Are IP Landscapes Costly and Effort-Intensive?
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A Generative AI-Based Revolutionary Platform
R’PAC Subscription Service Helps you Explore Your Seed Ideas through IP Landscape Studies
For R&D, Innovation, and Strategy Teams
Uncover Competitors’ Patent Strategies
Expedite Technology Landscape Studies
For IP Teams
Identify Quick Category for Developing Taxonomies
Classify Automated Taxonomy-Based Patents
For Universities and Students
Explore Patents for Desired Topics
Unveil Industry Insights in Specific Research Domain
Supercharge Your Research in the Age of Innovation
Overcome bandwidth constraints, budget limitations, and time constraints with our cutting-edge solutions for idea exploration and IP landscape studies!
Categorize thousands of patents in a few hours
Achieve 80% categorization conformance with manual analysis
Explore patents on unlimited technology topics without bandwidth, budget, or time constraint
Free-up up to 70% of your bandwidth consumed in IP landscape studies
Get unlimited AI-based categorization at only USD300/month
A dedicated Technology Expert will be assigned to address the requirement and execute the analysis.
How does our subscription model work?
Our subscription service for R’PAC is transparent, flexible, and scalable,
with unlimited access to patent libraries.
(Competitors Names OR Patent List )
Join our R’PAC Services
And get an opportunity to build an exceptional future by working with our diverse global clients
Sample Reports
FAQs
R’PAC uses a combination of generative AI-based large language models (LLMs) such as GPT 3.5, GPT 4, DaVinci, and Google Bard to analyze and categorize patents. In future, if new models are added in these technologies, R’PAC would automatically get upgraded.
While IP professionals express concerns about data privacy when using language models like GPT, OpenAI, the developer of GPT, assure (GPT developer OpenAI’s usage policy) that customer-submitted data via their API will not be used to train models or improve their services.
We believe it is safe to use OpenAI GPT for publicly available patent-related tasks such as patent landscaping or analyzing published patents/applications.
It is not advisable to input personally identifiable information or employ the tool for activities like assessing patentability or drafting invention disclosures
Our research suggests R’PAC can be best used for landscape study and IP licensing programs. It offers a reliable patent classification and can be used to:
- Develop an automated taxonomy from a set of patents
- Identify the focus area of a large set of patents without reading the full text
- Shortlist the right set of patents for licensing
- Scout targets for licensing patents from a red- or blue-ocean industry
- High-volume, low-cost landscape studies
- Automated categorization of thousands of patents
- Tracking innovation trend of competitors
- IP licensing
High-volume, low-cost landscape studies on innovative topics could be a best use case of Aranca R'PAC.
Although the platform only works on patents currently, other document types will be covered in the future.
Based on our experience and testing, R'PAC categorizes patents with >80% conformance vis-à-vis manual analysis.
- List of patents to categorize or identify contextual tags
- Taxonomy categories, if ready
- List of competitors to be analysed
Currently, R’PAC works best with a maximum of up to 1,500 patents at one time and taxonomy categories up to two levels.
Supported Input Language: Currently, R’PAC can successfully categorize patents provided in English, German, French, and Italian.
Supported Output Language: English, German, French, Italian, Mandarin, Japanese, and Korean.
- Dedicated technology expert for research support
- Unlimited patent categorization support for one year
- Categorize under Taxonomy Levels
- Identify Patent Tags
- Summarize Patent Text
- Extract Technology Focus Area
- Extract Relevant Purpose
- Extract Application Industries
- Extract specific text (e.g., enzyme name, biomarkers, chemical formula)
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