Demo

See real-time data,
on your own use case.

We tailor the walkthrough to what you trade or train on - the sources, the latency, and the delivery that fit your stack.

  • Live signal, the moment it happensWatch real-time records arrive, timestamped at the edge and evaluated - the edge of an event before it clears the tape.
  • Coverage for your use caseSee the global, satellite, and alternative sources relevant to what you trade or train on.
  • Provenance on every recordSee how each record traces back to its source and timestamp - data you can act on and audit.
  • Streaming and history, one interfaceThe live stream for production and point-in-time history for backtests - through the same API.

From quant desks to AI labs - built for any team that needs ground truth, in real time.

Request a demo

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Measured against something you already have a view on.

A demonstration on our showcase coverage proves very little, because we chose it. An evaluation is worth running against events you already track, where you know what happened and when you learned about it, so the comparison has a control. Bring the use case; we point the network at it.

What you are measuring is two things, and both are recomputable from the records rather than asserted by us. How much earlier a record arrived than your existing source, which the event time and the serving point of presence on each record let you calculate. And how often it was right, which is what the authenticity and data quality values are for.

The evaluation runs against live coverage with a sandbox credential, not a curated sample file, because a sample cannot demonstrate whether we are early. Research on point-in-time history runs alongside it, so a backtest and the live stream can be compared directly - they are the same records.

What desks and training runs do with it

What the first thirty days look like.

We would rather be measured than described. An evaluation runs against live coverage on a use case you already have an opinion about, because the only convincing result is one you can check against something you already know.

  1. Pick the events that matter to you

    Not our showcase coverage - yours. A commodities desk and an AI infrastructure fund care about different halves of the world, and the evaluation is worthless if it runs on the half you do not trade.

  2. Measure us against what you have

    Run our stream alongside your incumbent source and compare on the only two questions that matter: how much earlier the record arrived, and how often it was right. Both are recomputable from the provenance on every record.

  3. Backtest on point-in-time history

    Take the same coverage back through the archive and test the signal on what was actually knowable at each moment, with no corrected values leaking backwards into the result.

  4. Move it into production unchanged

    The interface, the record shape, and the data quality values are identical between the sandbox and production, so going live is a credential change rather than a rebuild.