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  • Predict interactions between biological entities
  • Extract business insights automatically
  • Search relevant academic and industry documents
DELEGATE
SCIENTIFIC RESEARCH
AND COMPETITIVE INTELLIGENCE
Request Demo
Predict interactions between biological entities
Search relevant academic and industry documents
DELEGATE
SCIENTIFIC RESEARCH
AND COMPETITIVE
Request Demo
INTELLIGENCE
Extract business insights automatically
OUR PRODUCTS FOR
Drug discovery
Industrial biotechnology
Market research
Technology landscape scan
Key leaders ideas
Medical guidelines analysis
Clinical notes analysis
Disease mechanism
Phenotypes data analysis
Literature research
Target physiological function
Disease association
Target signalling
Target interactions
Toxicity analysis
Adverse effects analysis
Toxicity mechanism analysis
Drug repurposing
Key leaders ideas
Competitors analysis
Scientific articles analysis
Patents analysis
Clinical trials analysis
Disease origin
Drug effects
Business and Scientific Trends
Disease hypothesis
Target identification
Post-marketing
Tech reglaments analysis
Key leaders ideas
Technology landscape scan
Patents analysis
Scientific articles analysis
Organism selection
Pathway analysis
Genes selection
Gene-gene interactions
Search for product cleaning methods
Medium selection
Reviews analysis
Competitors analysis
Search for analytics approaches
Business and Scientific Trends
Producer selection and optimization
Cultivation and product cleaning
Post-marketing
Reviews analysis
Existence reports gathering
Competitors analysis
Target technologies
Target people
Target companies
Social media data
News collection
Scientific literature
Companies info
Key leaders ideas
Possible events prediction
Time-series forecasting
Statistical analysis
Key-data updating
Reviews analysis
Post-marketing
Analysis of data
Definition of opportunity
Sample specification
Data collection
Industry data analysis
MULTIPLE TOOLS
WITH
INTUITIVE SYSTEM
ONE
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available scientific articles, patents, and clinical trials.
the most accurate list of publicly
FIND
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proteins and drugs, identify targets, and analyze molecular pathways by using our comfortable Knowledge graph.
interaction between genes,
PREDICT
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PERFORM
Examples :
  • Johnson&Johnson - acquired - Momenta Pharmaceuticals, Inc
  • Hypoxia - activates - p53
textual data analysis
to retrieve biological and business insights from academic and industry documents
Planning
MVP
Planning
MVP
Planning
Planning
MVP
MULTIPLE TOOLS
WITH
INTUITIVE SYSTEM
ONE
available scientific articles, patents, and clinical trials.
the most accurate list of publicly
FIND
academic and industry data automatically, in a form of triplets.
(Example. Protein A - activates - Gene B)
knowledge from any
EXTRACT
proteins and drugs, identify targets and analyze molecular pathways by using our comfortable Knowledge graph.
interaction between genes,
PREDICT
PERFORM
  • companies collaborations
  • product launches
  • financial deals
Automatically, in a form of triplets.
(Example : "Company A - acquires - Company B".)
massive news analysis
and get insights about business events:
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Learn More
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3 types of documents
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Advanced graph search
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Automated knowledge extraction
Natural language detection
KEY
FEATURES
3 types of documents
Advanced graph search
Automated knowledge extraction
Natural language detection
Learn More
Learn More
Learn More
Learn More
KEY
FEATURES
HOW IT WORKS
HOW IT WORKS
Text2Knowledge
Semantic search
Graph Search
Text2Knowledge
Semantic search
Graph Search
Description
Text2Knowledge is the best solution for processing textual data. It automatically detects and extracts facts from the uploaded texts with biomedical or business context, like articles, patents, clinical trials, or news.

Facts are extracted in the form of relationships. Each relationship describes two entities(companies, events, genes, proteins, etc.) and their relation.
  • Example 1: "Protein A - activates - Gene B"
  • Example 2: "Company A - acquires - Company B"

You can quickly navigate to sentences in the texts, from which are extracted respective relationships, to analyze facts in the context.
Input
Upload your textual data using one of two options:
  • Paste a web link to the page with a text, for example, a link to an article. Our system will automatically export the text from the linked web page with textual data
  • Upload file in the following formats: PDF, DOCX, TXT, JSON, RTF, HTML
Results
The final result is a list of relationships (facts) that can be filtered in a customizable way, to allow you to find specific facts at the snap of a finger.

Because each relation is extracted from a sentence in the text, you can quickly jump to the sentences in the text that contain the facts you found.

The system determines the importance of query words, or their synonyms for each document in the database, checking their frequency and similarity with words in the documents.
Use cases
  • Finding companies collaborations and financial deals
  • Gene-disease associations
  • Events tracking
Technology
Text2Knowledge is based on linguistic analysis of texts by complex AI algorithms.

Open relations extraction with dependencies parsing yields precise recognition of relations between business and biological entities within the sentences.

The system provides you with infallible insights from any data due to unique semantic approaches.
Try MVP version
Request Demo
Description
Text2Knowledge is the best solution for processing textual data. It automatically detects and extracts facts from the uploaded texts with biomedical or business context, like articles, patents, clinical trials, or news.

