v 14 argued the figure demonstrates how the data in the systems of record (9360) goes into the
15 ingestion box (9307) of the data processing system (9300), where electronic activities are then
Q 16 matched to record objects (Tr. 14-15). Counsel pointed to the box demarcating the data
= 17 processing system (9300), arguing defendants’ characterizations “just remove box 9300
. . . . . Z 18 altogether” (Tr. 15). Figure three depicts an embodiment of the invention, the search for an 19 inventive concept focuses on the language of the claim. And as explained, the language of the 20 claim does not preclude storage of the association in the CRM system itself. Because the 21 asserted claims do not require stroing associations separately from the systems of record, the 22 asserted claims do not recite the inventive concept People.ai has proffered. See Am. Axle & 23 Mfg., 967 F.3d at 1293; Interval Licensing LLC v. AOL, Inc., 869 F.3d 1335, 1348 (Fed. Cir. 24 2018). 25 Even if People.ai’s separation theory did make an appearance in the claim language, it 26 still falls short of qualifying as a transformative inventive concept. “Making associations 27 between electronic activities and record objects and storing them separate from the CRM” 28 describes, in substance, implementation of generic computer functionality akin to caching or
1 processing and storing data on a remote server. This fails to qualify as an inventive concept. 2 See, e.g., Customedia Techs., LLC v. Dish Network Corp., 951 F.3d 1359, 1365–66 (Fed. Cir. 3 2020); Smart Sys. Innovations, LLC v. Chicago Transit Auth., 873 F.3d 1364, 1374–75 (Fed. 4 Cir. 2017). Indeed, the stated benefits the claimed technical improvement address — avoiding 5 numerous API requests and permitting functionality without being connected to CRM — 6 reflect conventional improvements expected upon application of caching or remote-server 7 functionality. 8 People.ai submits the declaration of Oleg Rogynskyy, its CEO and a named inventor of 9 the seven patents-in-suit. The declaration fleshes out People.ai’s separation theory and its 10 alleged benefits, but at our procedural posture, review is limited to the contents of the pleading. 11 This order accordingly declines to consider Mr. Rogynskyy’s declaration. See Clegg v. Cult 12 Awareness Network, 18 F.3d 752, 754-55 (9th Cir. 1994); FRCP 12(d). In any event, this order 13 questions whether the declaration would provide much support since People.ai has not found a 14 hook for the inventive concept in the language of the claims. Further factual allegations would 15 not seem to rectify this flaw. 16 People.ai next argues that the ’129 patent embodies other, specific improvements, such as 17 “increasing efficiency of the system, reducing resource consumption, and eliminating the need 18 to run multiple searches across databases” (Opp. I at 16). People.ai notes that the specification 19 for the ’129 patent describes “the improvement over manual methods of matching, stating that 20 ‘due to the large volume of heterogenous electronic communications transmitted between 21 devices and the challenges of manually entering data, inputting the information regarding each 22 electronic communication into a system of record can be challenging, time consuming, and 23 error prone’” (Opp. I at 14, citing ’129 patent, col. 1:18–37). People.ai asserts that its 24 allegations regarding efficiency improvements “must be taken as true” and create fact issues 25 that “prevent resolving the subject matter inquiry” (Opp. I at 16; Opp. II at 19). But the law of 26 Federal Circuit is clear on this point: “[T]he improved speed or efficiency inherent with 27 applying the abstract idea on a computer does not provide a sufficient inventive concept.” 1 improvements expected when you incorporate a computer that amalgamates data from a 2 variety of sources, it has not generated a factual dispute. 3 People.ai also argues that claim 12 is specific and thus does “not preempt all automated 4 matching of electronic activities to record objects in CRM systems using rules” (Opp. I at 16). 5 For support, People.ai cites the Federal Circuit’s BASCOM opinion. BASCOM did not hold 6 that the scope of preemption dictated the outcome of the Alice analysis. Instead, it recognized 7 quite the opposite, stating that “simply because some of the claims narrowed the scope of 8 protection through additional ‘conventional’ steps for performing the abstract idea, they did not 9 make those claims any less abstract.” 