Exegy and STRANDS have announced a partnership to bring real-time prediction-market, digital-asset and smart-contract data from centralised and decentralised venues into Exegy’s Axiom consolidated feed service, with initial content scheduled for delivery in May 2026.
The announcement extends Exegy’s market-data offering into a broader set of emerging asset classes and data types, including prediction markets, spot crypto, derivatives, lending rates, funding rates and smart-contract data. While that expansion is notable in itself, the partnership is also framed around a more practical objective: making these datasets available through infrastructure and delivery models that institutional firms already use for traditional market data.A question of market structure
Part of the backdrop to the partnership is that prediction markets remain an evolving and only loosely defined category. That creates both commercial interest and technical complexity, particularly for firms looking to assess whether such data can fit into established research, trading and risk workflows.
In conversation with Market & Alt Data Insight, David Taylor, CEO of Exegy, says many firms are still trying to define the category in operational terms. “The question many clients are asking is: what are prediction markets? The category is still very open. The industry is going to have to segment the market, decide what it means by a prediction market, and start treating different types of these instruments in a more structured way.”
That suggests the opportunity is not simply about adding another niche feed. It is also about whether newer forms of market activity can be organised, classified and distributed in ways that make them more accessible to institutional users.
Bringing new data into familiar environments
Taylor describes Exegy’s role as helping firms access these newer datasets through delivery infrastructure they already know. “Part of our role in the institutional adoption of these markets is to give firms access to the data on a platform they already have onboarded and already trust, and to give them the same level of control and transparency over that data that they have for any traditional market. That can help mature those markets by accelerating clients’ analysis and adoption.”That emphasis on trusted distribution and operational consistency is central to the partnership. Rather than asking firms to build separate infrastructure around digital assets and prediction markets, the proposition is that these data types can be evaluated through existing market-data channels and governance models.
Taylor also indicates that institutional interest is not centred solely on speculative use cases. “The institutional players we have spoken to are interested in a more narrowly defined use of prediction-market structures and technology: whether they can help fill gaps in the ability to distribute and manage risk that are not addressed by traditional markets today.”
That framing places prediction markets in a broader market-structure context, rather than treating them simply as an extension of retail trading activity or crypto speculation.
The normalisation challenge
From STRANDS’ perspective, a key issue is not only access to the data, but how that data is represented and standardised. Tim Gorham, CEO of STRANDS, says the partnership is addressing a technical problem that remains unresolved across much of the market.
“From a technical perspective, we see prediction markets as instruments. The challenge is how to deal with this new data from a symbology perspective, because currently none of it is normalised.”
That challenge is likely to be familiar to firms that have tried to work with emerging or unconventional datasets. Instruments may be created dynamically, venue conventions may vary, and the lack of common symbology can make it difficult to map data consistently across systems. In that context, the value of the partnership lies not only in sourcing the data, but also in how it is structured for downstream use.
Fitting into existing workflows
Gorham argues that the partnership is intended to minimise that friction for clients already connected to Exegy’s infrastructure. “Because of the expertise and technology in this partnership, Exegy’s clients will be able to ingest this data without rewrites, in the same way they consume equities, ETFs, futures, options and other traditional market data. It will come through the same pipes and in a format they are already comfortable with.”
For firms interested in evaluating these markets, that may be an important part of the offering. The ability to consume newer datasets through existing delivery channels can lower the operational threshold for experimentation, analysis and possible production use.
This does not, in itself, resolve wider questions around regulation, venue quality, governance or long-term institutional demand. But it does address a more immediate barrier: the difficulty of bringing unfamiliar data into established environments without creating a separate technical stack.
Coverage beyond top-level venue data
The scope of STRANDS’ contribution is also broader than standard spot crypto coverage. Gorham says the company’s data extends beyond centralised exchanges into smart-contract-level information where required.
We do not just cover the largest centralised and decentralised exchanges; where needed, we also go directly to the smart-contract level. That is part of what makes the offering compelling. We go well beyond spot and perpetual future data on centralised and decentralised venues. We will deliver a comprehensive view of smart-contract data including lending and perpetual funding rates.”
That wider coverage reflects the way these markets operate. For institutional users, top-level price data may be only part of the picture, particularly in decentralised environments where activity, liquidity and execution conditions may depend on smart-contract structures as much as on venue-level trading data.
A broader shift in data distribution
Taken together, the announcement points to a broader development in the market-data landscape. As newer asset classes and market structures attract institutional attention, the focus is shifting from simple access to questions of packaging, normalisation and integration.
In that sense, the Exegy-STRANDS partnership is as much about delivery and usability as it is about content breadth. Prediction markets, digital assets and smart-contract data remain relatively new territory for many institutions. But if such datasets are to be assessed seriously within mainstream trading and research environments, they will need to be presented in forms that support existing controls, workflows and data-management practices.
That appears to be the immediate objective of this partnership: not to resolve every question around these markets, but to make the underlying data easier for institutional firms to access, analyse and compare within familiar operational settings.
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