Compare Azure AI Language vs. BLOOM

Dialogflow by Google Cloud is a natural-language understanding platform that allows you to create and integrate a conversational interface into your mobile, web, or device. It also makes it easy for you to integrate a bot, interactive voice response system, or other type of user interface into your app, web, or mobile application. Dialogflow allows you to create new ways for customers to interact with your product. Dialogflow can analyze input from customers in multiple formats, including text and audio (such as voice or phone calls). Dialogflow can also respond to customers via text or synthetic speech. Dialogflow CX, ES offer virtual agent services for chatbots or contact centers. Agent Assist can be used to assist human agents in contact centers that have them. Agent Assist offers real-time suggestions to human agents, even while they are talking with customers.

IBM watsonx Assistant is a next-gen conversational AI solution—it that empowers a broader audience that includes non-technical business users, anyone in your organization to effortlessly build generative AI Assistants that deliver frictionless self-service experiences to customers across any device or channel, help boost employee productivity, and scale across your business. -User-friendly interface with drag-and-drop conversation builder and pre-built templates. -Out-of-the-box Large Language Models, Large Speech Models, Natural Language Processing and Understanding (NLP, NLU), and Intelligent Context Gathering, to better understand the context of each conversation in natural language. -Retrieval-augmented generation (RAG) for accurate, contextual, and up-to-date conversational answers around the clock, grounded in your company's knowledge base.

Multilingualize your content and apps with machine translation that is available in thousands of languages. The Translation API Basic Edition instantly translates your website or application texts into more than 100 different languages. The Advanced Edition offers dynamic results as quickly as Basic edition but also includes customization features. This is important when you are using phrases or terms that are unique to certain areas and contexts. The Translation API's pre-trained model supports over 100 languages, from Afrikaans through to Zulu. AutoML Translation allows you to create custom models for more than fifty languages. The Translation API glossary ensures that the content you translate is true to your brand. You only need to specify which vocabulary you would like to give priority to, and save the glossary in your translation project.

kama.ai's Designed Emotional Intelligence, kama DEI, truly understands the meaning and human impact behind your client or user's situation or inquiry the way we as people understand each other. Our Natural Language Understanding (NLU) technology, combined with our proprietary knowledge base, and our human value guidance algorithm supports true human-like understanding and inference behind the interactions with users. Our knowledge base content is easily 'programmed' in natural language, rated by human values, that we all understand, creating an ever expanding Virtual Agent that can answer questions for your clients, employees or other stakeholders. Conversation journeys deliver prioritized product and service information, directly the way your product or service experts or client practitioners want to communicate it. No data scientists or programmers are required. kama DEI Agents can 'speak' over our website chat interface, Facebook Messenger, smart speakers, or from within mobile applications. Ultimately, we help you get the right information, to the right people, at the right time, providing any-time client engagement, increasing your marketing ROI and building your brand's loyalty

AutoML Vision provides insights from images at the edge and cloud. Pre-trained Vision API models can also be used to understand text and detect emotion. Google Cloud offers two computer vision products, which use machine learning to help understand your images with an industry-leading prediction accuracy. Automate the creation of custom machine learning models. Upload images, train custom image models using AutoML Vision's intuitive graphical interface, optimize your models for accuracy and latency, and export them to your cloud application or to a range of devices at the edge. Google Cloud's Vision API provides powerful pre-trained machine-learning models via REST and RPC APIs. Assign labels to images and classify them quickly into millions of predefined groups. Detect faces and objects, read printed and handwritten texts, and add valuable metadata to your image catalog.

Voice and written support makes it easy to get answers. Based on your interests, history, and role, you will receive personalized and recommended results. Quaeris provides near-real-time data access for all data. Quaeris enhances your existing dashboards. To increase knowledge sharing and track performance, teams can share insights and pinboards. Ask questions in plain English. There's no need for keywords or queries. Our advanced AI engine transforms your inquiry to a database-ready language within seconds. Data is nothing without context, just like life. Our cognitive AI engine interprets search terms, interests, roles, and past history to provide ranks results that allow further exploration. You can easily add filters to search results to dig into the details and explore relevant questions.

PackageX OCR API turns any smartphone into an incredibly powerful universal label scanner. It can read every bit of text, including barcodes, QR codes and other information on the label. Our OCR technology is the best in the industry. It uses proprietary algorithms and deep learning models to extract information from labels. Our OCR API has been trained using information from more than 10 million labels. This allows for the highest scanning accuracy in the market, at over 95%. Our technology can scan in low-light conditions and read labels from any angle. Create your own OCR scanner app to eliminate pen-and-paper inefficiencies. Our OCR scanner allows you to extract information from printed text or handwritten labels. Our OCR software is trained using multilingual label data extracted in over 40 countries. Detect and extract information from barcodes or QR codes.

By effortlessly handling diverse invoice formats from various channels and seamlessly integrating with your ERP system, Neil automates the entire AP process. This empowers your team to focus on strategic initiatives while Neil ensures accurate and timely invoice processing with an impressive 85%+ accuracy rate. Going beyond conventional RPA and OCR limitations, Neil leverages advanced AI and machine learning to extract critical data, optimize workflows, and maintain open communication with vendors. Result? 90% straight-through processing (STP), significantly reduced human error, strengthened vendor satisfaction, and overall optimized cash flow with better visibility and vendor discounts with timely payments.

QRA’s tools streamline engineering artifact generation, evaluation, and prediction, refocusing engineers from tedious work to critical path development. Our solutions automate the creation of risk-free project artifacts for high-stakes engineering. Engineers often spend excessive time on the mundane task of refining requirements, with quality metrics varying across industries. QVscribe, QRA's flagship product, streamlines this by automatically consolidating these metrics and applying them to your documentation, identifying risks, errors, and ambiguities. This efficiency allows engineers to focus on more complex challenges. To further simplify requirement authoring, QRA introduced a pioneering five-point scoring system that instills confidence in engineers. A perfect score confirms accurate structure and phrasing, while lower scores prompt corrective guidance. This feature not only refines current requirements but also reduces common errors and enhances authoring skills over time.

Fully managed ML tools allow you to build, deploy and scale machine-learning (ML) models quickly, for any use case. Vertex AI Workbench is natively integrated with BigQuery Dataproc and Spark. You can use BigQuery to create and execute machine-learning models in BigQuery by using standard SQL queries and spreadsheets or you can export datasets directly from BigQuery into Vertex AI Workbench to run your models there. Vertex Data Labeling can be used to create highly accurate labels for data collection.