Tenovos was selected by AWS as an Amazon Bedrock Data Automation “Launch Partner”. This means our team has had the esteemed honor of working closely with AWS both before and after the BDA launch to provide input to help optimize this new product for the market, underscoring our commitment to staying at the forefront of innovation and delivering modern solutions for our customers.

AWS re:Invent 2024 – Bedrock Data Automation Launch Presentation

While we are optimistic that Amazon Bedrock Data Automation and similar advancements will ultimately empower global enterprises to apply AI cost-effectively, the pace of change and innovation no doubt continues to rattle many boardrooms. 

With AI, as with most things in life, change can be a force for good–provided it is responsibly managed. And AWS, forging a future where AI not only drives innovation, but does so with robust governance and control, can certainly be seen as a positive evolution.  

After all, the value of innovation lies not only in its potential but in its ability to improve our lives–without introducing unnecessary chaos.