Three Keys to Effective Freedom-to-Operate Management

Freedom-to-operate is a murky world where the quality of the investigation greatly depends on the skills and resourcefulness of the lawyer or analyst doing the work. Best practices and standards of care are not very well defined and, even when systems exist, they are rarely adaptable to changing needs.

It is our mission at ClearstoneIP to gather, implement, and standardize best practices in FTO and patent risk management. This article is a step in that process and sets forth three basic foundational concepts for effective FTO management.

  1. Well-defined product parameters. For an effective FTO investigation, it is important to define the product or project parameters at the outset. FTO is necessarily carried out with regard to a specific subject. Thus, the analyst should create or ascertain a detailed definition of the product, process, system, or future concept that is being cleared  in order to memorialize the current state of the product. This contrasts with the sort of “invention harvesting” that might be done as part of growing a patent portfolio, where the goal is to identify broad inventive concepts and build on them in creative, but not necessarily actualized, ways. In FTO, the more that is known about the actual product intended to be sold, the more effective the investigation will be. Also, as a product evolves over time, past FTO analysis on that product may change radically. We should document parameters and features at a specific point in time in order to establish a clear historical record.
  2. Patent analysis must focus on the claims. More critically than perhaps any other activity in patent law, an FTO investigation must be centered on patent claims. Prior art patents might include any number of embodiments, alternatives, and everything else under the sun in its specification, but the claims define the exclusive rights. If we can point to a single element of a claim that is not present in the product being investigated, then the claim is cleared and we can move on. There may be some exceptions to this when, for example, we’d want to monitor a cleared patent and its family when the subject matter is particularly close. But the point remains that infringement analysis is all about the claims. Losing sight of this, and using systems that make it difficult to access and act upon claims, can result in inefficiency and wasted time.
  3. A mechanism to tie products to claim determinations. Building on the first two keys, it follows that the investigation would fall apart if we don’t use an effective mechanism to track, memorialize, and manipulate our work product. If we only had one simple product that never changed, this part wouldn’t be too difficult. But as products become more complex, upgrades and modifications are implemented, and product lines grow larger, our need for a robust system to handle the different permutations of product-analysis combinations becomes critical.

There is, of course, much more to the process, such as how to locate relevant patents, how to properly interpret patent claims, when to dismiss patents or merely flag them for monitoring, how to strategically assess relative risk among critical sets of patents, and more. We will touch on specific nuances and more in-depth analysis techniques in future articles.

ClearstoneIP Announces New FTO Platform

ClearstoneIP is proud to announce the beta release of its next generation freedom-to-operate management platform, Clearstone FTO. With guidance and feedback from IP industry leaders, we’ve infused this new web-based application with the ideal combination of best practices, workflows, and collaboration features to bring much-needed efficiency to a critical process.

Some of the core features of the platform include:

  • Product-focused organization of FTO reviews – all reviews for a product easily locatable in one place.
  • Claim-by-claim FTO determinations with integrated patent review interface.
  • Team collaboration – messaging, workflow management, asset sharing, all easily handled between team members.
  • Patent history review – easily see what decisions were made on a patent, in any prior review and any other product.
  • Customizable reporting – user-configurable to report the most essential information.

With state-of-the-art security features, Clearstone FTO makes it simple and safe to access vital information from anywhere. It’s an intuitive and powerful approach to manage and interact with information that was previously relegated to hundreds of spreadsheets scattered throughout organizations.

Click here to learn more.

Accuracy and Speed in Patent Infringement Searching Need Not Be “One or the Other”

“Faster and better results at lower cost!”

A claim so common it blends in with the hum of office chatter. We’d like to believe that patent searches could be turned around within a day or two, but it typically takes much longer.  We’d like to believe that the work returned to us includes everything we need to know.  But, at some level, we sense there are shortcomings.

This is particularly true in the case of freedom-to-operate investigations (FTO).  Searchers often fail to consider certain product features.  Claims are not always afforded their full scope.  And sometimes key patents are just plain missed.  Despite relying on highly competent and experienced analysts, “faster, better and cheaper” just does not seem a reality.

But a departure from conventional methods can overcome the trade-off between speed and accuracy. We can achieve both.  Clearstone Elements is that departure.

Why is there a speed/accuracy trade-off when using conventional search methods?

Imagine for a moment that you have been asked to carry out an FTO analysis.  Let’s also say that, as is often the case, you must complete this analysis under budget, say $3,500.  Assume a billing rate of $75/hour (you have overhead and a boss) and that you’re able to review a patent every 6 minutes.  That means you only have budget to manually review about 470 patents.

This might seem like a reasonably-sized lot.  However, experienced FTO searchers would likely feel that it’s not nearly enough to guarantee a high level of recall (i.e., the ratio of the number of relevant patents retrieved to the total number of relevant patents), say of about 95%.  This will of course vary case-by-case.  But, for many competitive industries, you’d need a starting set in the range of about 2,500-5,000 patents to achieve a sufficiently high recall.

