GG - GraphGrail
MA - MS Azure
IW - IBM Watson
YT - Yandex.Toloka
DA - Dandelion API
- Don't have
- Need to buy
- Need to pay salary
- Need to order custom solution
|GraphGrailGG||MS AzureMA||IBM WatsonIW||Yandex TolokaYT||Dandelion APIDA|
|Platform easy of use, usability|
|Text targeting, API provided, crowd labeling data|
|Features: Ai components and algorithms|
|No programing: easy to use Ai-designer, drag-n-Drop interface to create your custom solution with components, ready to use algorithms, text classification, NEL|
|Easy solution integration with your business, full cycle|
|Full cycle solution, connect with any type of source (Social media, internal database), Pre-configured integration with data templates: chat-bot builder, classification, Import & Export data the way you want (JSON, email, etc.)|
|Blockchain and token economy to cut the costs|
|Transparent and honest blockchain-based marketplace datastore, blockchain-based quality checking for crowd data-labeling, automatic rating system for platform participants|
|Get more, pay less: ready to use workflows|
|Ready to use semantic categories||Need to buy||Need to buy||Need to buy||Need to buy|
|Typical business workflow automatization||Need to pay salary||Need to pay salary||Need to pay salary||Need to pay salary|
|Easy to customize solution||Need to order custom solution||Need to order custom solution||Need to order custom solution||Need to order custom solution|
|Monetization model||From 3000 queries per day, from $30 to $500 per month||From 2000 queries per day, up to $750 per month|
|Your business specific crowd labeling specialist on the platform|
The Ai-designer is like a set of building blocks, because it allows combining several typical NLP modules of the GraphGrail Ai platform in any sequence to create the solution you need without programming!
The GraphGrail Ai GAI Token is utility token and acts as internal currency in the system. The Tokens provide NLP end product businesses customers access to the system and the ability to quickly order and receive a solution, such as software development, or an application and data markup for it.
Tokens are paid to data markers for their work. Tokens are also paid to the testers and voters for the model - delegates, who monitor their quality and community. The balance of demand and supply of tokens on the platform is achieved due to flexible pricing - the payment to the participants of the platform is greater the more difficult the work on the markup of data.
The ecosystem is maintained by the supply/demand balance of services and orders from business clients. The more clients, the more people working on data annotation, the greater the scope of segments, each of which requires custom language models. To access the platform, a business representative must buy from 5,000 to 10,000 Tokens on the exchange. Thus, liquidity is withdrawn from free circulation. A business can spend the Tokens on purchasing internal services on the platform, such as data collection, cleanup, tagging, custom settings for training neural networks, etc. The more participants in the system and the more orders are placed in the marketplace application, the greater is the platform's benefit for business, providing long-term capital through the accumulation of valuable data and models for all parties, such as data taggers, businesses, and model merchants in the marketplace.
CEO and founder, Ai, Data-science.
Python developer, Django framework. Data-science specialist, NLP stack: NLTK + Celery + Pymorphy2 + GLRparser etc. Victor has more than 6 years of experience in development and deep learning. Experienced in Google TensorFlow
Venture investor, CMO.
Futurologist, angel investor, serial entrepreneur, founder of VentureClub, MyWishBoard, MyDreamBoard, and SuperFolder. Chief Dreams Officer and partner in Future Action, founder of crowd-investing platform VentureClub.ru. Alexander has solid business experience
Artificial General intelligence (AGI) is a system with the cognitive abilities of a human, capable of performing a wide range of tasks and to apply this knowledge to solving unfamiliar problems without preparation.
Artificial neural network (ANN) is a mathematical model, as well as its software or hardware implementation, based on the principle of organization and functioning of biological neural networks — networks of nervous cells of a living organism.
Computational linguistics (also: mathematical or computational linguistics) is a research area in the field of mathematical and computer modeling of intellectual processes in humans and animals for creation of artificial intelligence systems, which aims to use mathematical models to describe natural languages.
Computational linguistics partially overlaps with natural language processing. However, in the latter the emphasis is not on abstract models, but rather on applied methods of describing and processing language for computer systems. The field of activity of computational linguists is developing algorithms and applied programs for processing language information.
(Linguistic) annotation (tagging) is the process or result of assigning special labels to texts and their components. Linguistic annotation is one of the basic concepts of corpus linguistics. Annotation enables identifying texts according to different parameters, allowing carrying out a meaningful search in the corpus. Linguistic annotation as such is divided into: morphological (separation of affixes, compound words, etc.), lemmatization (specifying the original from for each word of the text), etc.