FAQs

Yes Ada can be used as a supporting tool for procurement and investment, comparing companies in the same sector. This is most effective for larger and global companies where match rates are highest. Contact us for support on this analysis which our analysts will provide to your requirements.

As the Ada dataset has expanded, we have focused our research and data collection on multi year data for companies to provide an insight into emissions trajectories and how these may impact procurement or investment decisions that relate to Net Zero pathways. This additional analysis will be available to our subscribers in Q1 next year. In Q4 2026 this will be available to clients requiring offline analysis.

The majority of reporting companies outside large quoted companies have only been reporting for 4-5 years. This means that multi year analysis is not as exhaustive as our corporate reporting data.

Given that there are less than 25,000 companies worldwide who are publicly reporting their emissions in various geographies, we undertook 18 months of research into predictive reporting using the key financial indicators of companies reporting in their annual accounts to see if and where a link existed between emissions and financial performance. From 20 possible indicators, we identified four that had the strongest correlation to emissions, using high quality emissions and financial data of reported companies.

The results were very strong with over 90% accuracy being achieved using financial indicators, when running predictive analysis and then comparing with actual corporate data.

This function is used where high confidence exists in the outputs, using sector and country analysis, to supplement our weighted sector average data for non reporting companies. As our datasets grow so does our ability to deploy more predictive results based on financial indicators that we have validated and used in our LLM.

In most cases we will use a weighted sector average that is as granular as reported data by country and sector or sub sector will allow. There is no substitute for reported data, but our analysis shows that we can achieve robust estimates for non reporting companies.

Although our reporting provides multiple points of analysis via our online reporting and API, we do use our extensive data sets to provide offline bespoke analysis and supporting advice where required. Please contact our team to arrange an introductory call so we can assess your requirements and advise on how we can support you.

Your reports will remain accessible via the home screen that is accessible via your login. You can download a pdf summary for your records and continue to access prior reporting whilst you have a live subscription. Note for free trials the reports will not be accessible after the trial period without a subscription.

To register for a free trial or a paid subscription, simply follow the sign up instructions and select an appropriate subscription for your company requirements. You can process data via the website or for larger users an API is available for bulk data.

Multi year trajectories, like financial data can provide a guide to what may lie ahead in terms of an individual company’s performance. However past performance is not a guarantee of future performance in either investment or Net Zero pathways.

Using multi year reported performance is generally helpful in reviewing vendors and investments against their peers and their sector. There is no other way to be able to understand actual performance. Stated progress to Net Zero targets contains so many variables and reporting methods, that this can prove to be very unreliable. Our analysis of targets and progress in publicly available company reporting, have highlighted how complex target trajectories and progress to them, are to validate.

Ada is the result of over a decade of expertise from Carbon Responsible, a company that’s specialised in solving complex Scope 3 reporting challenges for its clients. After years of working with data, we realised that existing tools were not delivering the level of accuracy or transparency that businesses need.

Ada was created as a solution to fill that gap and provide companies with better insights to track and manage their carbon emissions.

Using the defined format, simply upload or drag and drop an excel file with the companies that you wish to report on or analyse, on the subscribers home screen. Your results will be processed in less than a few minutes.

Ada uses company reporting for its Scope 1 & 2 emissions to calculate the relevant Scope 3 impact that each company delivers for a reporting company, based upon its spend with that company. Scope 2 includes both location and market based emissions as available in company reporting.

Getting started with Ada is quick and simple. The platform is designed to be intuitive and accessible -no technical expertise required. Just input your basic company metrics into a straightforward template, and Ada takes care of the rest. Your data is automatically processed to generate a Scope 3 report, delivered via a user-friendly dashboard with clear, instant insights. Once your report is ready, you’ll be supported by a dedicated Account Manager and our Carbon Expert team, who will guide you through the results and help you take meaningful next steps.

If you’d like to get started with Ada, take a free trial or book a call with one of our experts. We’ll help you determine which level of subscription or service is the best fit based on your data needs. Book a call here.

