FAQ (Frequently Asked Questions)

• How We Add Value

• Which business processes does b-science.net address?
• What distinguishes b-science.net subscriptions from competing information sources?
• We have an internal patent monitoring department. Why does a b-science.net subscription still make sense?

• AI Methodology

• How are the commercially most relevant patent applications identified?
• What is the advantage of AI-supported patent search?

• Subscription Scope & Information Sources

• Why can I trust b-science.net as an objective information source?
• What is the source of patent information provided by b-science.net?
• What other information sources are covered?
• How does b-science.net 'author support' work?
• What is included in subscriptions?

• How We Add Value

• Which business processes does b-science.net address?

• 35-45% of new high-tech product launches fail, often because CTOs / R&D departments lack objective data for sound decisions. b-science.net addresses this challenge through an AI-based innovation & patent information service that improves the quality of energy storage product development and adjacent decisions.
• For the majority of our subscribers, we support the cross-functional process of developing and executing the launch of new products.
• Typical questions our subscribers face:

• What R&D direction do we prioritize?
• Which projects are on track?
• What balance between performance, safety and costs should we strike to deliver a well-rounded product?
• What resources are necessary to launch the product prior to competitors?

• Our subscriber base clearly bats above the average when it comes to (making progress towards) successful product launches (according to public announcements of sales and production volumes, and VC investment rounds). The understanding that objective, granular innovation & technology information is greatly helpful to arrive at the right product development decisions correlates with outcomes.
• Academic research groups that have subsequently spun out their technology into startups and investors also rely on our information.

• What distinguishes b-science.net subscriptions from competing information sources?

• Some competing information sources involve the generation of patent lists upon entering a search query, which are very time-consuming for R&D decision makers to process.
• At the other end of the competitive spectrum, consultants prepare tailor-made, condensed information for customers, at a price tag that often only general management can afford as opposed to product development groups that often also make key decisions that drive product success or failure. By closely working for only the general management of a comparably limited number of customers per consultant, consultants tend to lack objectivity.
• Our subscriptions are unique on one hand because they provide a much more granular yet condensed insight into the patent literature in relation to the specific trade-offs faced by technical decision makers, reaching the level of technical product / process specifications and benchmarking data. Because our subscriptions are purchased by multiple subscribers across America, Europe and Asia, they are more objective than tailored work by consultants and they are priced lower. 2 h of 'author support' included in subscriptions typically cover remaining customer-specific information gaps.
• Results provided by AI-bots that are not 'supervised' by subject matter experts potentially provide inspirational information, but time-consuming fact-checking is necessary and key facts might be missing. Some crucial information might never become available to AI-bots, such as panel discussions that take place at conferences, which often significantly impact b-science.net subject matter expert's view on the commercial prospects of a new technology.

• We have an internal patent monitoring department. Why does a b-science.net subscription still make sense?

• Many of our subscribers have an internal patent monitoring department, yet still purchased and renewed a b-science.net subscription. This usually happens when the decision-maker in charge of delivering a successful product launch insists on deciding based on multiple internal and external information sources and considers the purchase of a b-science.net subscription worthwhile in the context of a project budget that is usually much larger.

• AI Methodology

• How are the commercially most relevant patent applications identified?

• Thousands of data points on the prospective commercial relevance of newly published patent applications with respect to 10 energy storage categories are being defined every 3 weeks by b-science.net since 2018, such as 'Lithium-ion batteries - electrolytes - solid & semi-solid'. This body of well-informed, forward-looking judgements have allowed for the definition of superior AI models that interestingly can identify uniquely relevant patents even if the underlying concept is very novel. For example – as shown in the image below – a conceptually new supramolecular semi-solid electrolyte patent that might form the basis of CATL's breakthrough 'condensed battery' was ranked as the #1 commercially relevant patent application among 2k patent applications by CATL.
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• What is the advantage of AI-supported patent search?

• If a keyword search is comprehensive, it will typically generate a chronological list of several hundred entries that take a long time to analyze. If a keyword search generates few results, important patents will likely be missed.
• With our AI approach, queries can be ordered according to machine generated scores related to a specific research field.
• The commercially most relevant patents appear at the top of the list while the user can go as far down in relevancy to be comfortable of not having missed anything.
• Our commercial relevancy rankings are superior compared to established search engines because we carefully define each AI model based on thousands of individual patents, informed by our hands on knowledge of the energy storage sector.
• Unsupervised AI bots will become increasingly important, but the quality of results still can vary very substantially for now. In AI bots, the probability that an AI-generated result is right is not reflected in AI scores like in our case, which can be used by decision makers to decide if an AI data point (on the commercial relevance of a patent) is accepted, or if it is in a gray area that requires double-checking.

• Subscription Scope & Information Sources

• Why can I trust b-science.net as an objective information source?

• It lies in our economic interest to strive towards being an objective information source because our subscriber base is spread almost evenly between America and Europe, along with an important revenue share from Asia (incl. China)-based subscribers.
• We consistently pursue a methodology that is rooted in referenced publicly available data, based on which projections and interpretations are made based on arguments that the subscriber can selectively accept or dismiss to arrive at decisions of satisfactory quality.
• All b-science.net content is produced by professionals with hands-on industrial experience at companies that produce climate tech products, after having completed a PhD.
• The ownership structure of b-science.net LLC is publicly accessible in the trade register of Canton Zurich in Switzerland. It consists of 5 private persons based in Switzerland, the UK and Germany with knowledge of climate technology, IT/AI and commercial matters in high-tech.

• What is the source of patent information provided by b-science.net?

• Our database consists of >3M patent documents from the European Patent Office (EPO) database, published in 1980 or later, that either contain the words 'battery' or 'batteries' in the title or abstract, or to which CPC or IPC1-8 patent classification codes H01M (batteries & fuel cells) or H01G (capacitors) were assigned.
• The EPO database contains patent documents filed with more than 100 patent offices across the globe.

• What other information sources are covered?

• Technology-related news releases and reports along with technical information shared at various energy storage conferences at which we regularly participate. The academic literature is not systematically covered at this time.

• How does b-science.net 'author support' work?

• Subscribers can use (typically 2 h) 'author support' to analyze the technology portfolio of a company not covered in our reviews, to define SWOT diagrams for upcoming product development decisions, or to obtain a list of AI-ranked patents in relation to a specific search request.
• Responses can be delivered by b-science.net as PowerPoint slides, as Excel files and/or through Q&A sessions in video calls.
• Some of our startup subscribers requested that the 'author support' is used for conversations with their (prospective) investors to cover the technology landscape a startup is operating in. After such conversations, financing rounds of >USD 20M were closed thus far by our subscribers.

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