Paradigm Builds Its Own Prediction Market Trading Terminal, Also Considering Market Making and Index Products

marsbit2026-04-02 tarihinde yayınlandı2026-04-02 tarihinde güncellendi

Özet

Paradigm, a major crypto investment firm, is developing a dedicated trading terminal for prediction markets, targeting professional traders and market makers, according to anonymous sources. Led by partner Arjun Balaji since late 2025, the initiative aligns with growing institutional interest in prediction markets, where users speculate on events like elections or asset prices. The company is reportedly considering launching an internal market-making desk and exploring the creation of a prediction market index—similar to traditional indices like the S&P 500—by aggregating multiple prediction markets into a single tradable product. Paradigm has already begun compiling prediction market data into a public dashboard. Notably, Paradigm is a key investor in Kalshi, a leading prediction market platform it helped value at $22 billion, and insists the terminal does not compete with Kalshi’s core business. This move is part of Paradigm’s broader expansion beyond crypto into AI and robotics, evidenced by its ongoing efforts to raise a new $1.5 billion fund. The firm has a history of launching in-house projects, including the crypto software company Ithaca and Tempo, a stablecoin-focused blockchain developed with Stripe.

Author: Fortune (Anonymous Insider)

Compiled by: Deep Tide TechFlow

Deep Tide Guide: Prediction markets are evolving from niche tools to a mainstream financial sector. Paradigm is not content with just being an investor and is starting to build infrastructure itself. Behind this move is a top-tier crypto VC redefining its boundaries by incubating projects—from Ithaca to Tempo to the prediction market terminal, Paradigm is increasingly resembling a product company.

Full Text Below:

One of the most influential investment firms in the crypto space is seeking a larger share of the rapidly growing prediction market pie. According to insiders, venture capital firm Paradigm is developing a prediction market trading terminal for professional traders and market makers. The sources requested anonymity to discuss these non-public business plans. It is reported that Paradigm partner Arjun Balaji has been leading this project since late 2025.

Balaji did not respond to requests for comment, and a Paradigm spokesperson also declined to comment.

The advancement of this trading terminal project coincides with mainstream financial institutions racing to enter the prediction market space. Prediction markets allow traders to speculate on outcomes such as sports events, election trends, and even Bitcoin prices, and have seen growing popularity in recent years.

According to two insiders, Paradigm is also considering whether to establish an internal market-making desk for prediction markets alongside the development of the trading terminal.

Additionally, a third source familiar with Paradigm's situation stated that the venture capital firm is collaborating with researchers to explore the feasibility of creating prediction market indices. The core idea is to bundle multiple prediction markets into a tradable product, similar to how the S&P 500 index consolidates 500 company stocks into one index. Currently, Paradigm has begun aggregating prediction market data into a public dashboard.

Kalshi and Polymarket

Paradigm is a major investor in Kalshi, one of the top two prediction market platforms. In 2025, the venture capital firm participated in three rounds of funding for Kalshi and led the December round that pushed Kalshi's valuation to $11 billion. Currently, Kalshi has completed a new round of funding of at least $1 billion, raising its valuation to $22 billion.

Paradigm co-founder and managing partner Matt Huang serves on Kalshi's board of directors. According to one insider, Paradigm's development of a prediction market trading terminal does not compete with Kalshi's platform business.

Competitor Polymarket is also expanding rapidly. According to The Wall Street Journal, the platform is in talks for a new round of funding with a valuation of approximately $20 billion. Meanwhile, a new venture capital firm focused on prediction markets has been established, backed by the CEOs of both major prediction market platforms.

Paradigm's bet on prediction markets also comes as the company continues to expand its boundaries—from its traditional focus on digital assets to broader technology sectors. According to The Wall Street Journal, Paradigm is raising a new fund of up to $1.5 billion, with investment directions no longer limited to crypto but also including AI and robotics.

Paradigm has a tradition of incubating its own projects. In 2024, Paradigm CTO Georgios Konstantopoulos founded Ithaca, a crypto software development company, and serves as its CEO. Recently, Paradigm also collaborated with fintech giant Stripe to jointly develop Tempo—a high-speed blockchain designed for stablecoins. Managing partner Huang is leading this project. According to one insider, Tempo had about 70 employees by early March.

İlgili Sorular

QWhat is Paradigm reportedly developing according to the article?

AParadigm is reportedly developing a prediction market trading terminal for professional traders and market makers.

QWho is leading the prediction market trading terminal project at Paradigm?

AParadigm partner Arjun Balaji has been leading this project since late 2025.

QBesides the trading terminal, what other prediction market-related products is Paradigm considering?

AParadigm is considering establishing an internal market making desk for prediction markets and is exploring the feasibility of creating a prediction market index.

QWhich major prediction market platform is Paradigm a significant investor in?

AParadigm is a significant investor in Kalshi, having participated in multiple funding rounds, including one that valued the company at $11 billion.

QHow is Paradigm expanding its investment focus beyond its traditional areas?

AParadigm is expanding its investment focus to include not just digital assets but also AI and robotics, as it raises a new fund of up to $1.5 billion.

