Критерии создания регламента проверки контрагентов
Пошаговая подготовка внутреннего документа.
Details
LLC "YEMS IT"
Saint Petersburg
OGRN: 1227800154120
TIN: 7804697730
Active
Profile views
27
+3 last week
Subscribers
0
+0 last week
OKVED2 62.01 Total: 6
Computer programming activities
Monitoring Notes Reports Contact information
34,55
mln ₽, 2024
Revenue
+₽23mln
CEO
Yakovlev Nikolai Petrovich
32
Reliability Score
CEO
Yakovlev Nikolai Petrovich
2
years
Established
November 28, 2022
City Saint Petersburg
34,55
mln ₽, 2024
Revenue
+₽23mln
4
Connections
+0 last week
6
Employees
-1 last year

Taxes & Levies

Tax and levy liabilities

Taxes
Total amount as of ▒▒.▒▒.2025: ▒▒▒▒▒ ₽
Type of Debt
Underpayment
Late fee
Fines
Total
▒▒▒▒▒▒ ▒▒▒
▒▒▒▒▒ ₽
▒▒▒▒▒ ₽
▒▒▒▒▒ ₽
▒▒▒▒▒ ₽
Other
Total amount as of ▒▒.▒▒.2025: ▒▒▒▒▒ ₽
Type of Debt
Underpayment
Late fee
Fines
Total
▒▒▒▒ ▒▒ ▒ ▒▒▒▒▒▒▒ ▒▒▒
▒▒▒▒▒ ₽
▒▒▒▒▒ ₽
▒▒▒▒▒ ₽
▒▒▒▒▒ ₽

Paid taxes and levies

2023

Taxes
Total amount: ▒▒▒▒▒ ₽
Name
Paid amount as of ▒▒.▒▒.2023
▒▒▒ ▒▒▒ ▒▒▒▒▒▒ ▒▒ ▒▒▒▒▒▒▒▒▒▒ ▒▒▒▒ ▒▒▒▒▒▒▒▒▒▒▒ ▒▒ ▒ ▒▒▒▒▒▒▒▒▒▒ ▒▒▒ ▒▒▒▒▒▒
▒▒▒▒▒ ₽
Contributions
Total amount: ▒▒▒▒▒ ₽
Name
Paid amount as of ▒▒.▒▒.2023
▒▒▒ ▒▒▒▒▒▒▒▒▒ ▒▒▒▒▒▒▒▒ ▒▒▒ ▒▒▒▒▒▒▒▒▒▒ ▒▒▒▒▒▒ ▒▒▒▒▒▒▒▒▒ ▒▒ ▒▒▒ ▒▒▒▒▒▒▒ ▒▒▒▒▒▒▒▒▒▒ ▒▒▒▒▒▒▒▒ ▒▒ ▒▒▒ ▒▒▒▒▒▒ ▒▒ ▒▒▒▒▒▒▒ ▒▒▒▒▒▒▒▒▒▒ ▒▒▒▒▒▒ ▒▒▒▒▒▒▒▒▒ ▒▒▒▒
▒▒▒▒▒ ₽
▒▒▒▒▒▒▒▒▒ ▒▒▒▒▒▒▒▒ ▒▒▒ ▒▒▒▒▒▒▒▒▒▒ ▒▒▒▒▒▒ ▒▒▒▒▒▒▒▒▒ ▒▒▒ ▒▒▒ ▒▒▒▒ ▒▒ ▒▒▒▒▒▒▒▒▒ ▒▒▒▒▒▒▒▒▒▒ ▒▒▒ ▒▒ ▒▒▒▒▒▒▒▒▒▒ ▒▒▒▒ ▒▒▒▒▒▒▒▒▒▒
▒▒▒▒▒ ₽
▒▒▒ ▒▒▒▒▒▒▒▒▒ ▒▒▒ ▒▒▒▒▒ ▒▒▒▒▒▒▒▒ ▒▒▒ ▒▒▒▒▒▒▒▒▒ ▒▒▒▒▒▒▒ ▒▒▒▒▒▒▒▒▒ ▒▒▒▒▒▒▒▒ ▒▒ ▒▒▒ ▒▒▒▒▒▒▒ ▒▒▒▒ ▒▒ ▒▒▒ ▒▒▒▒▒▒▒ ▒▒▒▒▒▒▒▒▒▒
▒▒▒▒▒ ₽
Other
Total amount: ▒▒▒▒▒ ₽
Name
Paid amount as of ▒▒.▒▒.2023
▒▒▒▒▒ ▒▒▒▒▒
▒▒▒▒▒ ₽

