Just a few weeks ago, IBM announced an expansion to their embeddable AI software portfolio with the release of three containerized Watson libraries. This expansion allows our partners to embed popular IBM Watson capabilities, including natural language processing, speech-to-text, and text-to-speech into their applications and solutions. But what is embeddable AI, and what are its uses?
Embeddable AI is the first-of-a-kind suite of IBM core AI technologies that can be easily embedded within enterprise applications to serve a variety of use cases. Think of embeddable AI as an engine. Planes and cars both use engines to make them go, but each engine accomplishes its purpose in different ways.
The analogy doesn’t end there either, because just like with a car or plane engine, it’s much easier to use something pre-made than to construct one yourself. With embeddable AI, you get a set of flexible, fit-for-purpose AI models that developers can use to provide enhanced end-user experiences—like, automatically transcribing voice messages and video conferences to text.
Unfortunately, many organizations still struggle to find talent with the skills to build and deploy AI solutions into their businesses. So, it’s crucial for companies that want to add specific AI capabilities to their applications or workflows to do so without expanding their technology stack, hiring more data science talent, or investing in expensive supercomputing resources.
To address this, businesses have found value in embedding powerful technology using specific models to harness AI’s potential in the way that best fits their needs, whether it is through domain optimized applications to containerized software libraries.
IBM Research has added three new software libraries to IBM’s portfolio of embeddable AI solutions—software libraries that are not bound to any platform and can be run across environments, including public clouds, on-premises, and at the edge.
As a result, organizations can now use this technology to enhance their current applications or build their own solutions.
The new libraries include:
In addition to the libraries, the embeddable AI portfolio includes IBM Watson APIs and applications like IBM Watson Assistant, IBM Watson Discovery, IBM Instana Observability, and IBM Maximo Visual Inspection.
Embeddable AI libraries are lightweight and provide stable APIs for use across models, making it easier for organizations to bring novel solutions to market.
IBM partners are making use of embeddable AI in various ways and across different industries.
LegalMation, an IBM partner that helps the legal industry make use of AI and advanced technology, uses natural language processing to automate contract privacy. Contracts and agreements contain information that organizations want to be careful about. Usually, redacting information within a contract is a manual process involving a person going line by line to mark passages for redaction. Instead, LegalMation uses embeddable AI to create an automated solution. The legal company now uses a natural language processing tool to find and mark sensitive information automatically.
See how LegalMation also uses AI to reduce the early-phase response documentation drafting process from 6 – 10 hours to 2 minutes.
Language-training school ASTEX, based in Madrid, Spain, has seen student careers skyrocket after they completed its courses. ASTEX uses AI to streamline students’ onboarding experience, offer personalized learning plans and improve the program’s scalability by reducing its dependence on humans. IBM partner Ivory Soluciones connected ASTEX with IBM because of the tech company’s expertise in AI solutions. Working closely together, ASTEX, Ivory, and IBM developed the ASTEX Language Innovation platform on IBM Cloud® with IBM Watson® technology.
Call recording service, Dubber, uses speech-to-text, tone analyzer, and natural language understanding to capture and transcribe a variety of verbal exchanges. The solution, powered by embeddable AI, automatically translates phone calls and video conferences into text and assigns each conversation a positive, negative, or neutral value, depending on the call. Users can then mine the data using simple keyword searches to find the information they need.
Now, with the addition of the new software libraries, new and existing IBM partners can embed the same Watson AI that powers IBM’s market leading products with flexibility to build and deploy on any cloud in the containerized environment of choice.
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