NEMS Panorama
nems.ecoNEMS Panorama supports online corporate sustainability reporting by consolidating ESG data management, analysis, and disclosure for independent oil and gas operators. Delivered via a web browser, it gives distributed teams global, simultaneous access to a single platform for data entry, reporting, and oversight. The solution is built by oil and gas specialists to reflect sector-specific ESG, GRI, and IOGP reporting requirements, and is designed to provide consistent reporting across assets and disciplines, along with a transparent view of reporting workflows and status. It facilitates collaboration by enabling structured information sharing with internal and external stakeholders while maintaining information security.
The platform includes an analytical toolbox for handling large sustainability datasets, allowing rapid aggregation, graphical drill-down to emission sources and root causes, and benchmarking of assets across multiple dimensions through tables and visualizations. NEMS Panorama is compliant with ISO 14001/14031, supporting local data capture with centralized reporting to preserve traceability and consistency, and enabling users to investigate anomalies and assign follow-up actions via ticketing. Integration capabilities include automatic and ad-hoc export of data to other systems and Excel through an open API, as well as automatic data transfer from NEMS Accounter into NEMS Panorama.
LLM mention score The LLM mention score is the total number of mentions of this brand in different LLM chatbots, normalized to the scale from 0 to 100. You can get actual, non-normalized numbers via the LLM Mention API from DataForSEO.
Normalized 0–100 · last 8 weeks
Get LLM mention data of any company via DataForSEO API
Get access to the structured data on keyword, brand, and website mentions in LLMs, including metrics like AI search volume, impressions, and mentions count.
How to get LLM mention data →// Fetch NEMS Panorama mention score POST /v3/content_analysis/summary { "keyword": "NEMS Panorama", "type": "llm_mentions", "date_from": "2025-01-01" }