Bigdata.com Launches the Tokenization of Content: Precision Grounding That Cuts AI Token Consumption by up to 100×

RavenPack launches token-based content licensing on Bigdata.com, a marketplace where AI agents retrieve only the tokens that carry the answer, slashing inference costs while grounding every response in licensed, cited premium content from over 170 providers

NEW YORK, July 20, 2026 /PRNewswire/ -- RavenPack today launched the Tokenization of Content on Bigdata.com, the first platform where AI agents retrieve, license, and pay for premium content in the same unit AI itself is bought and sold: the token.

At the core of the launch is a direct answer to the industry's most pressing economic problem, runaway LLM token consumption. Bigdata.com's precision retrieval sends an AI model the exact excerpts that carry the answer instead of the entire documents that surround it, reducing the context consumed per query by up to 100× while making answers sharper, cited, and less prone to hallucination.

The token bill has become a board-level line item

AI has moved from pilots to production, and token costs have moved with it: from a rounding error to a recurring operating expense that leadership now watches. Agents don't ask one question and stop. They loop, retrieving, reasoning, and regenerating across many steps, often running continuously and unattended. At fleet scale, those costs compound faster than headcount ever did.

A naive system pours an entire document into the model to answer a single question, for example, spending some 20,000 input tokens, most of them wasted, with the relevant signal buried in noise. Bigdata.com's precision retrieval inverts this: it returns the roughly 200 tokens that carry the answer. Same question, same model, roughly 100× less paid context in the window, and three wins at once:

• ~100× lower inference cost per query. You only pay for the tokens that carry the answer.
• Sharper answers. The model reads pure signal instead of noise, so responses are more precise and better grounded.
• Lower hallucination risk. With no irrelevant context to misread, the model has far less room to invent a confident wrong answer.

Every organization is staring at a token bill

"The market has become acutely sensitive to token costs, and rightly so. Agents in production burn tokens around the clock, and every organization is staring at a bill that compounds monthly," said Armando Gonzalez, CEO of RavenPack and founder of Bigdata.com. "But the industry is pulling the wrong lever. The answer isn't a cheaper token; it's fewer, better grounding tokens. The bill collapses and the answer gets better at the same time. And because every one of those context tokens carries a license and a citation, you're not just saving money; you're grounding your AI agents in content you can trust and trace. That's the launch: precision, provenance, and payment, all in one unit."

How content tokenization works

Every source on Bigdata.com is broken into tokens, the same units an AI model reads, and each provider sets and publishes its own price per token. When an agent asks a question, precision retrieval searches across every source, selects the exact excerpts that answer it, and delivers them to the model. The tokens retrieved are counted, attributed to their sources, and settled at each provider's rate: that consumption is the transaction. Each retrieval carries the license with it: a per-use right to ground the model's answer on that content.

A knowledge layer, not a pipe

The launch also addresses a cost trap hiding inside the obvious architecture: wiring an LLM to a dozen data providers through raw connectors, leaving the filtering to the model itself, inside the paid context window. Every source added is another firehose of unfiltered tokens, so the bill climbs with each integration while the signal gets harder to find.

Bigdata.com is the knowledge layer. Sources arrive analyzed, entity-resolved, and enriched through RavenPack's 25-year knowledge graph, which disambiguates entities like companies, securities, products, and people across every source and format, and retrieval selects the context that matters before a single token is billed. Firms can add more sources without inflating the bill.

Consumption pricing addresses subscription fatigue

Subscriptions keep adding up while buyers struggle to see the value, or even the usage, behind them. Every provider demands its own contract, annual minimum, and per-seat license, paid in full whether a source is used once or ten thousand times. Need a report? Buy the entire feed, or go without. And the model breaks entirely for AI agents: a seat assumes a person who logs in, but an agent may touch a hundred sources in a single task, and no one can afford to subscribe to them all.

One integration, one contract, one entity graph

Currently, integrating any new data source requires a separate procurement process, a different API, a new schema, and an entirely new method for identifying the same entities, if they are even identified. Bigdata.com collapses it all: one connection via MCP or API, one licensing structure, and entity resolution built in.

For example, RavenPack's knowledge graph maps millions of companies to tickers, ISINs, and industry keys, and recognizes the same entity across diverse sources like news, filings, and podcasts. Adding a source becomes a catalog selection, not an engineering project. And buyers can bring their own licenses: existing provider agreements are honored, buyers pay only for retrieval, and no one pays twice for the same content.

170+ providers live at launch

Providers already tokenizing their content on Bigdata.com span market data, newswires, research, transcription services, expert networks, and global media. Providers are paid in proportion to how much their content actually grounds agent outputs, converting AI consumption into a revenue stream that scales with the agent economy itself.

The Bigdata.com platform is natively connected to Claude, ChatGPT, and Microsoft Copilot, and connectable to any AI agent via MCP or API.

About Bigdata.com

Bigdata.com is the grounding layer for AI: a precision search and retrieval platform, and token-denominated clearing house that lets AI agents pay only for the exact content they consume, cutting token consumption by orders of magnitude while grounding every answer in licensed, cited sources. Natively connected to leading AI assistants and accessible by any agent, Bigdata.com powers grounded, traceable answers for the agent economy.

About RavenPack

RavenPack is a leading provider of data and AI infrastructure for financial institutions, with a 20+ year track record serving the world's most sophisticated hedge funds, banks, and asset managers. RavenPack operates two core products: RavenPack EDGE, its alpha and risk analytics platform, and Bigdata.com, its AI grounding and search platform.