Core data is collected by a data analyst with carbon accounting experience and then undergoes a validation process by a separate analyst to verify the collected data. All data, including the date of collection, its source and all relevant metrics are stored for internal audit purposes, to ensure that regular data reviews can detect anomalies. Only validated data is entered into the live database for use in the platform. We aim for and expect to achieve an accuracy rate of 97% minimum in our primary data used for our datasets.

Ada relies upon acquisition of data from public reporting. This data is acquired and verified by data analysts to ensure that the input data for the platform is of the highest quality. It has proved to be the only way to ensure data anomalies in reporting can be identified and data quality scored accurately.

We undertook extensive trials in 2025 using AI to collect, analyse and validate reported emissions data from multiple sources. The results were analysed by data analysts with carbon accounting expertise and despite predictions of 90% accuracy, were found to have an accuracy rate of less than 30%.

The minimum subscription is for up to 50 companies for analysis and reporting. Pricing begins at 50 companies for GBP750 and unit pricing reduces with volumes processed. Your subscription will provide you with the relevant number of credits for processing and can be increased as needed either within the same pricing tier or by upgrading your subscription tier.

Many clients who have used Ada often start with the highest spend areas in their supplier base, usually isolating companies who comprise 50% of total spend to begin with. Long tail supply chains can contain many smaller companies for whom reported data and related analysis is not reliable. This is caused by small company emissions data being relatively rare.

The input data is captured and updated four times a year to ensure that the reported company data used in its reporting and analysis is as up to date as possible. This ensures the highest possible accuracy and addresses the aged data problem that is common in the majority of reporting tools available, including large global data providers.

Most data is less than two years old, based upon the date it was reported by a company. Sometimes the latest data available can be several years old where the company has not updated its reporting. All data is aged when reported, as is financial accounting data, albeit climate reporting can lag annual accounts in many instances. In 2026 many companies will be reporting 2025 or 2024 emissions. Our quarterly review and refresh of data ensures you get the latest available numbers. This also feeds through into our LLM and sector analysis, including predictive variances.

Over the years, it became clear that most existing tools lacked the accuracy and transparency needed to make meaningful progress. Businesses were missing opportunities and facing unnecessary risks due to poor-quality emissions data.

Ada was developed to change that. It provides a more accurate, transparent, and actionable way to track and manage emissions—especially Scope 3—giving companies the insight and confidence to drive real sustainability impact.

The appropriateness of use of spend data lies in the accuracy of the data used to match corporate emissions, to either investment or supplier spend for specific companies. High level spend data vs sectors is likely to be very low quality and thus is less effective, leading to many carbon accountants questioning its value. However, the alternative to spend is to use materials based reporting using EEIO models, although this is reliant on underlying data that is incomplete and does not disaggregate materials provided by low vs high carbon manufacturers or processors. Additionally, materials data from real world manufacture or processing sources is very poor, as highlighted in detailed life cycle analysis work undertaken by Ada team members in multiple sectors from farming to mobile telephony, that reveals how poor activity data undermines material or product use based reporting.

The data quality score for each company is aligned with the principles of data scoring used by PCAF ( the Principles for Carbon Accounting in Finance), they enable you to understand the relative quality of company data that has ben reported. The highest scores are companies where they have undertaken reasonable or limited assurance of their reporting and the lowest scores are attributed to companies who use broad estimates of input and output factors to report emissions.

For procurement, governance and engagement, the presence of lower data scores amongst companies where you have a high spend or significant investment, provides an opportunity to work with these companies to ensure better reporting.

Your reports will contain the following information:

Error reports indicating where data cannot be processed, often because a key data point like, your spend levels with a company, currency of spend or the company name is not correct.

Summary of total emissions for all companies, subdivided by sector and location.

Your top emitters by company.

Data quality scores as an average and by location or sector.

Predictive variance summaries and reports that allow you to see where your key sector impacts score for data quality.

Match rate showing clearly how many companies have a direct emissions data match and those that have used sector and country averages in the results. This output is rare as most providers imply high match rates but are usually majority based on sector averages.