Why must so many patents be manually reviewed in FTO?

Certainly, products don’t typically infringe thousands of patents.  Else, industries would come to a grinding halt.  Indeed, out of a robust set of patents to be reviewed, a searcher is likely to only uncover a handful of relevant ones.

The short answer to the above question is that it’s very difficult for a searcher to anticipate whether a patent is relevant without actually reading and understanding its legal claims.  Products may be described in countless ways, many of which will go unnoticed to a searcher.  Claims of a patent may be written in much broader terms than used to describe the specific embodiments of the patent’s technical disclosure.  For these and other reasons (see here for more information), conventional search tools are imprecise blunt instruments in the FTO context.  Thus, a broad net must be cast.

It should now be obvious why inaccuracy seeps in.

A searcher will typically approach a search with the best of intentions, considering every angle of attack.  Patent classes will be reviewed, important ones selected and queried.  Key assignees will be queried.  Citation, clustering, and family analysis will be conducted on patents flagged as relevant.  Natural language queries, perhaps using semantic analysis, will also be applied relating to key product features.

These tools are all great at robustly representing technology areas.  However, most likely, this aggregation will far exceed, in number, what could be reviewed under budget in an FTO context.  Accordingly, the searcher will necessarily have to take additional steps to downsize this set.  And this is where it goes awry.  The searcher may do as follows:

  1. limit all results by requiring the inclusion of certain key terms;
  2. exclude unknown or small-scale assignees;
  3. exclude patents based on Title, Abstract and/or Drawings; and/or
  4. limit patents by relevancy score cut-off (if relevancy scores are provided).

These processes are generally arbitrary in nature and bare little correlation with relevance.  They are simply not sound bases for reducing a large aggregation of patents in an FTO search.  Inevitably, they cause omission of critical patents.

How does Clearstone Elements overcome this dilemma?

Clearstone Elements is a fundamentally unique search platform.  In Clearstone Elements, associations between patents and technical attributes are memorialized, forming specialized data files called workspaces.  Notably, these technical attributes are associated with patents on the basis of their claims and using human analysis.  These attributes (or elements) are then presented to a searcher as an interactive taxonomy.  A searcher may than effortlessly eliminate swaths of patents from a robust patent set by selecting elements not embodied by the product undergoing search (more on this process here).  In contrast to the arbitrary procedures discussed above, the Clearstone process is objective, reliable, and deliberate.

In fact, current users of Clearstone Elements are typically able to reduce a robust patent set by 90-95%.  This means that, once a workspace is put in place, provided the same constraints as in the above example, a searcher using Clearstone Elements is actually able to objectively consider upwards of 4,700-9,400 patents.  We are essentially empowering searchers to cast significantly broader nets with significantly reduced manual effort.  By replacing the conventional tools that are blunt and arbitrary with Clearstone Element’s logic-based reduction process, “faster, cheaper and more accurate” is no longer an empty promise.

Enfish v. Microsoft: The Pendulum Might Be Changing Direction For Software Patents, But Challenges Still Exist

The Federal Circuit’s recent decision in Enfish v. Microsoft Corp. was significant in that it was the first time that the court reversed a trial court’s finding of invalidity under § 101 based on the Supreme Court’s Alice decision, and only the second time that it upheld validity under that section post-Alice (the first being DDR Holdings v.

The opinion was well-received by the patent bar, and the software industry in particular, as powerful precedent that can be used to fight rejections by the USPTO, defend counterclaims of invalidity in court, and otherwise strengthen the value of software patents. While the line between eligible and ineligible subject matter has become somewhat clearer, there is still ambiguity in certain areas, and questions exist regarding practical implications.

The Claimed Invention

Enfish involved patent claims directed to a “self-referential” database. The court referred to the following representative claim:

A data storage and retrieval system for a computer memory, comprising:

means for configuring said memory according to a logical table, said logical table including:

a plurality of logical rows, each said logical row including an object identification number (OID) to identify each said logical row, each said logical row corresponding to a record of information;

a plurality of logical columns intersecting said plurality of logical rows to define a plurality of logical cells, each said logical column including an OID to identify each said logical column; and

means for indexing data stored in said table.

Enfish's "self-referential database"
Enfish’s “self-referential database”

The court referred to the invention generally as “an innovative logical model for a computer database.” The primary contribution to the art of the invention was the “self-referential” aspect, which purportedly avoided the need in conventional “relational database model” systems to define and maintain many separate tables. Instead, the claimed invention can store the pertinent information in a single table. According to the patents, the new approach improved searching efficiency and resulted in more-effective storage of unstructured data.


