PATLY.AIExaminer difficulty
How examiners in this art unit compare
The spread of examiners on each measure. Click a bar to see who is in it.
3-year grant rate
56%
level with tech center 1600 allowed within 3 years of the first action
Allowance rate
61%
level with tech center 1600 range 60% to 62%
Rejections before allowance
2.0
+0.2 vs tech center 1600
Months to first action
20.6 mo
+3.9 vs tech center 1600
In plain words
With Art unit 1637, 56% of applications were allowed within three years of the first office action, against 56% for tech center 1600. The first action takes 20.6 months on average.
Timeline
Applications by filing year: drag across the years to study a period
Allowed in green, abandoned in red, pending in grey. The figures above and every chart that can be recomputed by filing year follow the span you pick; the rest are marked all years.
Ask the record
Questions practitioners ask, answered from 12,375 applications
Grant rate from the first action
Share allowed, by months after the first office action
The gold line is this record and the blue line is tech center 1600. The marker is the three-year grant rate.
Outcome simulator
Where you are, what you do next, and the odds that follow
A model of this record’s own transitions: each examiner action, the response to it, and what came next. Thin data borrows from tech center 1600.
Prosecution paths
How prosecution actually unfolds
Every application’s sequence of examiner actions, from the first action to the outcome. Hover a band for the count.
Compared with peers
Against the art unit, the tech center and the USPTO
The same figures for this record, tech center 1600, the tech center and the whole office.
Allowance over time
How fast applications are allowed, or abandoned
Share allowed (gold) and abandoned (red) by month since filing, with pending cases counted only while they are pending.
Rejection fingerprint
What gets rejected, by statute
Share of office actions raising each ground; blue is tech center 1600.
What works
Allowance by strategy used
Allowance rate among decided cases where each move was used at least once, against tech center 1600.
Interviews
Does an interview help?
Allowance with and without an examiner interview, and how often interviews happen.
Odds by round
Chance the next action is an allowance
After the first, second and later rejections.
Response clock
Days from a response to the next action
How long the examiner takes to act once you have answered.
Quarter-end timing
When allowances land in the fiscal quarter
Allowances by week of the USPTO fiscal quarter. An even spread would put 15% in the last two weeks.
Appeals
What happens on appeal
Appeals filed, briefs, examiner’s answers, and how the Board decided.
Trend
Allowance rate by filing year
Is it getting easier or harder? Gold is this record, blue is tech center 1600.
Who files here
Assignees and firms with the most applications
How often each one was allowed with this unit.
Landscape
Examiners across tech center 1600
Each dot is an examiner: allowance rate across, rejections before allowance down, size by caseload. Click one to open it.
Examiners
Every examiner in the unit, ranked by difficulty
| Examiner | Applications | Allowance rate | Difficulty |
|---|---|---|---|
| Danna E Bicknell | 42 | 14% | P91 Harder than peers |
| Suryaprabha Chunduru | 791 | 47% | P91 Harder than peers |
| Christina L Tran | 178 | 36% | P85 Harder than peers |
| Keyur Anilkumar Vyas | 162 | 41% | P85 Harder than peers |
| Angela Marie Bertagna | 712 | 44% | P85 Harder than peers |
| Bonnie Tsun Lau | 4 | 25% | P82 |
| Mark Staples | 101 | 26% | P78 Harder than peers |
| Suchira Pande | 226 | 42% | P71 Typical for peers |
| Alexandra Rose Lippolis | 125 | 36% | P70 Typical for peers |
| Stephanie Kane Mummert | 805 | 62% | P69 Typical for peers |
| Gary Benzion | 136 | 25% | P64 Typical for peers |
| Olayinka A Oyeyemi | 547 | 59% | P62 Typical for peers |
| Julio Washington Gomez Rodriguez | 109 | 28% | P62 Typical for peers |
| Jenna L Persons | 152 | 50% | P59 Typical for peers |
| Teresa E Strzelecka | 818 | 53% | P56 Typical for peers |
| Joyce Tung | 254 | 56% | P54 Typical for peers |
| Young J Kim | 1,280 | 62% | P53 Typical for peers |
| Sarah Elizabeth Allen | 118 | 43% | P46 Typical for peers |
| Samuel C Woolwine | 900 | 64% | P46 Typical for peers |
| John Charles McKillop | 102 | 55% | P45 Typical for peers |
| Ardin H Marschel | 201 | 51% | P44 Typical for peers |
| Tiffany Nicole Grooms | 288 | 57% | P40 Typical for peers |
| Heather Calamita | 171 | 38% | P35 Typical for peers |
| Christopher M Babic | 360 | 59% | P29 Typical for peers |
| Lexus Marc Tatge | 92 | 22% | P28 Typical for peers |
| Cynthia B Wilder | 1,004 | 70% | P18 Easier than peers |
| Aaron A Priest | 1,264 | 69% | P16 Easier than peers |
| Molly E Baughman | 13 | 69% | P13 |
| Jezia Riley | 1,480 | 82% | P11 Easier than peers |
| Kenneth R Horlick | 1,116 | 79% | P10 Easier than peers |
| David C Thomas | 956 | 80% | P8 Easier than peers |