Redwheel is a specialist, independent investment organisation established in 2000, managing $23.4 billion (as at May 2026) across eight autonomous investment teams spanning equity and convertible bond strategies. The firm runs several sustainable funds built on a rigorous, products and services-based approach to sustainable investment classification. Redwheel partnered with Clarity AI to strengthen the data foundations of this process with access to high-coverage SDG revenue alignment data, reducing manual assessment burden, and building a collaborative data partnership.
The Opportunity
The Solution
The Results
Sustainable Investment at Redwheel
Founded in 2000, Redwheel is an independent, active asset manager with offices across London, Miami, Singapore, and Copenhagen, managing $23.4 billion (as at May 2026) on behalf of clients worldwide. Sustainability is woven into several core strategies, including funds operating under SFDR, where defining and evidencing sustainable investments requires both a clear methodology and reliable underlying data. Redwheel partnered with Clarity AI to strengthen that data foundation, gaining access to high-coverage SDG revenue alignment data that supports its sustainable investment assessment process at scale.
Will Wilson, Senior Sustainability Specialist, sits within Redwheel’s Sustainability Strategy, Governance and Policy team, a central function responsible for ensuring investment teams operate in line with their sustainability commitments, chairing the internal Sustainable Investments Working Group, and keeping pace with an evolving regulatory landscape. Here, he explains why Clarity AI is best suited to cover Redwheel’s needs.
A Rigorous but Resource-Intensive Process
Redwheel’s sustainable investment classification methodology is precise by design. A company must demonstrate that at least 35% of its revenue is positively aligned to the SDGs, with no more than 10% negatively aligned (covering areas such as coal production, oil and gas, and tobacco). Portfolio managers submit each prospective sustainable investment to an independent internal Sustainable Investments Working Group for review, providing evidence of both positive SDG alignment and compliance with good governance and do-no-significant-harm criteria.
The model works well, but its effectiveness depends heavily on the quality and breadth of the underlying data. Where a trusted third-party provider’s assessment aligns with Redwheel’s own view, the process is efficient. Where coverage gaps exist or methodologies diverge, portfolio managers must conduct manual assessments, resulting in a significantly more time-intensive process.
Precision Data, Seamlessly Integrated
CHALLENGE 1
Finding a Methodological Match
When evaluating new providers, Redwheel ran a sample set of holdings through each candidate’s analysis, benchmarking results against both its previous provider and its own bottom-up assessments. The strength of agreement with Clarity AI stood out.
“We needed to make sure that it wasn’t going to cause too many changes versus the previous provider, but also that philosophically and methodologically it was very much aligned with how we see things”
This alignment matters practically as well as philosophically. Redwheel’s sustainable funds carry minimum commitments to the proportion of holdings classified as sustainable investments. A sudden data-driven shift in classifications could trigger unintended investment decisions. Clarity AI’s approach gave Redwheel the confidence that transitions would be smooth and that agreement between the firm’s own assessments and provider data would grow over time.
One feature particularly valued by Redwheel was Clarity AI’s geographic granularity in SDGs revenue alignment; the recognition that the same revenue-generating activity may have different SDG relevance depending on the region in which it occurs. For a firm with a number of emerging and frontier markets strategies, this nuance is central to accurate classification.
CHALLENGE 2
Coverage Where It Matters Most
In relation to emerging and frontier markets exposure, this is precisely where data coverage tends to be thinnest across the industry. With access to SDG revenue alignment data across approximately 96,000 companies, Clarity AI’s breadth of coverage has meaningfully reduced the instances where Redwheel’s portfolio managers must resort to manual assessments.
“The coverage is excellent. We’re starting to see better data coverage within emerging and frontier markets, and the overall alignment of philosophy and methodology means the instances where we agree with the provider within that sustainable investment assessment workflow continue to increase”
This improvement in coverage translates directly into efficiency gains for Redwheel’s investment teams and greater consistency across the sustainable investment review process.
CHALLENGE 3
Integration and Data Freshness
Redwheel accesses Clarity AI data both through its web app and via APIs, feeding into a centralised data aggregation platform that combines sustainability data with live investment data to dynamically reweight analysis based on position sizes and portfolio changes. Integration into this infrastructure was a core requirement during the selection process and one that Clarity AI met without friction.
Equally important is the frequency with which the underlying data is refreshed. Clarity AI’s frequent data updates are a meaningful operational advantage, ensuring that when a refinement in the data is needed, the updated figures flow through quickly.
“When we’ve had a very collaborative conversation, and it has led to Clarity AI thinking, ‘yes, that’s a valid point’, that then feeds through pretty quickly — whereas other providers only update quarterly or monthly”
A Collaborative Partnership That Improves Over Time
One of the less anticipated benefits of working with Clarity AI has been the quality of the collaborative relationship. Redwheel brings deep knowledge of many of its investee companies through direct engagement, and Clarity AI has been receptive to discussing cases where the two parties hold different views, whether around critical minerals, microfinance loans in emerging markets, or other nuanced SDG alignment questions.
In several instances, these conversations have led Clarity AI to update its assessments. In others, the robustness of Clarity AI’s methodology has confirmed the existing figures. Either way, the process strengthens the overall quality of the data and deepens the working relationship.
“It’s very collaborative. If we have more data than the data provider, we are very prepared to share that with Clarity AI, and they have been very receptive. It’s only a win-win”
Summary of Results
Reduced manual assessment burden
Methodological confidence
Faster data refresh cycles
Scalable integration
What’s Next for Redwheel
Looking ahead, Redwheel is interested in exploring alternative metrics beyond revenue alignment — such as R&D spend or generation capacity — to handle cases where revenue is not the most representative measure of a company’s impact, particularly for pre-revenue companies or those in build-out phases. This is a natural next frontier for the partnership.
“We’re constantly evolving our approach and trying to ensure it’s market-leading. Things are in a good place, but we’re always scanning for ways to increase the robustness and strength of how we assess and manage sustainability across the board”