PatentPia Inc. | Strategic Patent Intelligence for M&A, Investment, HR, and Technology Insights

Owns data and AI related to the identification, analysis, and global optimal reallocation of technology innovation assets, including technology companies, talent, technologies, and patents.

Possesses big data on individual innovation assets and their connections to each other, generated by processing global patent data.
Provides optimized services for analyzing technology trends, competitors, companies for M&A and investment, and researchers for talent acquisition.

Recruiting

MISSION.

The need for
technology big data

Technology innovation asset business includes M&A/investment in technology companies, recruitment of technology personnel, transation/licensing of patents or technologies, and open innovation. This business also includes effective communication of the value of technology assets to third parties.

To succeed in this business, it is important to respond swiftly to changes and emerging issues in the technology market, and to identify and act on high-value innovative assets before your competitors do.

To this end, it is essential to possess extensive and detailed data for measuring, analyzing, and evaluating not only the current status, activities, and trends of (i) technology-owning companies, (ii) technical personnel, (iii) technologies, (iv) patents, and (v) expert organizations worldwide, but also the interconnections, precedence, and dependencies among them.

The essence of
value creation in capitalism

One of the core value-creation processes in capitalism is the movement and reallocation of assets. Technology innovation assets are transferred through M&A and investment, recruitment, and patent transactions or licensing.

To accelerate and facilitate the discovery and movement of these innovation assets, technology big data and AI must be leveraged.

The hidden value
of technical data

Technical data remains one of the most underutilized types of data. Its use extends far beyond R&D, as at least 50% of the world’s most valuable innovations occur in the technology domain. These innovations are often disclosed through patents, academic papers, and software-related data. Over 80% of the world’s top 10 companies and wealthiest individuals are connected to technology.

The power of big data
in technology

Technology big data, alone or combined with AI, serves as a foundation for creating various innovative services. Big data and its applications can be widely leveraged across various fields, including finance, human resources, marketing, product development, research and development, and the patent industry.

MISSION

Technology big data use cases.

Technology big data is widely used to analyze technology trends, competitors, and technology sensing,
as well as to identify technology companies for M&A/investment, identify research talent for recruitment, and identify risks and business opportunities.

Analysis of companies in specific technology fields

Various analyses are provided on companies, universities, and research institutions that hold patents in specific technology fields (e.g., AI accelerators).

Purpose: Technology trends, competitors, market leaders, M&A/investment (specialized companies), collaboration, risk (NPEs), etc.

Analyze metrics: No. of patents owned, No. of citations, No. of rejecting subsequent patents, No. of purchased patents, No. of patent suits/trials, quality, etc.

Technology fields: 260,000 CPCs/IPCs, 100,000 technical categories, 5 million keywords

Types of patent holders: Core companies, leading companies, specialized companies, rapidly-growing companies, new companies, subsequent-patent-rejecting companies, universities/research institutes, NPEs, individuals Technical competitiveness: No. of citations, No. of citations per patent, No. of rejecting subsequent patents, No. of rejecting subsequent patents per patent, etc.

Technical competitiveness: No. of citations, No. of citations per patent, No. of rejecting subsequent patents, No. of rejecting subsequent patents per patent, etc.

Analytics not only on individual companies in the technology field(example link), but also on the individual companies themselves(example link)

Link to US data details screen

Talent analysis in specific technology fields, specific companies, or specific technology fields of companies

Various analyses are provided on technical talents who invented patents in specific technology fields (e.g., AI accelerators), specific companies (e.g., Samsung Electronics), or specific technology fields of companies (e.g., AI accelerator field of Samsung Electronics).

Purpose: recruiting, protecting in-house key research personnel, collaboration - discovering collaborative research targets, etc.

ethnicity: Korean, Chinese, Indian, Japanese, etc. (not address) and address

Technology fields: 260,000 CPCs/IPCs, 100,000 technical categories, 5 million keywords

Organizations/Companies : 3 million entities including universities and research institutes.

Technology fields of organizations and companies: 200 million classified technology items by entity

Analytics not only on individual technical talent in the technical field (link to example), but also on the individual technical talent itself (link to example)

Link to US data details screen

Data-driven technology innovation asset recommendations

Discover and analyze tech talent, companies, and patents relevant to specific companies by country.

Inputs: a specific company, a company's specific technology field (e.g., AI accelerators), inventor

Output: Relevant inventors, relevant companies

Relevance: related to prior patents that the company-owned patent cites, related to prior patents that reject the company-owned patent, etc.

Innovation assets: prior patents, companies with prior patents, inventors of prior patents

Applications: recruiting, M&A/investment, patent acquisition/licensing, risk hedging, etc.

Link to US data details screen

Technology trends and tech sensing

Sense keywords for companies, technology fields, and companies' technology fields by country (patent office).

Analytics to detect/sense keyword/concept expressions in patents of a specific audience (e.g., companies like Apple, technology fields like XR) along with their classifications

Keyword types: rapidly growing, new, and highly specialized keywords

Keyword/concept expression classification (up to 2 depth) to maximize navigation/sensing efficiency

Link to US data details screen

Assets held.

Base data

Document data on innovation assets, including full text of patents from countries around the world, patent transactions (including transfer through M&A), patent litigations, patent trials, patent citations, patent rejections, patents funded by government R&D, papers, and GitHub SW, etc.

Organizational data, such as companies/universities/research institutes/NPEs, processed from document data

Technology talent data, such as inventor, paper author or SW developer

Keyword and technical expression data extracted and refined from documents, and keyword classification data

Big data

Quantitative analysis data on organizations, people, and technologies included in 100 million full-text patents in countries such as the US, South Korea, Japan, China, and the EU, as well as data on the relationships between them

By organization: 3 million+ companies/universities/research institutes/NPEs

By technology talent: 90+ million inventors/researchers/developers

By technology field: 5 million keywords, 260,000 standard patent technology classifications(CPC/IPC)

By organization/talent's technology: 200 million+ technology fields of companies, 200 million+ technology fields of talents

Some AI

Predictive evaluation models for the future growth potential of technologies

Evaluation models for individual patents

Classification models that increase the use of big data such as the ethnicity classification of inventors

Natural language Q&A AI for companies and tech talent in technology fields using LLMs

Web services to understand our thoughts

Goldencompass.patentpia.com primarily implements differentiated big data strategies for innovative asset-driven businesses.

A technology strategy support scheme integrating patents+papers+SW is implemented at strategy.patentpia.com (currently only available in Korean)

Early adopter customers

Early adopter customers such as Samsung Electronics, LG Energy solution, and LG Electronics are utilizing PatentPia data.

Several biz models if

BMs oriented toward traditional patent/technology information markets

BM for niche markets

BMs based on other out-of-the-box ideas, etc. (but important prerequisites need to be met. *See the Suggestion menu.