827 F.3d at 1352. That reasoning applies here. 10 Moreover, the asserted claims have considerable breadth and the limitations they do recite 11 merely employ generic rules for accomplishing the abstract matching process contemplated by 12 the claim. 13 In sum, the elements of representative claim 20 fail to add something more and transform 14 the claim into a patent-eligible invention. The other claims of the ’129 patent People.ai cites in 15 its briefing or referenced at the hearing — claims 1, 11, 19, and 23 — are substantially similar 16 to claim 20 and linked to the same abstract idea. People.ai does not meaningfully distinguish 17 their limitations from those of claim 20. Because the asserted claims of the ’129 patent are 18 directed to an abstract idea and contain no transformative inventive concept, they run afoul of 19 Section 101 and do not qualify as patent-eligible subject matter. 20 3. THE ’106 PATENT (ASSERTED AGAINST CLARI). 21 The ’106 patent is entitled “Systems and Methods for Matching Electronic Activities 22 Directly to Record Objects of Systems of Record with Node Profiles.” After removing excess 23 jargon, representative claim 19 discloses a system with “one or more processors” configured 24 to: access electronic activities; access record objects stored in systems of record; extract data 25 in an electronic activity; “match the electronic activity to at least one record object . . . based 26 on the extracted data of the electronic activity and object field values” of the record object 27 using a matching policy “based on the one or more recipients or the sender of the electronic 1 People.ai admits “[f]or purposes of this analysis, claim 19 of the ’106 patent is 2 substantially the same as the claim 20 of the ’129 patent” (Opp. I at 18). Upon review, this 3 order agrees, and accordingly finds representative claim 19 of the ’106 patent directed to a 4 patent-ineligible abstract idea for the reasons previously stated for the claims of the ’129 5 patent. The other claims of the ’106 patent People.ai cites in its briefing or referenced at the 6 hearing — claims 1, 14, and 20 — are substantially similar to representative claim 19 and 7 linked to the same abstract idea. Further, People.ai does not meaningfully distinguish these 8 claims’ limitations from those of claim 19. The asserted claims of the ’106 patent are not 9 patent eligible under Section 101. 10 4. THE ’229 PATENT (ASSERTED AGAINST SETSAIL AND CLARI). 11 Next up is the ’229 patent, entitled “Systems and Methods for Matching Electronic 12 Activities Directly to Record Objects of Systems of Record.” Defendants argue that the claims 13 of the ’229 patent are ineligible under Section 101 for generally the same reasons they asserted 14 for the claims of the ’129 patent. People.ai acknowledges the similarities between the patents, 15 stating that its eligibility arguments for the ’129 patent claims apply “with equal force” to 16 representative claim 19 of the ’229 patent (Opp. I at 19; Opp. II at 21). 17 Stripped of excess verbiage, claim 19 of the ’229 patent recites a system comprising “one 18 or more processors” configured to: determine with a first policy that includes “one or more 19 filtering rules” that an electronic activity is to be “matched to at least one record object”; 20 identify a “first set of candidate record objects . . . based on . . . one or more recipients” of an 21 electronic activity; identify a “second set of candidate record objects . . . based on the sender of 22 the electronic activity”; and associate an electronic activity with a record object based on 23 “select[ing] at least one candidate record object in both the first . . . and the second set[s] of 24 candidate record objects”; and store the association in a data structure. 25 For Alice step one, People.ai contends that claim 19 of the ’229 patent “is further 26 removed [than the ’129 patent claims] from any alleged human activity or conventional system 27 because it identifies candidate record objects based on a second policy that includes a set of 1 based on senders” (Opp. II at 21–22; see also Opp. I at 19). Using the prototypical examples 2 of the patent terms discussed above reveals that claim 19 merely discloses the matching of an 3 email to a business record by cross-referencing two sets of records: one set generated by rules 4 based on the sender of the email, and a second set generated by a different batch of rules based 5 on the recipients of the email. This reflects a common business practice readily accomplished 6 in the human mind. Turning to our corporate salesperson analogy, the claim is directed to the 7 common practice of discarding junk mail, then filing a relevant communication in the correct 8 business file based on cross-referencing two sets of potential files, one based on the sender and 9 the other on the recipients. The analogy does not break down, as People.ai asserts, just because 10 the salesperson must apply several different sets of rules for filtering and compiling the sets of 11 records that are cross-referenced. This is a long common practice. The claim is directed to an 12 abstract idea. See Symantec, 838 F.3d at 1317–18. 