The Court’s Reasoning

The court began with the two-step analysis set forth in Alice and prior cases, in which the first step determines whether the claims are directed to a patent-ineligible concept, such as an abstract idea, and the second step considers whether the particular elements of the claims transform the nature of the claim into a patent-eligible application.

There is no doubt that the Federal Circuit took aim at some of the more egregious gaps that Alice left open. Primary among these gaps was the perceived Alice takeaway that there was no real limit on the height of abstraction that can be carried out on software claims in step one. In other words, one could conclude from Alice, and courts often did conclude, that a software claim is abstract if it can be summarized into something reasonably conventional, specific claim limitations be damned.

Enfish at least partly rectified this misconception by recognizing that “[t]he ‘directed to’ inquiry, therefore, cannot simply ask whether the claims involve a patent-ineligible concept, because essentially every routinely patent-eligible claim involving physical products and actions involves a law of nature and/or natural phenomenon—after all, they take place in the physical world.” Further, “describing the claims at such a high level of abstraction and untethered from the language of the claims all but ensures that the exceptions to § 101 swallow the rule.” Instead, claims must be considered as a whole and in light of the specification.

Accordingly, the Enfish panel carefully considered each element of the claims, including applying § 112, sixth paragraph, to interpret means-plus-function limitations, and examined the patent specification to both (i) shed light on the claim language; and (ii) express the advantages of the claimed invention over the prior art.

The court ultimately held that the relevant question is “whether the claims are directed to an improvement to computer functionality versus being directed to an abstract idea.” It concluded that the claimed self-referential database logic model is “a specific type of data structure designed to improve the way a computer stores and retrieves data in memory” and is therefore not an abstract idea. Having satisfied the first step of the Alice inquiry in the patentholder’s favor, the court did not need to address step two.

The Enfish holding gives teeth to the first step of the Alice inquiry and requires that the analysis take into consideration the nature of the invention and how it affects computer capabilities. In cases where the claims simply add conventional computer components to “well-known business practices,” they might be more likely to be found abstract under step one of the Alice inquiry.


Enfish is certainly a useful precedent for owners and seekers of software patents and should serve to strengthen patents as a general matter, but it does not (and cannot) fix the real havoc that was wreaked by the Supreme Court in Alice. Namely, the biggest problem with Alice is that it conflated and blurred the lines between questions of eligibility and those of prior art (i.e., novelty and obviousness).

Questions as to whether a claimed idea is “conventional,” “well known,” or is a “fundamental practice” have no place in an abstractness inquiry. These are questions that can be answered only by proving the existence or absence of prior art, not by some common sense-based purely mental exercise. Whether a claimed invention is abstract or practical is completely independent of novelty. The “abstractness” question should rely predominantly, if not entirely, on an isolated analysis of the actual features of the invention and whether it has some technical or practical component that makes it more than a mere idea in the ether. But that is a battle for another day, and one which the Federal Circuit does not appear to have the authority to fight until Alice is overturned or distinguished by future Supreme Court decisions.

Know Your Portfolio


“Which of our patents cover what the competitors are doing?”

“Where are the holes in our patent coverage?”

“Which of our patents cover our products?”

What the heck is in our patent portfolio?!?!”


A patent portfolio is both a sword and a shield; leverage

your analysis with Clearstone Elements to wield both with agility.

These are some of the most critical questions asked of in-house patent counsel, but they can also be the most dreaded. Experienced practitioners know there are no easy answers. Reliable results can be expensive and are often reached only after a significant investment in time.

ClearstoneIP is changing all of that.

In any strategic patent assessment, whether defensive or offensive, it is critical to know what technologies, products, or processes are actually covered by a particular portfolio. Patent metrics based on bibliographic and other surface data only go so far; these critical questions can only be answered with an in-depth analysis of patent claims.

For example, the cornerstone to any successful licensing program is “to have a detailed understanding of what you own and where the most value lies. It is also important to have an understanding of the technologies within your patent portfolio and how they are connected (a “taxonomy”).” In an effective defensive strategy, “good portfolio management requires monitoring of your competition’s patent holdings to identify opportunities and threats.” Key to these efforts is not just having a vague sense of generally protected subject matter, but identifying specific product-to-patent correlations with confidence and agility.

