Carbon Arc offers a marketplace for buying and selling licensed, real world transaction data to power LLMs and enterprise applications

Although data is everywhere, many of them remain trapped within corporate budgets, institutions, and old systems.

Mckeown’s way: “Special data is secured in every public budget in the world. The economy generates a huge exhaust-cloning data, health care claims, trade demands, credit cards-but they do not flow to decision makers.”

At the same time, the institutions driven by artificial intelligence face a set of generally used data. Through LLMS models, general data groups have quickly exhausted, companies must search for different and ownership intelligence to survive.

“More data means better questions,” Macion said. “Adult players will need more and more distinct data assets when they reach the market.”

Carbon Arc solution is to treat data such as financial asset, and to create an organized data market in the way in which stocks, bonds and derivative derivatives are traded today. This shift provides price discovery, detection of demand and actual time-which leads to liquidity to a non-historical data economy.

“The era of intelligence should not be different from previous revolutions – both the main technological transformation in history have required a shift in the basic initial materials of power,” McChyun added.

How does the carbon data market work

Carbon Arc has built a two -sided market where data owners contribute to their data groups, and companies pay each megapixel to the visions they use.

• Consumption -based pricing form Transfer data purchases from large Capex expenses to exact transactions, where the intensity and speed of the consumption engine value.
• API arrival Companies can directly combine organized intelligence into the analytical workflow, artificial intelligence models and institutions tools.
• Choosing granular data – unlike platforms that mix the main performance indicators, the carbon arc guarantees raw and unprecedented visions. McChyun confirms“We do not integrate the main performance indicators because we do not want to make self -decisions – what you choose is exactly what you get.”
• Developable architecture It is designed for high -frequency intelligence through industries such as financing, retail trade, artificial intelligence development and media.

While consumption -based pricing provides flexibility, it may also be difficult to manage. “Consumption prices are a great trade, but they frighten people because it is difficult to manage,” Mcihyun admitted. To address this, Carbon Arc offers a wallet structure that gives customers better control of their spending.

Already operating institutions across sectors

The platform is already used through multiple industries:

• Financial institutions and hedge funds Using market intelligence in real time for investment models.
• Ai native & llm companies – Enhancing artificial intelligence training with organized ownership data groups.
• Branding brands for retail and consumers – Tracking consumer spending, improving promotion and prediction of demand.
• Media and health care organizations Improving supply chains, consumer participation, and operational efficiency.
• Sports Florida Panthers Nhl used Carbon Arc visions to analyze fans preferences, which leads to new entertainment partnerships.

Clean and easy -to -navigate user interface with information panels or automatic

The Carbon Arc platform is designed for easy use, with interactive data perceptions, API connection and actual time intelligence flow.

Main interface features:

• Customized filters – Users can divide data by category, company and brand of the main product and standards.
• Interactive data information panels – Graphics display visions such as site traffic, points of sale, and supply chain data.
• Division of relationships based on the graph Users can explore communications between brands, products and competitors.
• API integration The flow of organized intelligence guarantees smoothly to business intelligence tools and artificial intelligence models.

For retailers, the platform provides comparisons in the actual time for market share, sales trends and consumer behavior through competitors such as LululeMon, American Eagle, and AberCrombie & Fitch.

In institutional analyzes, users can track spending trends via major retail dealers such as Walmart, Kroger and Target-which leads to a redirecting and pricing strategies.

What developers and decision makers mean data

Software and data scientists often face major challenges when dealing with non -structured data. Carbon Arc simplifies this process by restructuring raw data automatically, providing actual time visions via API, and eliminating the need for large -scale prior treatment.

Instead of adhering to wholesale data contracts, companies can only consume the visions they need, which reduces operational operating restrictions and budget.

The main benefits include:

• Improving access to data High -value data groups become available without complex extraction or manual processing.
• Flexible pricing form Institutions can pay based on actual data consumption and improve costs.
• API integration Data visions can be merged directly into current analyzes, information panels and decision -making function.
• Historical and constantly updated data groups Companies acquire updated visions without relying on slow -moving data pipelines.

“The predictions of artificial intelligence will not improve only over time, but they will always need historical data as a basis,” Mcihyun explained, saying that Arc Carbon may return to centuries, but they constantly add new updates on a weekly or daily basis, depending on the specified part.

In addition, the company guarantees supporting its data in multiple locations.

Macyun told me: “We are obsessed with repetition.” “I never want to take advantage of a single data provider – we have multiple sources to protect from high prices or supply disorders.”

Transfer data from a search product to a trading origin

Mckeown sees Carbon Arc as part of a greater shift in how to evaluate and exchange data.

“We are building a data market in the way in which stocks, bonds and derivatives are traded today – which leads to the discovery of prices and the discovery of demand on an organized stock exchange.”

This basic shift in data economics can reshape artificial intelligence, financing and business intelligence, which makes actual time visions easier and costly.

With $ 55 million financing, Carbon Arc is in a good position to determine how institutions and trade arrive and integrate intelligence. By converting data into liquid, trading assets, the company addresses one of the biggest challenges in artificial intelligence and commercial decisions today-where the data is no longer closed but it leads to the activity of ideas and innovation.

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