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Company profile

We Care 4 Air Limited

Air Quality Monitoring | WeCare4Air

Air Quality Monitoring equipment, spare parts, and services. With over 25 years of experience in the air quality monitoring industry.

CRN
09235089
Founded
2014
Age
11

Overview

Legal name
WE CARE 4 AIR LIMITED
Region
East of England
Registered address
UNITS 4,5 & 6 PARKLANDS BUSINESS CENTRE STORTFORD ROAD
LEADEN RODING
DUNMOW
ENGLAND
CM6 1GF
Insolvency history
No

Latest accounts

Financial period: 1 Oct 2023 to 30 Sep 2024

FULLACCOUNTS
Turnover
Unknown
Profit / Loss
Unknown
Employees
12

Company events

Reference milestones and recent Companies House filing stream events.

7 events
29 Jun
2027

Accounts due

Accounts Due

Next accounts due date

17 Oct
2026

Confirmation statement due

Confirmation Due

Next confirmation statement due date

03 Oct
2025

Confirmation statement filed

Confirmation

Last confirmation statement made up date

30 Sep
2025

Accounts filed

Accounts

Last accounts made up date

13 Oct
2024

Confirmation Statement With No Updates

Confirmation-statement

CS01 | Transaction MzQzOTI1MDEyNWFkaXF6a2N4

Published 13 Oct 2024 09:47

13 Oct
2024

Change To A Person With Significant Control

Persons-with-significant-control

PSC04 | Transaction MzQzOTI1MDExOWFkaXF6a2N4

Published 13 Oct 2024 09:46

25 Sep
2014

Incorporated

Inception

Company registered at Companies House

Public funding

2 awards
First funded
2023
Funded years
2023, 2024
Age at first award
8 years

Projects

2024 Collaborative R&D Lead participant

Sustainable Optoelectronic replacements to maintain reference grade air quality data monitoring

1 Jun 2024 to 31 Aug 2024

Awarded
£25,240
Total cost £25,240

We Care 4 Air are one of just 6 manufacturers of reference grade, MCerts and USEPA approved gaseous air quality analysers, and the sole manufacturer based in the UK. We are aiming to achieve Net Zero by 2030\. Our analyser range Aeris is highly accurate and has an excellent reputation worldwide. It is our intention for Aeris analysers to become the most s...

2023 Collaborative R&D Lead participant

The development of Machine Learning methods to correct data responses from low-cost sensors to improve agricultural productivity and air quality data accuracy.

1 Sep 2023 to 29 Feb 2024

Awarded
£35,622
Total cost £35,622

This project is to develop machine learning based methods to normalise the responses of electrochemical and solid state gas sensors used in air quality monitoring for transport, health and agriculture. The proposed models use a wide range of environmental parameters and reference grade trace gas analysers as well as the responses of the electrochemical an...

Product types

Collaborative R&D