That’s why we’ve built the ideal platform for capturing and interacting with patent portfolio analysis. After a one-time effort to index a patent collection, Clearstone Elements leverages that analysis to yield powerful results, including the ability to:

  • Map competitor products to your patent portfolio in minutes to discover the patents that are most likely to be infringed. The process can be repeated for any number of products, with each mapping typically taking less than 30 minutes (even for large portfolios that include thousands of patents).
  • Map your products to your patent portfolio to determine whether your portfolio provides adequate protection for your product line and to discover gaps in coverage. This is also a convenient way to manage patent marking.
  • Mix and match product mappings to different portfolios or collections of patents to assess offensive and defensive strategies with respect to various alignments. In Elements, users perform a product mapping by interacting with a hierarchy of technical elements irrespective of the underlying patents. The user can map a product once and apply the mapping to different patent sets interchangeably, a truly unique capability that only ClearstoneIP can offer.
  • Quickly adapt product mappings to account for product changes over time to zero in on which patents become relevant due to the changes.
  • Apply saved product mappings to patents and portfolios indexed later in time. The unique nature of Elements offers a mechanism that instantly compares saved product mappings to any patents that are indexed at a later time. So when newly issued/acquired patents are indexed, Clearstone Elements will instantly inform the user which of these patents are likely to cover previously mapped products.

The Elements platform provides a degree of patent omniscience that some of our users have likened to “seeing the matrix.”

Sign up for a Clearstone Elements trial account today to start leveraging your patent portfolio analysis for insight and efficiency.

Legaltech New York Wrap-up

What a week! Our first trip to Legaltech was a whirlwind, but a ton of fun. It was amazing to meet so many people who are excited about new ways that technology can improve our work in the legal industry. The show took place at the Hilton NY Midtown on Feb. 2-4. With thousands of attendees and hundreds of exhibitors, Legaltech is the largest trade show in the industry.

First we’d like to thank ALM, the organizer of the huge show, and the Stanford CodeX Center for inviting us to exhibit as part of the much-buzzed-about CodeX Pavilion. It was an honor to be part of such an amazing group of innovators (keep an eye out for Casetext – these guys are doing amazing things by crowd-sourcing legal commentary in a free research platform!).

Our exhibit attracted a lot of attention from patent professionals, press, and tech aficionados alike. Here is Jesse being interviewed by Larry Port of Rocket Matter:

We also had the privilege to participate in CodeX’s Legal Disruption Pitch Lightning Round, where we presented ClearstoneIP in front of a packed ballroom.

Click to read CodeX’s Recap of the Lightning Round, by Monica Bay.

See more write-ups about the CodeX session at:

The next Legaltech conference is just a few months away here in the San Francisco area on June 13-14, 2016. Hope to see you there!

Why Semantic Searching Fails For Freedom-to-Operate (FTO) and What You Should Be Doing Instead (PART 3)

Hammer-and-ScrewPart 3 of 3: What You Should Be Doing Instead

This three-part series explains why conventional techniques, particularly “semantics-based” searching, fall short for freedom-to-operate (FTO) searching and analysis.  It then puts forth a solution for avoiding these problems. Part I was an introduction to the differences between the searches. Part II identified the deficiencies of semantic searching in relation to FTO analysis. Part III explains how these deficiencies can be overcome. Click here to download a PDF of the entire series.


Part I and Part II of this series explained how semantic and similar keyword-based platforms are ill-suited for freedom-to-operate analysis. We saw how, for various reasons, these platforms show little for their cost.

We can overcome the shortfalls of conventional search tools by building a new FTO solution from the ground up.

Let’s take a look at some necessary characteristics of such a solution:

1.  The solution must recognize claim scope, not just patent disclosure.

Easier said than done, right? Patent claims are notoriously complex and are often intentionally vague or broad. Despite its complexity, claim scope could be effectively navigated with the right platform.

First, the solution ultimately must leverage human analysis in some form. We should dispel the notion that artificial intelligence, such as semantic-based algorithms, can properly interpret claims. Sure, they may be fine at retrieving patents that disclose pertinent subject matter, but there is a fatal disconnect when it comes to claim coverage. Semantic algorithms simply cannot read and process delineations of scope. They are essentially language-similarity detectors and can’t differentiate between claimed concepts and those that are merely disclosed.

Second, the solution needs to handle claim concepts in an eliminatory or deductive framework. This is a significant departure from the status quo. Conventional platforms amass or aggregate sets of potentially relevant patents to create a large set for deeper review. However, in FTO, it is far more efficient to arrive at a review set by first eliminating irrelevant patents from a large initial set based on a claim scope determination. Several reasons for this were discussed in a previous blog post.

The correct framework places the most relevant question at the forefront, not the back end. For FTO, the question is whether a particular product embodies each claim element of a patent. It is not whether a patent discloses similar subject matter.

2.  The ideal FTO solution accounts for the infinite ways of describing a product.

The ideal FTO solution should not require an analyst to identify keywords or specific terms ahead of time because, as discussed in Part II, there is never a single “right” way to do so. And if an analyst were to try to capture all of the ways, semantic platforms would retrieve an impossible amount of results.

The solution to this problem must remove this guesswork from the equation. Building on the eliminatory framework described above, the solution should present to the analyst an organized menu of claim concepts. Instead of considering what to bring into a search, an analyst only needs to consider which of the displayed claim concepts do not correspond to the product.

