We turn raw customs filings into something a trader can actually use — searchable, verifiable, and specific enough to act on.
Every day, customs authorities and port operators around the world generate millions of records describing goods crossing borders. Individually they are administrative paperwork. Together they are the most complete picture of global trade that exists. We collect those records, clean and classify them, and make them searchable by HS code, product, company, country and port.
Summary statistics tell you a market exists. Shipment records tell you who to call. We publish the latter.
Every row maps back to a declared consignment. We do not estimate figures and present them as fact.
Traders should not need a separate subscription per country. Our coverage sits behind a single search.
A clean result you can export and act on today beats a dashboard you have to learn first.
Four steps between a customs declaration and the row you see on screen.
A customs declaration or bill of lading is filed with the relevant authority at the point of import or export.
We obtain the record as a public filing, on the release cycle each authority publishes.
Fields are normalised — HS code, quantity, value, ports — so records from different countries sit in one consistent structure.
The record is indexed and searchable within our platform, ready for you to filter, export or track.
Exporters building buyer lists, importers qualifying suppliers, manufacturers tracking downstream demand, trading houses matching supply to demand, logistics providers targeting lanes, and analysts who need trade figures that hold up to scrutiny. If you want to see what the data looks like for your product, request a free demo.
Three principles govern how records reach these pages, and they are worth stating plainly because they determine what the site is useful for. Nothing is estimated: where a source did not publish a field, it stays blank, because an inferred counterparty or an imputed value is indistinguishable from a real one once it is downstream. Every figure carries its period and its source. And the aggregate statistics on the country, chapter and industry pages are generated directly from the ingested dataset rather than typed into the page, so they cannot drift away from the data behind them.
| Principle | What it means in practice |
|---|---|
| No estimation | A blank field means the source did not publish it |
| Provenance on every figure | Period and source shown next to the number |
| Generated, not typed | Statistics render from the dataset at build time |
| Limits stated | Markets with no reported data say so explicitly |
| Separation of layers | Aggregates and shipment records are never presented as the same thing |
Trade data is frequently oversold, and the overselling is what erodes trust in it. Customs records cover goods that crossed a border. They do not cover services, domestic trade, margin, contract terms or intent. Coverage of counterparty names varies by jurisdiction and is not universal. Data arrives on a lag and published periods are revised. None of that reduces the value of the record; pretending otherwise does.
Finding buyers who already import the category, and pricing into a band they can see.
Learn more ›Verifying suppliers on shipping history before committing credit or capacity.
Learn more ›Sizing the traded component of a market and mapping the supply base.
Learn more ›Reading lanes, ports and counterparty consistency.
Learn more ›Where a market has no reported figures, the page says why. Where a field is blank, it is blank. That is a deliberate choice about what a data provider owes its readers.
Every statistic on this site is generated from the ingested dataset at build time rather than written into the page. That is a deliberate constraint: numbers typed into marketing copy drift away from the data behind them within months, and nobody notices until a reader checks. Generating them means a figure on a country page and the dataset it came from cannot disagree, and it means that when a market has no reported data, the page says so instead of quietly omitting a section.
The direction is more depth rather than a larger country count. Deeper shipment-level coverage in the markets people actually trade with, better entity resolution so company profiles can be relied on, and clearer separation between what is measured and what is inferred. A headline number of countries is easy to increase and tells a reader almost nothing; knowing exactly what is available for the three markets you care about is what changes whether the data is useful.
Trade data rewards a short, boring discipline far more than it rewards technique. Four steps cover most of it, and skipping any one of them is where the confident wrong conclusions come from. Fix the classification first, because every filter, every duty figure and every price comparison downstream is keyed to the tariff line and inherits any error in it. Then read at least three years, so that seasonality and trend can be told apart rather than conflated. Then exclude the most recent one or two periods, which are still filling in as late filings arrive. Then separate value from volume, because a value movement can be price, quantity or a change of mix inside the line, and those point in different directions.
| Step | What it prevents | Cost of skipping it |
|---|---|---|
| Confirm the tariff line | Filtering the wrong product | Every downstream figure is wrong by an unknown amount |
| Read three years | Mistaking a season for a trend | Strategy built on a cyclical high or low |
| Drop the incomplete tail | Reading reporting lag as decline | Writing off buyers who never stopped buying |
| Separate value from volume | Reading price as demand | Investing against a movement that was not demand |
| Check the counterparty | Acting on an unverified name | Credit or capacity committed to a company with no history |
| Record the period and source | Unrepeatable analysis | Figures nobody can reconcile three months later |
The material here is one layer of a set that is meant to be used together. The country pages establish the shape of a market from official reported figures. The HS chapter pages take a single classification down to product level. The industry hubs group the chapters that make up a real industry and sum them, because almost no industry is one chapter. The India location pages read the national record as places, using the clearance point as a geographic signal. And the trade role pages take one job at a time — building an importer list, checking an exporter, reading a lane — and set out the signals that matter for it.
Reported totals, partner markets and chapter breakdown for 99 markets.
Learn more ›All 98 chapters, each with the markets that trade it.
Learn more ›Thirty-eight industries, each summed across the chapters it spans.
Learn more ›Seventy-nine trading places, their gateways and their clusters.
Learn more ›The same record read as a buyer list, a supplier check or a lane analysis.
Learn more ›Classification, documentation, pricing, sourcing and compliance in practice.
Learn more ›Customs records cover goods that physically crossed a border and were declared to an authority. They do not cover services. They do not cover domestic trade, so a business selling mainly inside its own market will look far smaller here than it is. They carry no margin, no contract terms, no payment behaviour and no intent. Coverage of counterparty names varies by jurisdiction and is not universal, data arrives on a lag, and published periods are revised as corrections come in.
None of that reduces what the record is good for, and stating it plainly is what makes the rest credible. Used within its limits, customs data is one of the very few commercial sources where the underlying event actually happened, was documented at the time, and was documented under legal obligation rather than for promotional purposes. That is a rare property, and it is worth not overselling.
Before relying on any trade dataset — ours or anyone else's — ask which markets are covered at which depth, what the lag is in each, how company names were matched, and what happens to a historical series across an HS revision. The answers tell you more than any headline figure.