Prosecution Insights
Last updated: October 04, 2026

ThoughtSpot, Inc.

Technology area: Computing & Software

4 pending office actions • 3 art units • 3 examiners • 0 of 4 (0%) have an AI response strategy ready • 9 patents granted in the last 365 days

Analysis

ThoughtSpot, Inc. has 4 pending office actions in the Computing & Software technology area. These actions are spread across 3 distinct art units, showing a diverse technical footprint within the software sector. The prosecution involves 3 distinct examiners, which closely matches the number of art units involved. This distribution across 3 distinct art units suggests that the company's software innovations are being reviewed by multiple specialized groups within the patent office.

The busiest examiner is KIM, PAUL, who is handling 2 of the pending office actions. This means half of the company's 4 pending actions are under the review of a single individual. The remaining actions are distributed among the other 2 distinct examiners, requiring the company to manage multiple examiner preferences across 3 distinct art units. With 4 pending office actions and 3 distinct examiners, the company must balance the specific feedback from KIM, PAUL with the requirements of the other 2 distinct examiners.

Written from this page's own data; every figure is computed from USPTO records and verified before publication.

Portfolio Summary

4
Total Pending OAs
2
Non-Final OAs
1
Final Rejections
1
Advisory / Quayle

Response Deadline Pressure

Based on the USPTO statutory response window for each pending office action. 1 of the docket's apps have a known mailing date; the rest are excluded from the tile counts.

0
Overdue
0
Due this week
0
Due this month
1
Due in next 60 days
0
Due later

Case Difficulty Mix

Difficulty is derived from the rejection statutes on the most recent pending office action. §101-driven and multi-statute cases are graded Hard; §112-only and obviousness-type double-patenting cases are graded Easy; everything else is Medium. "Unknown" means we have not yet parsed a statute for that office action.

4
Hard (100%)
0
Medium (0%)
0
Easy (0%)
0
Unknown (0%)

Rejection Statute Mix

BucketCases
§101 only1 (25%)
§101 + other2 (50%)
Multi-statute (no §101)1 (25%)

Industry Mix

How the docket's pending cases split across USPTO tech-center bands.

0
Life Sciences
0% of docket
4
Information Tech
100% of docket
0
Communications
0% of docket
0
Semiconductors
0% of docket
0
Mechanical / Eng
0% of docket
0
Business / Other
0% of docket

Time-on-OA Estimate

Manual office-action response work runs about 10 hours per case. The time-saved bands below show what IP Author's prosecution pipeline typically delivers — a conservative 20% on the low end, 35% in the middle, 50% on the high end.

40 h
Manual time on pending OAs
8 h
Time saved (low, 20%)
14 h
Time saved (mid, 35%)
0.3 wks
FTE-weeks freed (mid)

Top Examiners on this docket

ExaminerApps on this docketAllow rateInterview lift
KIM, PAUL 2 73.0% +19.9%
CHBOUKI, TAREK 1 81.2% +24.0%
ROY, SANCHITA 1 72.1% +47.5%

Hard Cases (4)

Multi-statute / §101-driven matters, or cases in front of an examiner with an allow rate under 30%. The top 4 ordered by deadline are shown.

App #TitleExaminerDue in
17879055 Insight Mining Using Machine Learning ROY, SANCHITA 34d
19282422 OBTAINING RESULTS DATA USING AGENTIC ANALYSIS CHBOUKI, TAREK —
19064943 Mapping Natural Language To Queries Using A Query Grammar KIM, PAUL —
18442193 Automatic Target Visualization Adaptation KIM, PAUL —

Interview Candidates (4)

Cases in front of an examiner whose interview lift is 10 percentage points or more — i.e. interviewed cases historically resolve more favorably than non-interviewed ones. The top 4 ordered by deadline are shown.

App #TitleExaminerDue in
17879055 Insight Mining Using Machine Learning ROY, SANCHITA 34d
19282422 OBTAINING RESULTS DATA USING AGENTIC ANALYSIS CHBOUKI, TAREK —
19064943 Mapping Natural Language To Queries Using A Query Grammar KIM, PAUL —
18442193 Automatic Target Visualization Adaptation KIM, PAUL —

Top Art Units

Art UnitApps
2152 2
2165 1
2146 1

Pending Office Actions

App #TitleExaminerArt UnitStatutesStatusDue inAIFiled
19282422 OBTAINING RESULTS DATA USING AGENTIC ANALYSIS CHBOUKI, TAREK 2165 §101§102§103Other Non-Final OA — Pending Jul 28, 2025
19064943 Mapping Natural Language To Queries Using A Query Grammar KIM, PAUL 2152 §102§103 Non-Final OA — Pending Feb 27, 2025
18442193 Automatic Target Visualization Adaptation KIM, PAUL 2152 §101 Non-Final OA — Pending Feb 15, 2024
17879055 Insight Mining Using Machine Learning ROY, SANCHITA 2146 §101§103§112 Final Rejection 34d Pending Aug 02, 2022

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