The menu of concepts should be displayed in an organized manner, for example an index-based system that an analyst can navigate. The index will present a list or taxonomy of technical concepts that each represent patent claim elements. In this way, the analyst can simply make a determination on an element-by-element basis as to whether it relates to the product at issue.

A rough semblance of a concept-based index exists in the form of official patent classification systems used by patent offices around the world, such as the former U.S. Patent Classification system (USPC) and the newly adopted Cooperative Patent Classification system (CPC). But these systems are still extremely cumbersome for FTO for several reasons: (i) they are not keyed to specific claim elements but, rather, general inventive concepts; (ii) they have no capacity to distinguish among different independent claims of a single patent; (iii) they are not nearly specific enough to be effective; and (iv) while they are updated from time to time, they are effectively static indices that are difficult to modify and adapt.

The ideal FTO solution includes a dynamic, easily modifiable taxonomical index of elements that are programmatically connected to specific patent claims. The index has high granularity but allows the analyst to operate as broadly or as specifically as desired without reducing efficiency.

3.  The ideal FTO solution does not sacrifice completeness for relevance.

In Part II, we discussed the problems that arise when a search platform provides results in a “ranked” order. We saw that these ranking algorithms could be arbitrary since they are based primarily on similarity of language or terminology. Highly relevant results from an FTO perspective can be placed far down the result list. Missing pertinent patents in an FTO analysis is far more consequential than missing a potentially relevant reference in a patentability search.

The ideal FTO solution should be equipped to capture all potentially relevant patents, readily bring them to the surface, and do so efficiently. It will avoid burying highly relevant patents and make them easy to locate.

Clearstone Elements™ – The Ideal Solution

Our Clearstone Elements application is the ideal FTO solution. It is an interactive platform that, as a core capability, provides a comprehensive taxonomical index of technical elements drawn directly from human analysis of patent claims. As an analyst navigates the hierarchy, he or she selects elements that are not present in a product under review. The software will automatically eliminate from the initial set the patents that require the selected element for infringement. After just a short period, typically less than an hour, 90-95% of the initial patent set is usually eliminated, leaving the most critical and relevant patents for closer review.

To see this more clearly, take a look at the below real-time video, in which more than 10% of the initial patent set is eliminated in less than 45 seconds:

These kinds of results and efficiency are simply not achievable with any other system. This is how the “noise” is removed from search results.

An interesting phenomenon occurs in FTO. A large proportion of patents tend to be dismissible from an initial patent set based on only a few, general requirements. This is due in part to the noisiness of conventional search tools, but also to the peculiarities of claim-drafting.

As an example, consider the golf club field. There are about 4,500 active patents in this field, a 100-plus year old industry. Obviously, these active patents are directed to nuanced, highly incremental improvements. Yet, of this universe of highly specific patents, the claims of about 62% require a golf club head to be an “iron-type,” “putter-type,” or “wood-type.” What this means is that, if one only applies those three broad technical concepts in Clearstone Elements, they could eliminate 30-40% of patents from any particular search. Imagine what is possible by applying a few more concepts.

Determining if this phenomenon occurs in your industry is simple enough. Review a random swath of patents from the initial patent set of your last comprehensive FTO investigation. For patents that you excluded, what were the reasons? Were they excluded for requiring broad, sweeping technical concepts (or were you compelled to dig deep to understand the fine points of novelty)? Did these reasons frequently recur (or were they unique)? I suspect that most patents were dismissible based on broader concepts that frequently recur throughout the patent set. Clearstone Elements leverages this phenomenon and more to achieve incredible results.

The graph below illustrates conceptually how the addition of a deduction-based platform such as Clearstone Elements can shift the cost-accuracy curve for FTO. Because of the ease of objectively eliminating large portions of patent references with little work, high accuracy could be achieved at little cost. Conventional tools are unable to achieve this efficiency.
Ded EngineAnother important aspect of Clearstone Elements is that the analyst does not have to know beforehand which aspects of the product may present infringement issues. The patented concepts are presented on the screen in the taxonomical index. The analyst only needs to decide whether the product embodies the concept or not. This is how the system ensures that critical patents are not missed – they are only removed from the initial set upon a deliberate decision by the analyst based on displayed concepts.

Taking this a step further, analysts can create a “product record” upon completing their review of the index. This product record is essentially a fingerprint of the product as it relates to the indexed elements, and, in turn, how the product relates to the initial set of patents. The product record can be opened and modified later on to quickly reflect any changes that are made to the product during development to achieve an incredible result: The Elements interface will instantly display a list of patents that become of issue solely due to the product changes. This capability is truly unprecedented and is key in streamlining product development through enhanced communication between product designers and the legal department. See the blog post, Bridging the Divide Between Patent and Engineers, for more.