13 People.ai also contends several dependent claims of the ’229 patent provide “further 14 specificity” and recite “specific techniques.” (see Opp. I at 3; Opp. II at 21). As an example, 15 People.ai states that claim 11 recites the additional limitation that a specific object field be used 16 in matching — the relevant team. This additional limitation does not merit a different result. 17 Considering subgroups such as teams and working groups is a common business practice. 18 Claim 11 is also directed to an abstract idea. 19 For Alice step two, People.ai asserts the same inventive concept theory for the claims of 20 the ’229 patent as it did for the claims of the ’129 patent (Opp. I at 19–20; Opp. II at 23). As 21 explained in more detail above, the concept of storing associations between electronic 22 activities and record objects separately from the CRM is not recited in the claims of the ’229 23 patent, nor is it an inventive concept. In the hearing, counsel stated: “You wouldn't need to 24 identify a system of record . . . if there was only one and you were operating within it” (Tr. 32). 25 But again, the claim recites “one or more systems of record” (emphasis added). 26 The other claims of the ’229 patent People.ai cites in its briefing or referenced at the 27 hearing — claims 6, 7, and 11 — are substantially similar to representative claim 19 and linked 1 limitations from those of claim 19. The asserted claims of the ’229 patent are not patent 2 eligible under Section 101. 3 5. THE ’783 PATENT (ASSERTED AGAINST CLARI). 4 We next consider the ’783 patent, entitled “Systems and Methods for Generating New 5 Record Objects based on Electronic Activities.” Representative claim 12 of the ’783 patent 6 discloses, after removing excess jargon, a system comprising “one or more processors” 7 configured to: “determine . . . that an electronic activity is to be matched” to a record object; 8 “determine for each candidate record object” a “match score indicating a likelihood of the 9 electronic activity matching the candidate record object” by “comparing the activity field-value 10 pairs to the object-field value pairs” of the candidate record objects; generate a new record 11 object with its type “based on one or more participants of the electronic activity” if the match 12 score does not satisfy a threshold; and store the association “in one or more data structures.” 13 Under Alice step one, Clari contends the claims of the ’783 patent are directed to an 14 abstract idea for the same reasons it asserted for the claims of the ’129 patent. People.ai 15 disagrees, arguing that representative claim 12 is more specific because it “specifically require 16 determining ‘a match score’” (Opp. I at 3–4, 21). To begin, this specificity argument fails for 17 the same reasons previously laid out in the analysis of McRO above. Claim 12 addresses 18 whether to associate a communication with an existing record or to create a new record if it is 19 unlikely any of the existing records are a good match (’783 patent at Abstract). This is a long 20 prevalent, fundamental human practice readily performed by our corporate salesperson. See 21 Return Mail, 868 F.3d at 1368. 22 Considering the match score in more detail, the asserted claims describe the limitation in 23 functional terms. And the specification provides only generic, abstract instructions on the 24 actual calculation of a match score. The specification does not elaborate on the calculation of a 25 match score between an electronic activity and a record object. It does however, provide some 26 detail for a match score between an electronic activity and a node profile, which is still 27 insightful for our purposes: a match score between the electronic activity and a candidate node 1 profile by comparing the strings or values of the electronic activity match corresponding values of the candidate node profile. The 2 match score