@Pyth Network #PythNetwork #PYTH $PYTH
Introduction
Pyth Network is a decentralized financial oracle. It delivers real-time market data on-chain. It does this securely and simply. It does not rely on many middlemen nodes. Instead, it takes data directly from exchanges, trading firms, market makers. That means better speed, better trust, better accuracy.
This report explains:
What Pyth has done so far (Phase 1: DeFi domination)
What Pyth plans to do now (Phase 2: institutional subscription / revenue / expanding into a big market)
Why institutions want Pyth
How the token PYTH works, what utility changes are coming
What are the risks and challenges
Why this roadmap could change the value for everyone: data contributors, users, token holders
What to watch next
Phase 1: DeFi Domination
Pyth’s start was in DeFi (decentralized finance). In Phase 1 it focused on:
Building infrastructure to collect price data from first-party sources (exchanges, trading firms)
Providing many price feeds: crypto, real-world assets (RWAs), equities, FX, commodities etc.
Integrating with many protocols on many blockchains (100+ chains)
High update frequency and low latency, so DeFi smart contracts can use accurate, current data.
This built credibility. Developers and protocols saw Pyth’s data was good and reliable. It became one of the top oracles for DeFi. But DeFi only captures part of the demand for market data.
Vision: Disrupting the $50 Billion+ Market Data Industry
Pyth is now entering Phase 2 of its roadmap. The goal: expand beyond DeFi and serve institutional finance. That means selling high-quality, real world market data to banks, asset managers, trading firms, governments, and compliance/regulatory systems.
Here are key points about that opportunity:
The global market data industry is worth more than 50 billion USD per year. Institutions already spend this on acquiring data from legacy providers like Bloomberg, Refinitiv, etc.
If Pyth captures even 1% of that market, that is about 500 million USD in annual recurring revenue (ARR).
Institutions often pay high fees, suffer fragmentation of data, slow delivery, limited regional coverage. Pyth can address these problems by using its decentralized, first-party approach, fast updates, broad asset / geography coverage.
Phase 2: Key Features of the Institutional Subscription Product
What Phase 2 will bring:
1. Subscription-based product
Pyth plans to offer data subscription services for institutions. These will be premium feeds: off-chain & on-chain, very low latency, high frequency. Includes use cases like risk models, analytics, regulatory/regulatory compliance workflows, display data, historical research.
2. Multiple payment methods
Institutions may pay in USD, stablecoins, or PYTH token. This gives flexibility.
3. Revenue flows to the DAO + token holders + data contributors
Subscription revenues are proposed to flow into Pyth DAO. Then the DAO will decide how to use those funds: possible options include buybacks, revenue sharing, rewarding publishers, or staking rewards. This adds real utility to PYTH beyond just governance.
4. Enhanced Asset & Geographic Coverage
More real-world assets (stocks, equities, FX, etc.), more market data from different geographies. For example, Pyth has added equities from UK, Hong Kong, Japan, emerging markets.
5. Publishing & Monetization for Data Providers
Those who already produce data (exchanges, market makers etc.) can publish via Pyth, and be rewarded. This flips the model: rather than paying data providers but letting others profit more, Pyth lets providers capture more value.
6. DAO Governance & Token Utility Enhancements
Token holders will have more say. Also, token may be used for subscription payments, staking, governance. More utility increases demand.
Institutional Adoption: Why Institutions are Interested
Institutions (banks, asset managers, hedge funds, regulatory bodies) have big needs:
Need real-time, accurate, broad market data for risk, compliance, trading, settlement
Current providers are expensive, slow, opaque, fragmented by geography or asset class
Institutions want to reduce costs and increase reliability & transparency
Pyth offers:
First-party data sources (less intermediaries) → more trust
Fast, accurate updates → good for risk models, trading
Global reach, many asset types → fewer gaps in data
Transparent pricing, subscription model → predictable costs perhaps
Also recent proof points: Pyth has already been invited by institutions to test its subscription product. Some companies said the data was better than prior suppliers: more comprehensive, better performance.
Token Utility: What PYTH Does / Will Do
The PYTH token is central to Pyth’s value and future. Key utilities:
1. Incentives for Data Contributors / Publishers
Providers who feed data into the network are rewarded in PYTH tokens. This encourages high quality and more coverage.
2. Governance
Token holders can vote in Pyth DAO on decisions: how revenue is allocated, which features to prioritize, fee structures, subscription terms, etc. This gives holders power over direction.
3. Revenue Sharing / Token Use in Subscriptions
Institutions might pay in PYTH. DAO might execute buybacks or distribute a share of subscription revenue to token holders / stakers / data contributors. This gives an economic benefit to holding PYTH.
4. Maintaining Data Integrity & Security via Staking
PYTH holders / stakers may be involved in staking / oracle integrity work. There is also the concept of oracle integrity staking (some amount of token locked to ensure correct behavior).
Financials & Traction: Where Pyth Stands Now
Some numbers to show real progress:
600+ protocols across 100+ blockchains integrated already.
1,800+ price feeds overall, including about 900+ real-world assets.
