2023 Form 5500 filing — Southeast Modular Manufacturing Welfare Benefits Plan
Plain-English filing summary
According to public Form 5500 filings published through the U.S. Department of Labor (DOL) Employee Benefits Security Administration (EBSA) via the EFAST2 system, this is the 2023 Form 5500 filing (EFAST2 acknowledgement 20240521161006NAL0003021489001) for Southeast Modular Manufacturing Welfare Benefits Plan, reported by Amtex-Nms, Inc. Dba Southeast Modular Manufacturing under EIN 58-1895025 and plan number 511. It reports 174 participants. Attached schedule details are not reported in the loaded dataset.
Filing snapshot
- EFAST2 acknowledgement
- 20240521161006NAL0003021489001
- Plan sponsor
- Amtex-Nms, Inc. Dba Southeast Modular Manufacturing
- EIN
- 58-1895025
- Plan number
- 511
- Location
- Leesburg, FL
- Received date
- not reported in the loaded dataset
How to read this filing
- This is a single annual Form 5500 filing, identified by its EFAST2 acknowledgement id.
- Schedule chips (Sch H / I / C) show which schedules this filing includes.
- Net assets = total assets minus total liabilities (Schedule H/I).
- Fields a filing did not report are labeled not reported in the loaded dataset — never estimated.
- For the plan's full history, open the plan profile.
Reported financial snapshot
Reported figures as filed, in whole dollars. Only fields the filing reports are shown.
This 2023 filing is loaded, but detailed Schedule H/I financial figures are not present for it in the current loaded dataset. Participant counts and filing identity above are reported; asset and contribution detail comes from the financial schedules where filed.
Frequently asked questions
- What does EFAST2 acknowledgement 20240521161006NAL0003021489001 cover?
- It is the 2023 Form 5500 filing for Southeast Modular Manufacturing Welfare Benefits Plan, reported by Amtex-Nms, Inc. Dba Southeast Modular Manufacturing (EIN 58-1895025).
- Which Form 5500 schedules are attached to this 2023 filing?
- Attached schedule details are not reported in the loaded dataset.