can be based on a number of fields of the node profile including a value that matches a value or string in the electronic 3 activity. The match score can also be based on different weights applied to different fields. The weights may be based on the 4 uniqueness of values of the field 5 (’783 patent, col. 21:48–58). The specification merely explains that the system should 6 compare the data in the communication with the data in a data profile, and that comparison 7 could weigh different datapoints differently. The specification does not describe how the 8 match score should be constructed. The claim’s disclosure of a “match score” is thus a black 9 box for performing the desired abstract function. In other words, the claim invokes a structure 10 but, in substance, is directed to a particular end result. See Alice, 573 U.S. at 223; Two-Way 11 Medial Ltd. v. Comcast Cable Comms., LLC, 874 F.3d 1329, 1337 (Fed. Cir. 2017); see also 12 Visual Memory LLC v. Nvidia Corp., 867 F.3d 1253, 1263 (Fed. Cir. 2017) (Hughes, J., 13 dissenting). The claim is directed to an abstract idea. 14 Under Alice step two, the parties’ arguments align with those previously discussed. 15 People.ai’s contends that storing associations outside the CRM is an inventive concept here 16 because it “improve[s] the . . . quality and health of the system of record,” and “improve[s] the 17 quality of analytics that can be derived from the system.” (Opp. I at 21). This theory fails for 18 the same reasons previously addressed, and for the additional reason that these highlighted 19 improvements amount to mere efficiency gains. The improvements that come with the 20 incorporation of a computer fail to qualify as an inventive concept. See Symantec, 838 F.3d at 21 1315. In sum, representative claim 12 of the ’783 patent does not disclose an inventive 22 concept. 23 The other claim of the ’783 patent People.ai cites in its briefing or referenced at the 24 hearing — claim 13 — is substantially similar to representative claim 12 and linked to the 25 same abstract idea. Further, People.ai does not meaningfully distinguish that claim’s 26 limitations from those of claim 12. The asserted claims of the ’783 patent are not patent 27 eligible under Section 101. 6. THE ’345 PATENT (ASSERTED AGAINST CLARI). 1 2 Up next, the ’345 patent, entitled “Systems and Methods for Filtering Electronic 3 Activities by Parsing Current and Historical Electronic Activities.” Stripped of excess 4 verbiage, representative claim 11 of the ’345 patent recites a system comprising “one or more 5 processors” configured to: identity a first electronic activity and a second electronic activity; 6 parse the first electronic activity to identify the sender or the recipient(s); select one or more 7 filtering policies to apply including at least one of (i) a keyword policy, (ii) a regex pattern 8 policy, or (iii) a logic-based policy; apply the filtering policies “to restrict the first electronic 9 activity from being matched with one or more record objects”; apply the filtering policies and 10 match the second electronic activity to a record object based on a “match policy”; “transmit, to 11 the system of record, instructions to store an association between the second electronic activity 12 and the first record object in the system of record.” 13 The parties make substantially the same arguments for Alice step one as those discussed 14 previously (Opp. I at 4, 22). For the same reasoning outlined above, this order finds claim 11 15 directed to the abstract idea of data processing by restricting certain data from further analysis 16 based on various sets of generic rules. Our corporate salesperson has long conducted this 17 activity every time she discards the junk mail before updating the business files she maintains 18 with relevant communications. 19 Under Alice step two, we first consider People.ai’s argument that claim 11 is patent 20 eligible because it reduces computing resources and the amount of noise in the CRM systems, 21 and thus improves the operation of the CRM systems (Opp. I at 22–23). See Enfish, 822 F.3d 22 at 1339. Again, all People.ai claims is the beneficial result of increased efficiency that flows 23 from filtering with a computer prior to inputting the data in CRM, not a specific improvement 24 in computing. The filtering policies that the claim recites rank as simple, generic filtering 25 methods, such as looking for certain keywords. This does not qualify as an inventive concept. 26 See Two-Way Media, 874 F.3d at 1337; Symantec, 838 F.3d at 1314. 