İlgili Okumalar

Gensyn AI: Don't Let AI Repeat the Mistakes of the Internet

In recent months, the rapid growth of the AI industry has attracted significant talent from the crypto sector. A persistent question among researchers intersecting both fields is whether blockchain can become a foundational part of AI infrastructure. While many previous AI and Crypto projects focused on application layers (like AI Agents, on-chain reasoning, data markets, and compute rentals), few achieved viable commercial models. Gensyn differentiates itself by targeting the most critical and expensive layer of AI: model training. Gensyn aims to organize globally distributed GPU resources into an open AI training network. Developers can submit training tasks, nodes provide computational power, and the network verifies results while distributing incentives. The core issue addressed is not decentralization for its own sake, but the increasing centralization of compute power among tech giants. In the era of large models, access to GPUs (like the H100) has become a decisive bottleneck, dictating the pace of AI development. Major AI companies are heavily dependent on large cloud providers for compute resources. Gensyn's approach is significant for several reasons: 1) It operates at the core infrastructure layer (model training), the most resource-intensive and technically demanding part of the AI value chain. 2) It proposes a more open, collaborative model for compute, potentially increasing resource utilization by dynamically pooling idle GPUs, similar to early cloud computing logic. 3) Its technical moat lies in solving complex challenges like verifying training results, ensuring node honesty, and maintaining reliability in a distributed environment—making it more of a deep-tech infrastructure company. 4) It targets a validated, high-growth market with genuine demand, rather than pursuing blockchain integration without purpose. Ultimately, the boundaries between Crypto and AI are blurring. AI requires global resource coordination, incentive mechanisms, and collaborative systems—areas where crypto-native solutions excel. Gensyn represents a step toward making advanced training capabilities more accessible and collaborative, moving beyond a niche controlled by a few giants. If successful, it could evolve into a fundamental piece of AI infrastructure, where the most enduring value in the AI era is often created.

marsbit12 saat önce

Gensyn AI: Don't Let AI Repeat the Mistakes of the Internet

marsbit12 saat önce

Why is China's AI Developing So Fast? The Answer Lies Inside the Labs

A US researcher's visit to China's top AI labs reveals distinct cultural and organizational factors driving China's rapid AI development. While talent, data, and compute are similar to the West, Chinese labs excel through a pragmatic, execution-focused culture: less emphasis on individual stardom and conceptual debate, and more on teamwork, engineering optimization, and mastering the full tech stack. A key advantage is the integration of young students and researchers who approach model-building with fresh perspectives and low ego, prioritizing collective progress over personal credit. This contrasts with the US culture of self-promotion and "star scientist" narratives. Chinese labs also exhibit a strong "build, don't buy" mentality, preferring to develop core capabilities—like data pipelines and environments—in-house rather than relying on external services. The ecosystem feels more collaborative than tribal, with mutual respect among labs. While government support exists, its scale is unclear, and technical decisions appear driven by labs, not state mandates. Chinese companies across sectors, from platforms to consumer tech, are building their own foundational models to control their tech destiny, reflecting a broader cultural drive for technological sovereignty. Demand for AI is emerging, with spending patterns potentially mirroring cloud infrastructure more than traditional SaaS. Despite challenges like a less mature data industry and GPU shortages, Chinese labs are propelled by vast talent, rapid iteration, and deep integration with the open-source community. The competition is evolving beyond a pure model race into a contest of organizational execution, developer ecosystems, and industrial pragmatism.

marsbit14 saat önce

Why is China's AI Developing So Fast? The Answer Lies Inside the Labs

marsbit14 saat önce

3 Years, 5 Times: The Rebirth of a Century-Old Glass Factory

Corning, a 175-year-old glass company, is experiencing a dramatic revival as a key player in AI infrastructure, driven by surging demand for high-performance optical fiber in data centers. AI data centers require vastly more fiber than traditional ones—5 to 10 times as much per rack—to handle high-speed data transmission between GPUs. This structural demand shift, coupled with supply constraints from the lengthy expansion cycle for fiber preforms, has created a significant supply-demand gap. Nvidia has invested in Corning, along with Lumentum and Coherent, in a $4.5 billion total commitment to secure the optical supply chain for AI. Corning's competitive edge lies in its expertise in producing ultra-low-loss, high-density, and bend-resistant specialty fiber, which is critical for 800G+ and future 1.6T data rates. Its deep involvement in co-packaged optics (CPO) with partners like Nvidia further solidifies its position. While not the largest fiber manufacturer globally, Corning's revenue from enterprise/data center clients now exceeds 40% of its optical communications sales, and it has secured multi-year supply agreements with major hyperscalers including Meta and Nvidia. Financially, Corning's optical communications revenue has surged, doubling from $1.3 billion in 2023 to over $3 billion in 2025. Its stock price has risen nearly 6-fold since late 2023. Key future catalysts include the rollout of Nvidia's CPO products and the scale of undisclosed customer agreements. However, risks include high current valuations and potential disruption from next-generation technologies like hollow-core fiber. The company's long-term bet on light over electricity, maintained even through the telecom bubble crash, is now being validated by the AI boom.

marsbit14 saat önce

3 Years, 5 Times: The Rebirth of a Century-Old Glass Factory

marsbit14 saat önce

İşlemler

Spot
Futures
活动图片