APIs & AI: Understanding AI APIs and Their Potential For Your Enterprise Legacy Systems

API AI adoption continues to skyrocket, underscoring the critical value of artificial intelligence in software development. 

From AI-powered security systems and invoice processing to AI-generated code, images, and text, AI can be integrated into various business operations to drive efficiency, innovation, and better user and customer experiences. 

For businesses that rely on enterprise legacy systems, integrating your applications with AI advancements is a top priority. However, these integrations often face challenges due to outdated architectures and incompatibility with modern AI-driven solutions.

With API AI adoption growing by 96% in 2023 compared to 2022, businesses that fail to follow suit will struggle to meet customer demands and optimize operational efficiency, reducing competitiveness, innovation, and growth. 

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This is where OpenLegacy comes in. By enabling seamless API integration with legacy systems, OpenLegacy ensures that enterprises can harness the power of AI without the need for complex reengineering efforts.

So, let’s discuss everything you need to know about AI APIs— what they are, the main types and solutions, the key benefits, and how you can unlock their potential to empower enterprise legacy systems.

What are artificial intelligence APIs?

Before we dive into artificial intelligence APIs, let’s quickly recap what an API is.

An application programming interface (API) is a software intermediary that establishes rules and protocols for how two different software programs communicate with each other. 

They facilitate secure, seamless data sharing, integration, and the creation of new, innovative solutions.

An artificial intelligence API enables developers to incorporate AI features into applications without needing to possess deep knowledge of AI algorithms or write extensive code. 

Leveraging powerful technologies, they bestow the applications with intelligent capabilities, such as facial recognition, sentiment analysis, and speech recognition.

However, integrating AI APIs into legacy systems can be a challenge. OpenLegacy simplifies this process by providing an automated, API-driven approach to expose and modernize legacy systems, making them AI-ready.

Main types of AI API

There are lots of different types of AI APIs, each with unique functionalities:

Computer vision APIs

Computer vision APIs use advanced machine learning algorithms to autonomously interpret and process visual media, such as photos, images, and videos. 

They can recognize faces, gestures, objects, and emotions, and they can perform real-time video analysis and content moderation. 

These abilities can be integrated into a wide range of applications to automate tasks that involve visual recognition, such as:

• Retail product tracking and label identification
• Security surveillance 
• QR-code scanning
• Automated product quality inspection
• Face anonymization
• Explicit content detection

Speech recognition APIs

Also leveraging machine learning, speech recognition APIs allow machines to understand, extract meaning from, and interact with spoken human language. 

They can convert speech into text transcriptions, detect sentiments, and respond to voice commands and queries, empowering voice-enabled software interactions across a range of accents and languages.

Speech recognition APIs can be embedded into applications to help businesses deliver convenient, personalized user experiences. 

Common use cases include:

• Customer service chatbots
• Virtual assistants
• Language translators
• Real-time voice transcription and sentiment analysis

Text APIs

Text APIs use natural language processing (NLP) algorithms to understand, analyze, and respond to text data. With the ability to automatically extract data and infer meaning from it, text APIs can streamline and automate tasks that require comprehending large volumes of text.

Some examples of functionalities provided by text APIs include:

• Keyword extraction
• Text summarization
• Sentiment analysis
• Language detection

For example, a text API could gauge positive and negative sentiments in customer testimonials and online reviews and analyze them for recurring topics and keywords. This provides you with a better idea of how customers feel about your brand. As a result, you can quickly respond to negative sentiments and pinpoint persistent customer issues.

Document parsing APIs

Document parsing APIs use optical character recognition (OCR) and NLP to extract and interpret data from documents like PDFs, resumes, passports, and invoices. 

These APIs are integrated into applications to automate document extraction processes, reducing human error and speeding up workflows. They scan and analyze documents to extract relevant information and convert it into a structured, usable format. 

Document parsing APIs can be applied to serve various use cases, including: 

• Invoice processing
• Contract analysis
• Form processing 
• Content management

Generative AI APIs

Generative AI APIs use machine learning algorithms to create new, original content. By analyzing patterns from large volumes of existing datasets and using prompted inputs as a guide, they can generate different forms of content. This includes articles, product descriptions, images, code, and videos.

McKinsey reports that the function for which generative AI is used the most is marketing and sales (34%), followed by product/service development (23%) and IT (17%):

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Within these functions, the most popular use cases are content strategy support, design development, and helpdesk chatbots respectively.

H3: Translation APIs

Translation APIs translate languages in real time to remove language barriers. They use NLP to read text written in one language and translate it into another language, facilitating global communications and operations that enhance customer experiences and business scalability.

For example, translation APIs can be used to build:

• Language translation tools
• Multilingual chatbots
• Multilingual websites

Benefits of AI APIs for legacy systems 

Leveraging AI API solutions makes AI functionalities and capabilities more accessible. That said, it can still feel like a daunting task when you’re navigating the incompatibility between legacy systems and modern technologies. So, is it worth it? 

Here’s how AI APIs can benefit legacy system modernization:

Faster integration and deployment

Migrating legacy systems to cloud platforms and generating modern APIs and AI-powered digital services from these systems is a top priority. Leveraging AI APIs to facilitate these tasks accelerates integration and deployment cycles. 

For example, technologies like AI-assisted discovery, documentation, and analysis identify legacy artifacts and dynamically document data models, dependencies, and service contracts. This eliminates manual errors, illuminates integration priorities, and speeds up integration design. 

OpenLegacy takes this further by automating the API creation process from legacy systems, ensuring rapid and standardized AI integration while minimizing complexity.

 Enhanced capabilities and accessibility

AI APIs enhance legacy system capabilities. They enable businesses to access advanced, modern AI advancements without changing their underlying systems. 

