We’re pleased to announce that our API is now available on Apiosk, a European-focused infrastructure platform that enables API providers to accept per-call payments from AI agents, settled in USDC. Agents and the developers building them can now access CityFALCON’s financial intelligence, real-time news, sentiment, insider transactions, investor relations content, and official filings, priced per request with no subscription.

The Apiosk partnership follows our recent listing on Proxygate and reflects a shared belief that agentic software needs infrastructure designed for how it actually works: on-demand, per-call, and without the friction of traditional procurement. Where the Proxygate blog post focused on the cost economics of building financial intelligence at scale, this article looks at three characteristics of the our API and data that make it particularly relevant for the next wave of AI agents: multilingual coverage, breadth across data types, and the ability to sift signal from noise at volume.

 

Agents Don’t Sleep, and They Don’t Speak Only One Language

Consider a common scenario in the agent economy: an autonomous trading or research agent operating in Europe with a focus on Japan. It’s 3am local time in Europe. A major Japanese company issues a press release or a domestic news outlet publishes a market-moving story in Japanese. The agent needs to process that information immediately, whether or not a human user is awake to intervene.

For any agent operating internationally, this is not an edge case. Global financial markets never really close. Corporate news, insider transactions, regulatory filings, and investor communications happen continuously across time zones, and they happen in dozens of languages.

Our API is designed for exactly this environment. It aggregates content from over 10,000 sources across more than 50 languages, delivered in a consistent, structured format regardless of the source language. A Japanese news story, a Brazilian investor relations post, a Korean company disclosure, and a French press release all arrive through the same API endpoint, with the same structured metadata attached.

For agents, this is transformational. Instead of maintaining separate integrations for different regional data providers, waiting for translations, and possibly paying for unneeded translations, an agent can query a single API and receive structured, scored, tagged data in the original language and ready to act on. That means coverage in the local language of the market being monitored, at whatever hour that market becomes active, without the agent having to build its own multilingual processing layer.

This matters even more in an environment where markets are increasingly interconnected. A move in Japanese equities affects positioning in US futures. A regulatory decision in Brussels ripples through Asian markets. Agents that can only see one language, or that can only operate during one region’s business hours, are structurally disadvantaged.

 

Beyond News: The Breadth of Financial Intelligence

Most financial data APIs specialise in one type of content. Some focus purely on news. Others provide only filings. Others focus on alternative data like insider transactions or investor relations content.

For an agent trying to make decisions based on what’s happening at a company, this fragmentation creates sourcing problems. Integrating multiple providers is expensive, both in engineering effort and in ongoing cost. Reconciling different data formats, timestamps, entity identifiers, and refresh cycles adds complexity. And gaps between providers can leave agents blind to important context.

Our API brings multiple content types into a single, unified stream. Through Apiosk, agents can access:

  • Real-time news from over 10,000 sources in more than 50 languages
  • Analisi del sentimento at the story level and as a timeseries across assets and topics
  • Punteggio CityFALCON for relevance ranking of content to specific tickers, sectors, and topics
  • Insider transactions, giving visibility into what corporate officers and major shareholders are actually doing with their shares
  • Investor relations content, including earnings materials, presentations, and shareholder communications globally
  • Official company filings in the US and UK

Each of these data types serves a different agent use case. A trading agent might weight news sentiment and insider transactions heavily. A research agent might focus on IR content and filings. A compliance agent might monitor all of them, watching for events across every category.

The breadth also matters at the strategic level. Complete situational awareness of a company requires all these signals. A CEO stepping down might be announced in a press release, discussed in news coverage, disclosed in a filing, referenced in earnings materials, and reflected in insider stock sales, all within days or even minutes of the event. Agents with access to only one channel may see only part of the picture.

 

Sifting Signal from Noise at Volume

The final characteristic worth highlighting is how our API handles the sheer volume of financial content. A single day generates tens of thousands of news stories, filings, and updates across global markets. For agents that need to process this volume in real time, filtering matters more than aggregation.

As a first line of defence, our data is only sourced from human-vetted sources, which helps significantly in weeding out algorithmic noise, most promotional content, and misclassified tags. The data feed that we start working with has a minimum quality level, before we even start processing it further to eventually be delivered to clients.

Once in our pipeline, every piece of news content flowing through the CityFALCON API is scored on at least two dimensions: sentiment and relevance. Sentiment captures whether a story is positive, negative, or neutral for a specific asset. Relevance, via the proprietary CityFALCON Score, captures how important the story is to that asset, distinguishing between a passing mention and a substantive development.

For agents, these scores are the difference between a manageable data stream and an unusable firehose. Instead of receiving every article that mentions a ticker, an agent can subscribe to content above a specific relevance threshold, or trigger actions only on sentiment shifts above a specific magnitude. This turns raw content into filtered, actionable signal.

This is particularly important given how much financial content is essentially noise from a decision-making perspective. Boilerplate press releases, restatements of prior news, and syndicated coverage all fill the raw feed. Sentiment and relevance scoring separate the material developments from the surrounding noise, so agents can focus their processing budget on what actually matters.

 

How Apiosk Fits the Model

Apiosk complements the CityFALCON API by providing a payment infrastructure designed specifically for how AI agents transact. Agents pay per request in USDC, and for providers that opt-in, there is an off-ramp directly into euro accounts via SEPA. For consuming agents, there is no subscription to negotiate or contract to sign.

For European businesses in particular, Apiosk’s SEPA settlement makes agent-driven revenue accessible without the operational overhead of managing crypto directly. For agents and developers, the per-call model means paying only for what’s actually used, without the sunk cost of subscriptions that may or may not match usage patterns.

This complements rather than replaces our other partnerships. As we described in our earlier article on the CityFALCON × Proxygate partnership, each of these marketplaces serves the broader agent economy. ProxyGate and Apiosk together make CityFALCON’s financial intelligence accessible through the payment rails and marketplaces that agents actually use.

Moreover, enterprise contracts are not obsolete. High volume applications are better off with a negotiated contract with cost caps and a direct relationship with the team, who can provide services otherwise not available to agent-based users. 

 

Building for the Agent Economy

The common thread across these partnerships is that the AI agent economy has different needs than traditional enterprise software. Agents operate continuously. They cross language boundaries as easily as timezones. They need structured, scored data more than raw text. And they need to pay for exactly what they use, priced per call rather than per seat or per subscription.

We have spent more than a decade building the infrastructure to serve this kind of usage: aggregating, scoring, and structuring financial content at scale. The Apiosk partnership makes that infrastructure available to agents and developers through a per-call payment model designed for machine-to-machine transactions.

Whether you’re building a trading agent that monitors markets somewhere in the world overnight, a research agent that pulls together news, filings, and insider activity for company deep dives, or a compliance agent that watches for regulatory events across dozens of jurisdictions, our new listing on Apiosk gives you access to the underlying data at fair prices in the way your agents actually operate.

 

Explore the Listing

The CityFALCON API is now live on Apiosk. Agents and developers can discover the endpoint, call exactly the data they need, and pay per request in USDC, with automatic euro settlement for European businesses.

Explore the listing on Apiosk to get started, and read more about our approach to the agent economy in our earlier article on the CityFALCON × Proxygate partnership.