Many more interesting and powerful results are being achieved with Clearstone Elements as a foundation, which will be discussed in future articles. The methods discussed here will pave the way for a new industry standard for all varieties of patent claim analysis since they represent the correct analytical approach (not to mention how enjoyable it is to interact with the application and watch the patent counter drop!). We hope you join us on this exciting journey.

Why Semantic Searching Fails For Freedom-to-Operate (FTO) and What You Should Be Doing Instead (PART 2)

Hammer-and-ScrewPart 2 of 3: Why Semantic Searching Fails for FTO

This three-part series explains why conventional techniques, particularly “semantics-based” searching, fall short for freedom-to-operate (FTO) searching and analysis.  It then puts forth a solution for avoiding these problems. Part I was an introduction to the differences between the searches. Part II identifies the deficiencies of semantic searching in relation to FTO analysis. Part III explains how these deficiencies can be overcome. Click here to download a PDF of the entire series.


I.  How Semantic Search Platforms Work

There are countless patent searching software platforms available. Each has unique features, but broad commonalities exist. Available platforms tend to offer some combination of natural language, Boolean, classification and semantic searching. Semantic searching is the primary focus of this discussion, as it is the most evolved.

Semantic patent searching generally refers to automatically enhancing a text-based query to better represent its underlying meaning, thereby better identifying conceptually related references. This process generally includes: (1) supplementing terms of a text-based query with their synonyms; and (2) assessing the proximity of resulting patents to the determined underlying meaning of the text-based query. Semantic platforms are often touted as critical add-ons to natural language searching. They are said to account for discrepancies in word form and lexicography between the text of queries and patent disclosures.

Based on this, it would seem that semantic searching is powerful and effective. Well, it is…  for some types of searches (e.g., patentability or invalidity searches). However, it is surprisingly ineffective for FTO. And this has everything to do with the distinctiveness of FTO as discussed in Part 1.

II.  The Effect of Semantic Platforms on FTO

Semantic platforms, by their nature, assume a certain paradigm. They purport to interpolate the underlying meaning of a text-based query. This is great in cases where an analyst knows which technical concepts are relevant. For example, in a patentability or invalidity search, the analyst has a specific claim under review with specifically-recited elements. FTO searches do not fit this paradigm.

Consider the distinctions discussed in Part 1 of this series:

(1) In FTO, relevance of patent results is determined by claim scope, not description. The technical aspects described by a patent’s disclosure are distinct from its claims.

In a patentability search, the semantic platform will return precisely what the searcher desires – patents describing the subject concept of the query.

For FTO, the platform will not. Some patents describing a product feature under review may contain claims covering such feature. However, the vast majority will not. The claims will instead be drawn narrower by requiring additional aspects and specificity. Accordingly, semantic engines necessarily output a high proportion of non-relevant patents (i.e., they are “noisy”).

The reverse scenario is also problematic. Many patents will exist that do not describe a specific product feature, yet will have claims sufficiently broad to cover the feature. Semantic engines will rarely identify these types of patents. Even if identified, they are likely to be assigned a low relevancy rank given their much broader scope. This makes sense in a patentability search, but not in an FTO context.

For this reason, semantic platforms suffer two deficiencies at opposite ends of the spectrum: (1) they are under-inclusive as they are prone to missing relevant broad patents; and (2) they are over-inclusive due to their noisiness with respect to patents with narrow or otherwise non-relevant claims.

(2) Products tell a thousand stories. Products, due to their physical existence, can be described in thousands of ways. Each way could be a basis for infringement. Patentability searching, instead, is more discrete.

Semantic search tools force analysts to play an arbitrary game of “guess the element.” They require that analysts examine features of a product and pick out just the right ones worthy of review. Even for experienced analysts, this exercise is more conjury than skill. It is simply impossible to accurately predict which aspects of a product are likely to be the basis of infringement in an FTO analysis.

In practical terms, semantic platforms unduly force analysts to pit accuracy against timeliness. If an analyst is selective, many relevant references will inevitably be missed. If, on the other hand, the analyst is cautious and queries many product features, the results will be unworkably noisy.

 (3) Missing patents in an FTO search could be dire. Finding relevant patents in an FTO search is no indication whether additional relevant patents exist. An entire technology space must be cleared. In patentability searching, producing a few close results is more acceptable.

Because of points (1) and (2) above, semantic-based results are likely to contain a large number of patents, perhaps ranked by purported relevance. In a patentability search, an analyst may be comfortable reviewing only the first tier of patent references (e.g., the top one-hundred or so). However, the purpose of FTO is to assess and minimize liability risk. Reviewing only the first arbitrary tier of references would undermine this mission. FTO is not concerned with which patents most predictably cover a product; FTO means ensuring that no patents cover the product.