27 But we have a twist at step two for the ’345 patent. As explained, People.ai contends the 1 “are directed to storing associations outside of the CRM” (Opp. II at 1; see also Opp. I at 1). 2 But unlike the other asserted claims of the other patents-in-suit, claim 11 of the ’345 patent 3 explicitly discloses a system that “transmit[s], to the system of record, instructions to store an 4 association between” the electronic activity and the record object “in the system of record” 5 (’345 patent, col. 193:51–53). 6 People.ai tries to explain away the difference: “By performing the steps locally and then 7 transmitting to the system of record, the invention is able to avoid carrying out the filtering and 8 matching steps with the CRM and it is able to avoid issues with syncing and connection that 9 are outlined” for the other claims. (Opp. I at 23). But this does not follow. First, and 10 foremost, claim 11, similar to the claims of the ’129 patent, recited “one or more processors” 11 and does not define the location or relationship of the claimed system to the CRM. Second, it 12 is unclear how the claimed system avoids issues with syncing and connection without being 13 able to control when the transmission to the CRM takes place. This timing issue would seem 14 to require the claimed system to be able to store the association in the claimed system. But the 15 claim only discloses storage in the CRM. Unclaimed features are irrelevant to the Alice 16 analysis, and the inventive concept People.ai describes is not recited in the language of the 17 claim. See ChargePoint, 920 F.3d at 766, 769; Am. Axle & Mfg., 967 F.3d at 1293. 18 Moreover, as explained above in the analysis of the ’129 patent, even if this order found a 19 hook for People.ai’s proffered inventive concept in the claims of the ’345 patent, the notion of 20 having the filtering and matching taking place in the claimed system and outside the CRM 21 amounts to caching or data processing via a remote server, concepts that the Federal Circuit 22 has found to be generic computer functionality. See, e.g., Customedia, 951 F.3d at 1365–66; 23 Smart Sys. Innovations, 873 F.3d at 1374–75. In short, claim 11 does not contain an inventive 24 concept. 25 The other claim of the ’345 patent People.ai referenced in its briefing or at the hearing — 26 claim 18 — is substantially similar to representative claim 11 and linked to the same abstract 27 idea. Further, People.ai does not meaningfully distinguish that claim’s limitations from those 7. THE ’634 PATENT (ASSERTED AGAINST SETSAIL AND CLARI). 1 2 We next consider the ’634 patent, entitled “Systems and Methods for Determining a 3 Completion Score of a Record Object from Electronic Activities.” Representative claim 10 of 4 the ’634 patent discloses a system comprising “one or more processors” configured to: select a 5 record object from one or more systems of record; identify “electronic activities . . . associated 6 with the first record object”; determine “at least one participant of each of the . . . electronic 7 activities”; determine, for each participant “at least one of a role, a title, or a department 8 corresponding to the . . . participant”; “determine a completion score indicating a likelihood of 9 completing an event associated with the first record object, the completion score based on the 10 timestamp of each of the plurality of electronic activities and at least one of the role, the title, 11 or the department of the at least one participant of each of the plurality of electronic activities”; 12 and store “in one or more data structures” the association between the record object and the 13 completion score. 14 Under Alice step one, similar to the asserted claims of the ’129 patent, claim 10 of 15 the ’634 patent is directed to a long standing economic practice that is readily performed by a 16 corporate salesperson. Assessing the likelihood that a deal will close based on who the 17 salesperson is negotiating with — e.g., with a junior project manager or with the CEO — and 18 when those communications occurred — e.g., yesterday or two years ago — is an elementary 19 business concept. The specification acknowledges this, stating “enterprises rely on the data 20 included in their systems of records to make projections or predictions on deals” (’634 patent, 21 col. 177:32-33). 