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BRAIN SCIENTIFIC INC.: filings

Every BRAIN SCIENTIFIC INC. annual and quarterly report in the SEC record with the published financial measures it tagged, 32 filings, each linked to its SEC index.

Filing record ends 2023-03-31

The latest filing in this captured record is a 10-K filed 2023-03-31. No later filing is in the SEC companyfacts record captured on 2026-09-22. BRAIN SCIENTIFIC INC. may have stopped filing, merged, or changed its reporting entity; nothing on this page describes its current status. Values are as reported at the time.

Filings with published measures

Each page shows what one filing reported, as tagged in that filing, with the periods it covered. Later filings can restate a value; the company overview shows the latest-filed value per period.

FormFiledFiscal periodMeasuresFactsSEC accession
10-K2023-03-31fiscal FY 202245890001213900-23-025650
10-Q2022-11-14fiscal Q3 2022471360001213900-22-071879
10-Q2022-08-15fiscal Q2 2022451260001213900-22-048004
10-Q2022-05-13fiscal Q1 202244890001213900-22-026336
10-K2022-03-31fiscal FY 202144820001213900-22-016981
10-Q2021-11-15fiscal Q3 2021411200001213900-21-059156
10-Q2021-08-23fiscal Q2 2021411150001213900-21-044324
10-Q2021-05-24fiscal Q1 202136700001213900-21-028684
10-K2021-04-15fiscal FY 202039720001213900-21-021685
10-Q2020-11-19fiscal Q3 2020361000001213900-20-038212
10-Q/A2020-09-16fiscal Q1 202033660001213900-20-026881
10-Q2020-08-19fiscal Q2 202034950001213900-20-022828
10-Q2020-05-19fiscal Q1 202034680001213900-20-012856
10-K2020-03-31fiscal FY 201937690001213900-20-008234
10-Q2019-11-12fiscal Q3 201935910001213900-19-022890
10-Q2019-08-14fiscal Q2 201935980001185185-19-001133
10-Q2019-05-15fiscal Q1 201932680001185185-19-000750
10-K2019-04-01fiscal FY 201834700001185185-19-000489
10-Q2018-11-19fiscal Q3 201833890001185185-18-002062
10-Q2018-08-14fiscal Q2 201823660001185185-18-001459
10-Q2018-08-07fiscal Q1 201823480001185185-18-001362
10-K2018-07-13fiscal FY 201723480001185185-18-001247
10-Q2017-11-14fiscal Q3 201725700001185185-17-002382
10-Q2017-11-13fiscal Q2 201723660001185185-17-002315
10-Q2017-11-13fiscal Q1 201723480001185185-17-002312
10-K2017-11-13fiscal FY 201622450001185185-17-002310
10-Q2017-08-11fiscal Q2 201723660001185185-17-001709
10-Q2017-07-26fiscal Q1 201723480001185185-17-001607
10-K2017-03-07fiscal FY 201622450001185185-17-000534
10-Q2017-02-13fiscal Q3 201618500001185185-17-000311
10-Q2017-02-13fiscal Q2 201616440001185185-17-000309
10-Q2017-02-13fiscal Q1 201617360001185185-17-000307

Inspect the source

Entity
BRAIN SCIENTIFIC INC. / CIK 0001662382
Captured
SEC response SHA-256
65e17d0e702756b77c9b53df1319f658664a8db70c1434c3f7959f007a39e761

Current SEC company facts · Download the original response snapshot (gzip) · Download the selected JSON

Every published concept a filing tagged, with the periods it covered, as reported in that filing at capture time. Forms 10-K, 10-K/A, 10-Q, 10-Q/A, 20-F, 20-F/A, 40-F, 40-F/A. A filing page needs at least 8 published concepts. Later filings can restate these values; the company history pages show the latest-filed value per period.

Public company accounting reference, not market prices, returns, an investment recommendation, or ALPHAC performance. Validate a separately constructed return series with the validation API; accounting values are not returns.

Use this in research

A financial period ends before its results become public. Use the filing date as a minimum availability boundary, inspect amendments, and retain the original filing vintage when testing historical signals. This latest-filed selection can contain information unavailable at the time.

These pages do not supply prices, total-return histories, corporate-action adjustments or a tradable universe. Build those inputs separately before evaluating a strategy. A profitable backtest can still reflect selection bias or costs that were left out.

Research methodology · Execution and cost assumptions · Check backtest overfitting

Build with the open-source tools

Use these accounting records as inspectable inputs. When you have constructed a return series, the validation tools can help test its statistical evidence and preserve the result with its limitations.

Read the published dataset with Python
import json
from urllib.request import urlopen

with urlopen("https://canlicapital.com/company-data/0001662382.json") as response:
    record = json.load(response)
print(record["fetched_at"])
print(record["policy"])
for concept in record["concepts"]:
    print(concept["tag"], next(iter(concept["observations"])))