III.  Summing Up Semantics

Conducting FTO searches using semantic platforms produces noisy results that are also prone to significant omission of relevant patents. This presents the analyst with a dilemma. The analyst must choose between: (1) reviewing a compact set of references that is likely incomplete; or (2) reviewing a comprehensive set of references that likely contains a significant amount of noise.

If interested in whether these findings relate to you, perform a simple test. Dig up your last comprehensive FTO search. Review the patent references that you ultimately deemed relevant. Do they generally fall within the same patent classes (as opposed to being scattered over the classification map)? Do they all pertain to a predictable technical feature (as opposed to relating to the product in unexpected ways)? Do you believe they could have all been retrieved using just a few keywords? If your responses are generally “no,” then your experience is quite typical. If your responses are generally “yes,” you’ve experienced a surprising amount of luck. I suggest buying a lottery ticket.

The illustration below shows how semantic search platforms handle patentability and FTO searches differently in terms of accuracy and cost (“cost” essentially being a proxy measure for work time). A high proportion of missed references results in an inaccurate search. A high proportion of noise results in a costly search. The darker shaded regions represent where industry cases typically fall.

semantic graphics

The point here is that semantic platforms can deliver effective results for patentability searches at a reasonable cost but, when it comes to FTO searching, the effectiveness of the platforms is limited even at great cost.

This all leads to the question of whether FTO searches are innately high-cost/low-accuracy processes or if we are just not handling them correctly. Many in the patent industry seem resigned to the belief that improving FTO is a futile endeavor. This point-of-view is understandable but incorrect. FTO can be made accurate and low-cost. It just takes a fresh approach.

More on streamlining FTO in Part 3: What You Should be Doing Instead.

Why Semantic Searching Fails For Freedom-to-Operate (FTO) and What You Should Be Doing Instead (PART 1)

Hammer-and-ScrewPart 1 of 3: Introduction to the differences between Patentability and FTO searching

This three-part series explains why conventional techniques, particularly “semantics-based” searching, fall short for freedom-to-operate (FTO) searching and analysis.  It then puts forth a solution for avoiding these problems. Part I is an introduction to the differences between the searches. Part II will identify the deficiencies of semantic searching in relation to FTO analysis. Part III will explain how these deficiencies can be overcome. Click here to download a PDF of the entire series.

Not all patent searches are the same.

This seems an obvious point. But how well understood are the conceptual distinctions between the various types of patent searches? We are quite familiar with a “patentability search,” which attempts to answer the question:

Is this concept novel and non-obvious? 

We are also familiar with an “invalidity search,” which attempts to answer the question:

Should this patented invention have been considered novel and non-obvious? 

These types of searches are conceptually similar, and may be collectively referred to as “patentability searches.” Now consider, in contrast, the question posed in an FTO search:

Is this product likely to infringe an active patent?

Based on these different underlying questions, three critical distinctions between FTO and patentability emerge.

1.  In FTO, relevance of patent results is determined by claim scope, not description.

Patents necessarily include a technical description and legal claims. While the technical description must enable the claimed inventions, the actual scope of what is claimed may vary significantly from what is described in the technical description. For example, practitioners generally aim for detailed technical descriptions yet broad all-encompassing claims.

In the vast majority of FTO cases, the claims of patents that describe features of a product undergoing FTO do not actually cover those features. Usually these claims are significantly narrower in scope. Other times, the subject matter of the claims is simply directed to other disclosed aspects.

The reverse scenario is also a significant concern. Patents that do not describe features of a product undergoing FTO could certainly have claims that cover one or more of its features. For example, consider a cup having a handle. A patent may never describe a handle, but may claim a cup with circumferentially asymmetric mass distribution. A handle could likely fall within those bounds. These scenarios are quite common.

2.  Products tell a thousand stories.

Questions of patentability are often limited to a concept or a fixed set of concepts. The question hinges on a specific claim that is, by definition, a single textual sentence. On the other hand, FTO analysis centers on actual products. A product, by its physical presence, could be described in thousands of ways. For example, even a simple device implicates all of its structural components, its mass characteristics, its geometric characteristics, processes underlying its manufacture, and processes involving its use.

Anticipating all the ways in which a product can be described is serious guesswork. Opting to focusing on some ways and not others is an arbitrary exercise.

3.  Missing patents in an FTO search could be dire.

A final distinction between these types of searches lies in the consequences of missing key patent references. Missing key patent references in a patentability search is certainly not desirable. However, I would venture a guess that, if they were forced to choose, most companies would prefer to have a potentially invalid patent issue than a potentially infringing product launch.

Also, finding some relevant patents in a patentability search is helpful. In fact, perhaps, in an invalidity investigation, a few good references is all it takes; no need to lose sleep over the prospect of other patents lurking about. In other words, there are pro rata rewards to locating relevant patents in patentability searches; the more relevant patents we find, the better we understand the landscape of a feature.