For example, legacy systems can be integrated with modern applications to automate repetitive processes and deliver real-time information to AI solutions. 

Because no extensive changes need to be made to the legacy system—and because the APIs can be used across platforms—your workforce doesn’t need to possess specialist AI knowledge to leverage these AI capabilities, improving accessibility. 

OpenLegacy’s platform ensures seamless API generation from legacy systems, reducing technical debt and making AI functionalities easily accessible without major IT overhauls.

Continuous improvement

As legacy systems become outdated, the need for continuous improvement is paramount. 

Instead of completely replacing your legacy systems and starting again from the ground up (which is risky and expensive), you can use APIs to access AI capabilities from your legacy systems. 

OpenLegacy’s API-first approach allows organizations to continuously enhance their systems, ensuring they remain competitive without the need for costly and disruptive system overhauls.

Examples of the best AI APIs

From giant AI platforms offering entire suites of tools to powerful, specialized solutions, let’s take a look at six standout API AI software solutions to see what they deliver: 

1. Amazon Web Services

Amazon Web Services (AWS) is a market-leading AI platform that offers a suite of machine learning AI APIs. 

There’s Polly, which can translate text into human-like speech. Amazon Lex builds natural language, AI-powered chatbots that can be integrated into applications. 

Rekognition can recognize faces and objects, as well as analyze videos. Textract can extract data from documents, including printed text, handwriting, and layout elements.  

But that’s only the tip of the iceberg; there are a range of further AI APIs to address different needs. This explains why AWS continues to be the market leader for cloud infrastructure at 31%, followed by Microsoft Azure and Google Cloud: 

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2. Microsoft Azure Cognitive Services

Microsoft Azure also offers a suite of AI APIs as part of their Cognitive Services. This comprehensive solution delivers computer vision, speech recognition, text analysis, and more, all in a tightly integrated, scalable solution. 

For businesses with Microsoft-based legacy infrastructures, Azure enables native, seamless API integration with other Microsoft services, which is a huge plus.

3. Google Cloud Vision API

Google is a top-tier API AI provider, with its Google Cloud Vision API offering powerful computer vision capabilities. With sophisticated image, document, and video recognition and analysis, the API can classify and label objects and landmarks for image-based search, perform OCR, and detect faces, facial features, and emotions.

The established reliability of Google Cloud Vision API makes it a solution that can be deployed confidently.

4. IBM Watson Speech-to-Text

IBM Watson’s Speech-to-Text API uses advanced AI technologies to transcribe audio into text with precision. Supporting multiple languages, it enables fast transcription to serve a variety of use cases, from customer self-service and live meeting transcriptions to speech analytics.

What makes IBM Watson one of the top AI-based APIs is its versatility. 

It offers out-of-the-box functionality as well as advanced customization. It has a range of impressive capabilities and features, such as language and acoustic training options,  low latency transcriptions for real-time speech applications,  and the ability to detect up to six individual speakers in multi-party conversations.

5. OpenAI GPT-4 API

OpenAI’s GPT-4 is the latest iteration in their series of text-generator APIs. Designed to expand the capabilities of text generators, GPT-4 can translate languages with accuracy, understand context, generate coherent, tailored responses, and even create original content like articles and code. 

This makes GPT-4 one of the top AI-based API tools for developing intelligent chatbots, writing code, and generating content from technical documents to marketing copy. 

6. Clarifai

Clarifai API stands out for its specialization in image and video recognition. Developers can use it to integrate state-of-the-art image and video recognition capabilities into their existing applications. 

Its use cases include security surveillance, personalized recommendation engines, and explicit content moderation.

Explore the potential of AI APIs for your legacy systems with OpenLegacy’s help

Despite their resilience, legacy systems are ingrained with numerous limitations. From compatibility issues to complex, obsolete architectures that lack agility, their challenges prevent them from integrating innovative modern technologies—like AI—as seamlessly as cloud-native systems. 

But that’s not to say enterprises using legacy systems have to miss out on AI. They also don’t have to perform expensive and disruptive full-scale cloud overhauls. 

With the help of OpenLegacy, you can unlock APIzation and make the first step toward making your legacy systems AI-ready.

Simplify and automate API creation from legacy systems, accelerating legacy system modernization and the integration of AI functionalities. Using AI-driven processes to automate API standardization, documentation, transformation, and conversion, OpenLegacy readies your legacy systems and APIs for AI capabilities.

Additionally, OpenLegacy works with your existing architecture, eliminating the need to replace or make extensive changes to your legacy systems. 

With auto-generated integration flows, no-code automations, and AI-assisted error handling and validation, you can maintain your original infrastructure to streamline the process while reducing the risk of errors and reliance on specialized skills.

Whether you want to deploy image recognition, voice-enabled communications, or document parsing via large AI API platforms or specialized solutions, OpenLegacy can help you create an AI-friendly architecture. 

Ready to begin your AI journey with APIzation? Request a demo with OpenLegacy today.

AI API FAQs

What is an AI API?

An AI API is a tool that enables developers to connect their software with AI services to integrate artificial intelligence capabilities into their applications without needing specialized knowledge. 

Examples of AI capabilities include machine learning, natural language processing, image recognition, and speech-to-text translation.

How do AI APIs work?

AI APIs work by providing developers with pre-built technology that acts as the intermediary between legacy applications and AI services. The developer sends a request to the API endpoint, and the API responds to the request with the desired result.

What are the benefits of APIzation via OpenLegacy?

APIzation via OpenLegacy eliminates modernization challenges by building a bridge between legacy systems and modern AI technologies. 

It creates an AI-ready infrastructure that unlocks benefits like fast API generation and deployment, cost-efficiency, minimized risk, and reduced complexity, unlocking access to advanced AI capabilities for businesses using legacy systems.