Firstly the use of EEIO data has been analysed by the Ada team using company data reported by providers of materials and how the use of EEIO varies from actual corporate emissions. Trials showed a variance of up to 2000% when running a comparative analysis of top quality assured corporate reporting and EEIO.

This type of analysis does not allow for meaningful engagement with suppliers and investments to improve performance and nor does it contribute to real world emissions reductions or procurement options. Example – if you used steel in your manufacturing you could use a materials emissions factor for steel. This would be an average of all available data and not distinguish between production from highest vs lowest efficiency production of steel. The only way that your company could reduce its emissions would not be by switching supplier but by reducing consumption, which may be commercially undesirable. Purists will say that usage reduction will reduce emissions, which it will were the market demand for products and also the recycling of these materials not factored into the equation.

The match rate is simply the number of companies in your report who have directly reported their emissions and for which your report provides an exact match based upon spend and reported currency. Most well known brands providing data do not make this clear to their subscribers, implying high match rates, whereas the real match rate may be a maximum of 40%.

The match rate enables better engagement with supply chains to ensure that suppliers or investments deliver public reporting. Surprisingly many large companies do report but choose not to make their reporting available for customers and investors.

Using the data we hold for every company in a sector we are able to determine the highest and lowest extent of a sector emissions range by company. Your specific results are shown on this scale to allow you to understand how your reported data sits within this range and the likely level of accuracy of your sector results. No Scope 3 data is 100% accurate and so understanding variance is important. Where we hold significant country or sub sector data that will support granular analysis of predictive variance this is provided.

Ada has been developed by carbon accounting and data experts, some with two decades of experience in carbon reporting and emissions data. It is further based upon work undertaken for investors and large corporates over many years to deliver audit quality outputs and ISO 14064-3 limited assurance of reported corporate data. This experience is both the genesis of Ada, but also enables a depth of understanding of models, methodology and data quality used in corporate reporting. Most of the work was undertaken by Carbon Responsible, a leading independent carbon accounting firm founded in 2012, which has consistently worked to maximise accuracy for global clients with significant reporting challenges.

The data used by our Ada platform is of the highest available quality based upon reported emissions. Company reporting can contain huge variances in quality of reported emissions, in clarity, formatting and actual metrics used. This is the reason why AI has proved to be less valuable in the data collection and validation process, leading to the garbage in – garbage out risk that is inherent in poorly validated data. Its value lies more in LLMs and rapid analysis of the validated data. Many companies offering AI reporting are using exactly the same process that we trialled ourselves. This leaves an accuracy rate for all input data that will be 60% lower than Ada.

Ada stands out due to its accuracy, the quality of the data it uses, and its transparency. Ada can produce more accurate results than competitors, mainly due to the up-to-date data it uses, combined with its intelligent use of machine learning. Ada’s unique level of transparency also provides users with an unparalleled level of confidence in the calculations and results.

Ada’s ability to deliver highly accurate Scope 3 insights.

Unlike tools that rely on flat averages, Ada blends inputs to identify emissions hotspots and reveal whether your reporting is on track. It starts as a discovery tool and quickly becomes strategic, helping you focus on high-impact reduction areas.

Whether you’re a CEO tracking targets or a private equity firm managing multiple portfolios, Ada delivers instant clarity – no more waiting months for manual reports.

The data supplied by Ada reports should be applied to Scope 3 Category 1 for supplier emissions, being Purchased Goods and Services. Investment reporting is applied to Scope 3 Category 15, being Investment emissions.

There are several reasons why Scope 3 emissions from reporting companies. Firstly the Scope 3 emissions of a reporting company, when included in a Scope 3 calculation will in effect be double counted as an emissions value. This is an established and core principle of corporate emissions accounting. Secondly using Scope 3 analysis to help inform wider corporate impact for thousands of companies, would aside from the double counting risk, use highly variable data in terms of completeness across all 15 Scope 3 categories, and varying levels of estimate strength. It would also lead to more extensive reporting by a company, penalising companies with comprehensive reporting, over those that do not report much if any Scope 3 emissions.