2022

Taxes
Total amount: ▒▒▒▒▒ ₽
Name
Paid amount as of ▒▒.▒▒.2022
▒▒▒ ▒▒▒ ▒▒▒▒▒▒ ▒▒ ▒▒▒▒▒▒▒▒▒▒ ▒▒▒▒ ▒▒▒▒▒▒▒▒▒▒▒ ▒▒ ▒ ▒▒▒▒▒▒▒▒▒▒ ▒▒▒ ▒▒▒▒▒▒
▒▒▒▒▒ ₽
Contributions
Total amount: ▒▒▒▒▒ ₽
Name
Paid amount as of ▒▒.▒▒.2022
▒▒▒ ▒▒▒▒▒▒▒▒▒ ▒▒▒ ▒▒▒▒▒ ▒▒▒▒▒▒▒▒ ▒▒▒ ▒▒▒▒▒▒▒▒▒ ▒▒▒▒▒▒▒ ▒▒▒▒▒▒▒▒▒ ▒▒▒▒▒▒▒▒ ▒▒ ▒▒▒ ▒▒▒▒▒▒▒ ▒▒▒▒ ▒▒ ▒▒▒ ▒▒▒▒▒▒▒ ▒▒▒▒▒▒▒▒▒▒
▒▒▒▒▒ ₽
▒▒▒ ▒▒▒▒▒▒▒▒▒ ▒▒▒▒▒▒▒▒ ▒▒▒ ▒▒▒▒▒▒▒▒▒▒ ▒▒▒▒▒▒ ▒▒▒▒▒▒▒▒▒ ▒▒ ▒▒▒ ▒▒▒▒▒▒▒ ▒▒▒▒▒▒▒▒▒▒ ▒▒▒▒▒▒▒▒ ▒▒ ▒▒▒ ▒▒▒▒▒▒ ▒▒ ▒▒▒▒▒▒▒ ▒▒▒▒▒▒▒▒▒▒ ▒▒▒▒▒▒ ▒▒▒▒▒▒▒▒▒ ▒▒▒▒
▒▒▒▒▒ ₽
▒▒▒▒▒▒▒▒▒ ▒▒▒▒▒▒▒▒ ▒▒▒ ▒▒▒▒▒▒▒▒▒▒ ▒▒▒▒▒▒ ▒▒▒▒▒▒▒▒▒ ▒▒▒ ▒▒▒ ▒▒▒▒ ▒▒ ▒▒▒▒▒▒▒▒▒ ▒▒▒▒▒▒▒▒▒▒ ▒▒▒ ▒▒ ▒▒▒▒▒▒▒▒▒▒ ▒▒▒▒ ▒▒▒▒▒▒▒▒▒▒
▒▒▒▒▒ ₽
Data sources Information on paid taxes and fees is collected from public sources.

Accurate binding to a company can be created only if the information source contains its TIN and OGRN values. If identification details are not specified, the binding is created by using linguistic algorithms. Although these algorithms are being constantly improved, some information may be absent.

If you have noticed an error or lack of information, please let us know about it. Let's improve Seldon.Basis together!

Data sources Information on paid taxes and fees is collected from public sources.

Accurate binding to a company can be created only if the information source contains its TIN and OGRN values. If identification details are not specified, the binding is created by using linguistic algorithms. Although these algorithms are being constantly improved, some information may be absent.

If you have noticed an error or lack of information, please let us know about it. Let's improve Seldon.Basis together!