Total Value Secured (TVS) in Q2 2025: about 5.31 billion USD, rising from previous quarter; Pyth is one of the few oracle networks growing in this metric.
Price updates in Q2 2025: around 648,240 updates (on-chain) in that quarter, up 10.8% quarter-on-quarter. Cumulative updates since inception ~759 million.
These show that Pyth is not just planning, but already operating at scale and seeing growth.
Why PYTH Could Be Undervalued
Many oracles suffer from weak revenue models. Their tokens are used for governance & staking but do not capture large revenue flows. Sometimes fees and usage don’t go back to token holders. Because of this, market often undervalues the token compared to its utility.
Pyth’s Phase 2 changes that by:
Creating subscription revenue
Sharing that revenue via DAO / token holders
Using token for payments, staking
If adoption by institutions grows, demand for PYTH will rise (for payments, staking, governance). That puts pressure on token value, if supply / unlock schedule is managed well.
Risks & Challenges
To be fair, there are risks Pyth needs to manage:
1. Competition
Legacy firms like Bloomberg, Refinitiv, FactSet are large and well entrenched. Institutions trust them. Pyth must prove it can match reliability, regulation, customer support.
2. Regulatory Risk
On-chain data, data licensing, privacy, compliance differ by country. Some data (e.g. economic or government data) may have legal constraints.
3. Adoption Speed
Selling to institutions takes time: sales cycles, legal contracts, support, trust, integration. It won’t happen overnight.
4. Quality & Latency Demands
Institutions often demand extremely high guarantees: service level agreements (SLAs), uptime, latency. If Pyth fails or has glitches, it could hurt reputation.
5. Tokenomics / Supply Issues
Unlocks of tokens, inflation, staking rewards need to be designed carefully so token holders benefit and supply pressure doesn’t dilute value.
6. Infrastructure & Cost
To serve high-volume, low-latency institutional feeds, Pyth needs robust infrastructure, redundancy, security. These cost money. Scaling cost vs revenue must be balanced.
Why I Believe Pyth’s Phase 2 Will Be Powerful
Here are reasons I think Pyth has a strong chance:
It already has Phase 1 working well. The data feeds, the integrations, the credibility are there. It is not starting from zero.
Demand exists. Institutions already complaining about high data costs, fragmentation. If Pyth can offer accurate, fast, less expensive, more transparent data, institutions will be interested.
The token alignment is strong. Tokenholders, data providers, users all get benefits. If revenue sharing is well implemented, PYTH gains value.
Pyth is thinking upstream: capturing data from originators, rather than resellers. That gives more margin and more control.
The DAO has shown it is engaging with community proposals (Monetization, Subscriptions) which suggests plan is not just theoretical.
What to Watch Next
To see if Phase 2 succeeds, some signals to monitor:
1. Institutional Subscription Product Launch
When is the product formally launched? What SLAs, pricing tiers, asset coverage, and payment methods are offered?
2. Adoption from Traditional Finance Firms
Are banks, asset managers, regulators using Pyth subscription feeds? Are there customer contracts?
3. Revenue and DAO Actions
How much subscription revenue comes in? How DAO decides to use that revenue (buybacks, token rewards, governance)?
4. Token Metrics
How many PYTH are staked? What is the circulating supply? Any unlock_schedule events? Demand vs supply.
5. Quality Metrics
Latency, accuracy, number of price feeds, asset & geography coverage. How fast are updates?
6. Regulation / Legal Frameworks
Regions where market data has strong regulation (EU, US, Asia) and how Pyth handles compliance, data licensing.
Conclusion
Pyth Network is not just another oracle. It built its foundation in DeFi (Phase 1), with very strong performance, broad adoption, many feeds. Now it is entering Phase 2: aiming to be the price layer for institutions, expanding reach, creating real revenue via subscription products, sharing value via PYTH token.
If Pyth succeeds at Phase 2:
It could capture a piece of the $50B+ market data industry
Token holders and data contributors will see more utility and value
Institutions will gain access to better, cheaper, more transparent data
But success depends on execution: delivering high-quality service, earning trust, handling regulation, managing tokenomics.
For those thinking long term, this roadmap gives a strong reason to watch PYTH, contribute, hold, and participate (if possible). It may be undervalued now because these changes are just starting; but the potential upside is big.
Final Thoughts
Phase 1 (DeFi Domination) was essential. It built trust and tested the product.
Phase 2 (Institutional Subscription, Revenue Model) is the turning point. It turns Pyth from “just infrastructure” into infrastructure plus business.
Token utility expansion is crucial. The more revenue and usage, the stronger PYTH gets.
If you believe that in the future, financial decisions – trading, risk, compliance, settlement – all need real-time, reliable data, then Pyth is positioning itself to be in the center of that future.
References (key sources)
Pyth’s Phase 2 blog: “Phase Two: Institutional Monetization Through Offchain Data”
State of Pyth Q2 2025 report (TVS, price update numbers, asset coverage)
DAO proposals and monetization offchain expansion discussions
Market data industry size, 1% capture potential, etc.