Not true for an FTO search. Finding relevant patents “along the way” does not bring an analyst any closer to the finish line or provide any greater satisfaction that their work is complete. Finding some patents of concern is little indication of whether other patents exist that may also be of concern. That one missed patent could spell complete disaster for a product line or, worst case, a business.

These observations may not be news to experienced patent analysts, who have long understood the unique difficulties associated with FTO patent searching and analysis. What is notable, however, is that conventional analytical tools have not evolved to recognize these distinctions. They apply virtually the same processes to both patentability and FTO, despite their compelling distinctions.

These shortcomings will be discussed further in Part 2: Why Semantic Searching Fails for FTO.

Bridging the Divide Between Patent Analysts and Engineers


The communication divide between a company’s legal department and its engineering corps is an ongoing source of contention, confusion, and consternation for many companies. This divide is especially problematic in the patent context where legal matters are ever-intertwined with technical complexity. For example, successful drafting and prosecution of patent applications requires in-depth technical knowledge. Effective freedom-to-operate similarly necessitates an intimate understanding of a company’s products, development strategy and ability to anticipate product revision. Patent litigation and licensing nearly always involves technical expertise and a thorough understanding of the relevant art.

Because information needed to carry out these critical tasks is often “siloed” in different departments, tension and inefficiency often results. The technical team often perceives the legal team as overly reliant and thus deserving of “Class-A Inhibitor” status. We’ve worked with some companies that have even gone so far as to locate their legal department in a completely separate building from the engineers for fear of contaminating the creative process. Yet the technical team’s efforts to involve themselves in patent matters or to “take matters into their own hands” draw ire from the legal team.

This divide has been difficult to bridge. Solutions are less than optimal, and typically involve extensive back and forth communication between the departments and murky work product boundaries. The legal team must go to great lengths to sufficiently inform the engineering side about how patents should be read and understood to ensure that they are not dismissed inappropriately. For example, a common tendency is for engineers to read teachings from the specification into the claims, which can result in construing a critical patent too narrowly and an overlooked issue. At the other end, engineers must spend significant time preparing product specifications and informing the legal team about technical aspects that are not readily available from generally-accessible company documents. A frequent difficulty here is when certain aspects of a product or process of manufacture are simply not documented (e.g., aspects that are kept under tight security measures or even those that are common knowledge to the designers but are simply not readily known to others).

There is hope.

Clearstone Elements is a software tool developed primarily to carry out infringement-based analysis, such as FTO investigations, with great efficiency and accuracy. A remarkable and somewhat surprising aspect of the platform is that it naturally provides the ideal interface between the engineering corps and the legal department. The engineering side of the interface presents an interactive technical element hierarchy while the legal side of the interface allows the legal team to conduct the necessary patent analysis based on the engineers’ technical input. The engineers can use their interface to define the technical characteristics of a particular product or process under development without actually placing eyes on a single patent. Using pre-recorded mappings of technical concepts to claim language, significant numbers of “noisy” patents are eliminated from an initial patent set. Thus, the legal team is left only with the most relevant patents that may be implicated by the specified characteristics.

Here’s how it works:

Step 1: The patent analyst reviews the claims of a collection of patents and categorizes the claim elements into a technical element hierarchy (click to enlarge):

Patent Annotation: performed by patent analyst (services also available from ClearstoneIP)
Patent Annotation: Patent analyst annotates and categorizes claim elements (annotation services also available from ClearstoneIP)


Step 2: A member of the engineering team reviews the technical element hierarchy and creates a Product Record based on features not present in the product or process under development:

Product Mapping: Engineer selects technical features not embodied by product under development
Product Mapping: Engineer selects technical features not embodied by product under development


Step 3: Clearstone Elements eliminates irrelevant patents and leaves only the most critical patents for review by the patent analyst:

Patent Review: Patent analyst reviews the most relevant patents based on the engineer’s Product Record
Patent Review: Patent analyst reviews the most relevant patents based on the engineer’s Product Record


Step 4 (if needed): If the product later undergoes modifications, the engineer returns to the previously saved Product Record and makes the necessary changes to reflect the new technical characteristics. Clearstone Elements automatically identifies which patents become of issue due to the product changes:

Product Variation: Clearstone Elements automatically indicates which patents become of issue due to product changes
Product Variation: Clearstone Elements automatically indicates which patents become of issue due to product changes



Clearstone Elements supplies the perfect interface between the legal team and the technical team. Technical information is efficiently received from engineers in a manner that maintains the proper legal framework applicable to freedom-to-operate studies (and other infringement-based analysis). Patent analysts and engineers can now work together seamlessly and frequently throughout the entire product development cycle to realize tremendous gains in freedom-to-operate efficiency.  Now if only we could do something about Marketing…