22 People.ai disagrees with this assessment, saying that the determination of a completion 23 score is not human conduct. The specification describes a “completion score module” that 24 calculates the completion score, but provides only general, functional guidance on how the 25 module would calculate the score based on the timestamp of the electronic activity, and at least 26 one of the role, title, or the department of the participant of the electronic activity (’634 patent 27 fig. 28, cols. 179:43–180:46). Similar to the “match score” discussed previously, the 1 the likelihood of completing an event. In short, the claim invokes a structure but is merely 2 directed to an end result. See, e.g., Dropbox, Inc. v. Synchronoss Techs., Inc., 815 Fed. App’x 3 529, 533 (Fed. Cir. 2020). 4 People.ai next reiterates its specificity arguments, stating claim 10 provides a specific 5 way of calculating a completion score (Opp. II at 23). For the same reasons laid out previously 6 this theory misstates the reasoning of McRO. The claims here do not replace artists with rules. 7 Rather, they are directed to applying conventional rules with generic characteristics to ensure 8 efficient data processing (e.g., ’634 patent, col. 177:36–55). The claims of the ’634 patent are 9 directed to an abstract idea. 10 Moving to Alice step two, People.ai argues the claims of the ’634 patent contain an 11 inventive concept because they “are directed to calculation of a completion score based on 12 constantly changing variables that may be aggregated and compared for the purpose of 13 predicting a likelihood of the completion of a certain event” (Opp. II at 25). People.ai further 14 explains that “prior systems did not allow for the prediction of revenue generating events based 15 on real-time data or the use of matched emails to generate completion scores” (Opp. I at 25). 16 In substance, People.ai has simply highlighted the advantages of using a computer to quickly 17 crunch the numbers. The claim only recites generic hardware and software. It does not 18 progress beyond reciting the abstract idea of determine the likelihood of a given event 19 completing and then saying “apply it” with computer software. As this order has emphasized, 20 “merely adding computer functionality to increase the speed or efficiency of the process does 21 not confer patent eligibility on an otherwise abstract idea.” Intellectual Ventures I LLC v. 22 Capital One Bank (Capital One II), 850 F.3d, 1363, 1370 (Fed. Cir. 2015). 23 Additionally, People.ai also reiterates its separation theory: 24 [The ’634 patent’s] concrete improvements include the determination of accurate predictions of revenue generating events, 25 and the presentation of such predictions to business decision makers, making it possible for the enterprise to obtain the benefit 26 of the data within its systems of record without having to access servers on which the electronic activities matched to the record 27 objects are stored 1 (Opp. II at 25, citing SetSail Sec. Amd. Compl. ¶ 70). People.ai reminds we must accept these 2 factual allegations as true (ibid.). But the problem is, as explained in detail in the review of 3 the ’129 patent claims, this inventive concept is not found in the language of the claim. 4 People.ai here focuses on the separation between the claimed system and the system that stores 5 the electronic activities. But claim 10 only discloses “one or more hardware processors,” not 6 the location of the claimed system relative to the system that stores the electronic activities. 7 Moreover, as Clari notes, the claim also recites “identify[ing] a plurality of electronic activities 8 transmitted or received via electronic accounts and associated with the first record object” 9 (’634 patent, col. 196:51–53). This order finds the system architecture asserted by People.ai is 10 not found in the claim, and hence cannot qualify as the claim’s inventive concept. And as 11 explained, even if the separation theory was found in the claim, it does not qualify as an 12 inventive concept. See Interval Licensing, 869 F.3d at 1348; ChargePoint, 920 F.3d at 769. 13 The other claim of the ’634 patent People.ai cites in its briefing or referenced at the 14 hearing — claim 17— is substantially similar to representative claim 10 and linked to the same 15 abstract idea. Claim 17, dependent on claim 10, recites a “stage value,” which serves as 16 another generic input comparable to the recited timestamps (stage values will be discussed 17 further for the ’132 patent). People.ai does not meaningfully distinguish the limitations of 18 claim 17 from those of claim 11. In sum, the asserted claims of the ’634 patent are not patent 19 eligible under Section 101. 