BNGAI™ enables Amazon to scale biodiversity assessment across development sites

BNGAI™, the AI-powered biodiversity intelligence platform, is enabling Amazon to assess and manage biodiversity across its development sites in England.

LONDON, GREATER LONDON, UNITED KINGDOM, May 21, 2026 /EINPresswire.com/ -- BNGAI™, the AI-powered biodiversity intelligence platform developed by AiDASH, is enabling Amazon to assess and manage biodiversity across its development sites in England.

The work is detailed in a new case study prepared by Amazon, which describes how the company used BNGAI™ to conduct biodiversity assessments across development sites in England. By combining satellite data, remote sensing, machine learning, and geospatial analysis, the platform enables rapid evaluation of biodiversity baselines and development impacts while supporting biodiversity enhancement under biodiversity net gain (BNG) regulations.

"Amazon is taking steps to measure, protect, and enhance biodiversity across our sites. BNGAI™ is helping us assess baselines quickly and consistently across our development sites in England, giving us the data we need to make informed decisions that prioritise biodiversity enhancement. We are encouraged by the early results and are exploring how to build on this approach as we continue to measure and minimise our potential biodiversity impact."
— Phil Birch, Global Biodiversity Lead, Amazon

The early success of the initiative demonstrates how AI-powered biodiversity intelligence can help organisations integrate environmental considerations into development planning at scale.

Incorporating biodiversity into development processes has become increasingly important. Traditional field-based ecological surveys, while thorough, can present challenges in terms of time, cost, logistics, and site accessibility - particularly when assessments must be conducted across multiple sites and markets.

These challenges are especially significant in England, where developments must achieve a minimum 10% biodiversity net gain, requiring precise and defensible data to demonstrate measurable improvements to habitat value.

BNGAI™ supported Amazon in assessing biodiversity baselines at development sites across England, evaluating the impact of development scenarios on local habitats, and calculating the biodiversity units required to demonstrate biodiversity net gain.

“As organisations expand their infrastructure footprints, integrating biodiversity insight into development planning is becoming increasingly important. BNGAI™ was designed to help organisations understand biodiversity quickly and at scale, using AI and satellite data to complement the work of ecologists and support better environmental decision-making.”
— Shashin Mishra, SVP BNGAI™, AiDASH

According to the case study, the AI-powered approach demonstrated strong technical performance, producing results comparable to traditional ecological surveys. The findings confirm that remote sensing and machine learning can effectively complement conventional ecological assessment methods.
The work also reinforced the importance of combining advanced analytics with ecological expertise. Professional ecologists continue to play a critical role in validating outputs, conducting site visits, and refining analytical models, creating a hybrid approach that integrates AI capabilities with on-the-ground ecological knowledge.

Early results have demonstrated strong potential for broader adoption across Amazon’s operations, with opportunities to expand the approach across additional business units and international countries.

Building on these learnings, BNGAI™ is working alongside AWS to further optimise its AI workflows and data processing pipelines. The collaboration focuses on improving how environmental data is collected, analysed, and continuously refined, creating the foundations for efficient biodiversity assessments at scale.

About BNGAI™
BNGAI™ is an AI-powered nature intelligence platform developed by AiDASH. Built on AWS infrastructure, the platform combines remote sensing, satellite imagery, machine learning, and geospatial analytics to support biodiversity assessment and development planning at scale.

Anastasiia Filatova
AiDASH
+44 7447 082313
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