Scale vs. Supervisely Comparison Chart

Derive insights from your images in the cloud or at the edge with AutoML Vision or use pre-trained Vision API models to detect emotion, understand text, and more. Google Cloud offers two computer vision products that use machine learning to help you understand your images with industry-leading prediction accuracy. Automate the training of your own custom machine learning models. Simply upload images and train custom image models with AutoML Vision’s easy-to-use graphical interface; optimize your models for accuracy, latency, and size; and export them to your application in the cloud, or to an array of devices at the edge. Google Cloud’s Vision API offers powerful pre-trained machine learning models through REST and RPC APIs. Assign labels to images and quickly classify them into millions of predefined categories. Detect objects and faces, read printed and handwritten text, and build valuable metadata into your image catalog.

Dialogflow from Google Cloud is a natural language understanding platform that makes it easy to design and integrate a conversational user interface into your mobile app, web application, device, bot, interactive voice response system, and so on. Using Dialogflow, you can provide new and engaging ways for users to interact with your product. Dialogflow can analyze multiple types of input from your customers, including text or audio inputs (like from a phone or voice recording). It can also respond to your customers in a couple of ways, either through text or with synthetic speech. Dialogflow CX and ES provide virtual agent services for chatbots and contact centers. If you have a contact center that employs human agents, you can use Agent Assist to help your human agents. Agent Assist provides real-time suggestions for human agents while they are in conversations with end-user customers.

Build, deploy, and scale machine learning (ML) models faster, with fully managed ML tools for any use case. Through Vertex AI Workbench, Vertex AI is natively integrated with BigQuery, Dataproc, and Spark. You can use BigQuery ML to create and execute machine learning models in BigQuery using standard SQL queries on existing business intelligence tools and spreadsheets, or you can export datasets from BigQuery directly into Vertex AI Workbench and run your models from there. Use Vertex Data Labeling to generate highly accurate labels for your data collection.

Get insightful text analysis with machine learning that extracts, analyzes, and stores text. Train high-quality machine learning custom models without a single line of code with AutoML. Apply natural language understanding (NLU) to apps with Natural Language API. Use entity analysis to find and label fields within a document, including emails, chat, and social media, and then sentiment analysis to understand customer opinions to find actionable product and UX insights. Natural Language with speech-to-text API extracts insights from audio. Vision API adds optical character recognition (OCR) for scanned docs. Translation API understands sentiments in multiple languages. Use custom entity extraction to identify domain-specific entities within documents, many of which don’t appear in standard language models, without having to spend time or money on manual analysis. Train your own high-quality machine learning custom models to classify, extract, and detect sentiment.

Speechmatics is the most accurate and inclusive speech-to-text API ever released. Speechmatics is the world’s leading expert in Speech Intelligence, combining the latest breakthroughs in AI and ML to unlock the business value in human speech. Businesses use Speechmatics worldwide to accurately understand and transcribe human-level speech into text regardless of demographic, age, gender, accent, dialect, or location in real-time and on recorded media. Combining these transcripts with the latest AI-driven speech capabilities, businesses build products that utilize summarization, topic and chapter detection, sentiment analysis, translation, and more. Speechmatics processes over 500 years of transcription worldwide every month in 50 languages and can translate 69 language pairs. Having pioneered machine learning in speech recognition, its neural networks consider acoustics, languages, dialects, multiple speakers, punctuation, capitalization, context, and implicit meanings.

From effortlessly managing a deluge of invoices across various channels including email, vendor portals, chats, and more to seamlessly integrating with all finance ERPs including Oracle NetSuite, SAP, QuickBooks, etc., Neil handles the entire AP process without human intervention. This means AP teams get to focus on strategic initiatives while most of the day-to-day AP tasks are performed automatically by Neil with accuracy more than 85%. Going beyond the traditional RPA and OCR-based automation, Neil leverages advanced ICR, AI-powered workflows, and real-time vendor communication to ensure accurate data extraction, efficient processing, and timely payments—resulting in happier vendors and better discount opportunities for the enterprise. With Neil on your team, achieve remarkable 90% straight-through processing (STP) rates, eliminate human errors, and optimize vendor relationships like never before.

IBM watsonx Assistant (Formerly Watson Assistant) is a market-leading enterprise conversational AI platform that allows you to build intelligent virtual and voice assistants that can provide customers with fast, consistent and accurate answers across any messaging platform, application, device or channel. Using artificial intelligence and large language models, watsonx Assistant learns from customer conversations, improving its ability to resolve issues the first time while removing the frustration of long wait times, tedious searches and unhelpful chatbots. Most chatbots try to mimic human interactions, frustrating customers when a misunderstanding arises. IBM watsonx Assistant is more than a chatbot. It knows when to search for an answer from a knowledge base, when to ask for clarity and when to direct users to a human agent for more assistance. And since it can be deployed in any cloud or on-premises environment – smarter AI is finally available wherever you need it.

QVscribe, QRA's flagship product, unifies stakeholders by ensuring clear, concise artifacts. It automatically evaluates requirements, identifies risks, and guides engineers to address them. QVscribe simplifies artifact management by eliminating errors and verifying compliance with quality and industry standards. QVscribe Features: Glossary Integration: QVscribe now adds a fourth dimension by ensuring consistency across teams using different authoring tools. Term definitions appear alongside Quality Alerts, Warnings, and EARS Conformance checks within the project context. Customizable Configurations: Tailor QVscribe to meet specific verification needs for requirements, including business and system documents. This flexibility helps identify issues early before estimates or development progress. Integrated Guidance: QVscribe offers real-time recommendations during the editing process, helping authors effortlessly correct problem requirements and improve their quality.

Product recommendations tailored to your customers' preferences in a fully-managed service. BytePlus Recommend draws from our expertise in machine learning to offer dynamic and targeted recommendations. Our industry-leading team has a track record of delivering recommendations for some of the world’s most popular platforms. You can learn from the data of your users to engage them better, and provide personalized suggestions based on granular customer behavior. BytePlus Recommend is easy to use — leveraging your existing infrastructure as well as automating the machine learning workflow. BytePlus Recommend leverages our research in machine learning to deliver personalized recommendations tailored to your audience’s preferences. Our experienced and talented algorithm team provides customized strategies that adapt to evolving business needs and goals. Our pricing is based on results from A/B testing. Optimization goals are determined based on business demands.

BigQuery is a serverless, multicloud data warehouse that simplifies the process of working with all types of data so you can focus on getting valuable business insights quickly. At the core of Google’s data cloud, BigQuery allows you to simplify data integration, cost effectively and securely scale analytics, share rich data experiences with built-in business intelligence, and train and deploy ML models with a simple SQL interface, helping to make your organization’s operations more data-driven.