Facts are extracted in the form of relationships. Each relationship describes two entities(companies, events, genes, proteins, etc.) and their relation.
  • Example 1: "Protein A - activates - Gene B"
  • Example 2: "Company A - acquires - Company B"

You can quickly navigate to sentences in the texts, from which are extracted respective relationships, to analyze facts in the context.
Input
Upload your textual data using one of two options:
  • Paste a web link to the page with a text, for example, a link to an article. Our system will automatically export the text from the linked web page with textual data
  • Upload file in the following formats: PDF, DOCX, TXT, JSON, RTF, HTML
Results
The final result is a list of relationships (facts) that can be filtered in a customizable way, to allow you to find specific facts at the snap of a finger.

Because each relation is extracted from a sentence in the text, you can quickly jump to the sentences in the text that contain the facts you found.

The system determines the importance of query words, or their synonyms for each document in the database, checking their frequency and similarity with words in the documents.
Use cases
  • Finding companies collaborations and financial deals
  • Gene-disease associations
  • Events tracking
Technology
Text2Knowledge is based on linguistic analysis of texts by complex AI algorithms.

Open relations extraction with dependencies parsing yields precise recognition of relations between business and biological entities within the sentences.

The system provides you with infallible insights from any data due to unique semantic approaches.
Try MVP version
Word-based search
Metadata-based search
Sentence-based search
Q&A search
Word-based search
Metadata-based search
Sentence-based search
Q&A search
Description
Word-based(or keywords) search accurately finds all publicly available articles, patents, or clinical trials that include queried words and phrases or their synonyms.
Input
Words, phrases.
Example: "Covid, vitamin D."
Results
The system provides a list of the most relevant articles, patents, or clinical trials organized according to the level of compliance with queried keywords or a phrase.
Use cases
  • Finding companies collaborations and financial deals
  • Gene-disease associations
  • Events tracking
Technology
The system determines the importance of query words, or their synonyms for each document in the database, checking their frequency and similarity with words in the documents.
Semantic search is an academic search engine that accurately finds scientific articles, patents, and clinical trials according to the search query. It understands natural language and recognizes queries as keywords, sentences, questions, or metadata so it can provide respective search results.
Request Demo
Description
Word-based(or keywords) search accurately finds all publicly available articles, patents, or clinical trials that include queried words and phrases or their synonyms.
Input
Words, phrases.
Example: "Covid, vitamin D."
Results
The system provides a list of the most relevant articles, patents, or clinical trials organized according to the level of compliance with queried keywords or a phrase.
Use cases
  • Finding companies collaborations and financial deals
  • Gene-disease associations
  • Events tracking
Technology
The system determines the importance of query words, or their synonyms for each document in the database, checking their frequency and similarity with words in the documents.
REQUEST DEMO
Semantic search is an academic search engine that accurately finds scientific articles, patents, and clinical trials according to the search query. It understands natural language and recognizes queries as keywords, sentences, questions, or metadata so it can provide respective search results.
Description
Metadata-based search accurately finds all articles, patents, and clinical trials that contain metadata specified in your query such as author name, journal title, etc.
Input
Author name, journal title, year, title, DOI, article section, article type.

Example: "Systematic reviews"
Results
The system provides a list of the most relevant articles, patents, or clinical trials organized according to the level of compliance with queried metadata.
Use cases
  • Metadata analysis
  • Review analysis
Technology
This type of search matches the metadata from your query with metadata from articles in the database. In this type of search, articles are sorted due to the citation count.
REQUEST DEMO
Semantic search is an academic search engine that accurately finds scientific articles, patents, and clinical trials according to the search query. It understands natural language and recognizes queries as keywords, sentences, questions, or metadata so it can provide respective search results.
Description
Metadata-based search accurately finds all articles, patents, and clinical trials that contain metadata specified in your query such as author name, journal title, etc.
Input
Author name, journal title, year, title, DOI, article section, article type.

Example: "Systematic reviews"
Results
The system provides a list of the most relevant articles, patents, or clinical trials organized according to the level of compliance with queried metadata.
Use cases
  • Metadata analysis
  • Review analysis
Technology
This type of search matches the metadata from your query with metadata from articles in the database. In this type of search, articles are sorted due to the citation count.
REQUEST DEMO
Semantic search is an academic search engine that accurately finds scientific articles, patents, and clinical trials according to the search query. It understands natural language and recognizes queries as keywords, sentences, questions, or metadata so it can provide respective search results.
Description
Sentence-based search accurately finds all articles, patents, or clinical trials, which contain semantically similar sentences to your query.
Input
Sentence.

Example: "Bacterial products, such as LPS, are potent bioactive factors that result in the switch of macrophage phenotype from M2 to M1."
Results
The system provides a list of the most relevant articles, patents, or clinical trials organized according to the level of compliance with a queried sentence.
Use cases
  • References searching
  • Anti-plagiarism analysis
Technology
If the query has a sentence structure, our system will automatically run a sentence-based type of search.
The results are documents with the most similar sentences to your query.
REQUEST DEMO
Semantic search is an academic search engine that accurately finds scientific articles, patents, and clinical trials according to the search query. It understands natural language and recognizes queries as keywords, sentences, questions, or metadata so it can provide respective search results.
Description
Sentence-based search accurately finds all articles, patents, or clinical trials, which contain semantically similar sentences to your query.
Input
Sentence.

Example: "Bacterial products, such as LPS, are potent bioactive factors that result in the switch of macrophage phenotype from M2 to M1."
Results
The system provides a list of the most relevant articles, patents, or clinical trials organized according to the level of compliance with a queried sentence.
Use cases
  • References searching
  • Anti-plagiarism analysis
Technology
If the query has a sentence structure, our system will automatically run a sentence-based type of search.
The results are documents with the most similar sentences to your query.