20 8. THE ’132 PATENT (ASSERTED AGAINST CLARI). 21 Finally, the ’132 patent is entitled “Systems and Methods for Forecasting Record Object 22 Completions.” Stripped of draftsmanship, representative claim 12 recites a system comprising 23 “one or more processors” configured to: access data from electronic activities associated with 24 a given record object that includes “a first object field-value pair identifying a stage of a 25 process”; parse the data of the electronic activities; determine the role of the participant based 26 on their seniority, department, or role; determine for the record object “a likelihood that the 27 process . . . will be completed within a predetermined time . . . based on . . . the stage of the 1 structures.” A field-value pair is a standard data entry, such as “associating a value of John to 2 the first name field” (’132 patent, cols. 149:16–21). As for stages of the process, the “stages 3 can include, but are not limited to: prospecting, developing, negotiation, review, closed/won, 4 or closed/lost” (id. at col. 68:35–37). Clari contends that the ’132 patent is directed towards an 5 abstract concept for the same reasons as the ’634 patent. People.ai acknowledges that 6 exemplary claim 12 of the ’132 patent “is similar to claim 10 of the ’634 patent” (Opp. I at 24). 7 Under Alice step one, this order finds that determining the likelihood that a given process 8 will be completed in a predetermined amount of time is a longstanding commercial practice 9 readily performed by our corporate salesperson. A corporate salesperson uses information 10 such as the role of the participant on the other side of the deal (e.g., CEO or junior project 11 manager), the stage of the process (e.g., prospecting or closing), and the information compiled 12 from emails to estimate the likelihood of a given event occurring on a particular timetable. 13 The ’132 patent recognizes that businesses often make these types of predictions and 14 projections (’132 patent, col. 50:13–17). 15 People.ai contends that claim 12 of the ’132 patent “is more specific [than claim 10 of the 16 ’634 patent] and includes additional inputs making it even more removed from activities that 17 might be carried out by a human being” (Opp. I at 24). But for the same reasons laid out 18 above, none of the limitations that claim 12 recites are meaningful or recite a specific 19 improvement in computing. The stage of the process is the new input here, and according to 20 the specification, it can either be defined by the user or determined by the system using a 21 “stage classification engine” (’132 patent, col. 68:29–37). Either way, the stage value is 22 another black box for performing the desired abstract function: either the user makes the 23 determination the same way our corporate salesperson had always evaluated the stage of the 24 deal, or the patent invokes the stage classification engine and applies generic computer 25 functionality to make the determination. To that end, the specification explains: 26 The stage classification engine (325) can be any script, file, program, application, set of instructions, or computer-executable 27 code, that is configured to enable a computing device on which the 1 (id. at col. 68:19-24). The stage value limitation is thus analogous to the “match score” and 2 “completion score” previously addressed. Claim 12 of the ’132 patent is directed to an abstract 3 idea. 4 Under Alice step two, People.ai asserts the same arguments it gave for the claims of the 5 °634 patent. They fail for the same reasons. In addition, the “calculation of a completion score 6 based on constantly changing variables” and “dynamically determining a completion score for 7 a business opportunity” equate to adding computer functionality to increase speed and 8 efficiency (Opp. I at 25). This does not amount to an inventive concept. See Capital One II, 9 792 F.3d at 1370. 10 People.ai did not address any further claims of the °132 patent beyond claim 12 in its 11 briefing or at the hearing. In sum, the asserted claims of the 132 patent are not patent eligible 12 under Section 101. 13 CONCLUSION 14 For the reasons stated, the motions for judgment on the pleadings are GRANTED. The 3 15 asserted claims of the °129, °106, °229, ’783, °345, 634, and the ’132 patents are invalid as a 16 patent ineligible under Section 101. IT IS SO ORDERED. 18 19 Dated: December 13, 2021. Ls Pee 21 ~ WILLIAM ALSUP 22 UNITED STATES DISTRICT JUDGE 23 24 25 26 27 28