Navoiyazot’s story
Navoiyazot was built in the 1960s, when the natural gas fields of the Bukhara region made it possible to produce nitrogen fertilizers close to the farms that needed them. More than ten design institutes took part in planning the plant. The first ammonium nitrate was produced on 29 December 1964, and two days later the state commission accepted the plant into operation, the date from which its history is counted. The first ammonia followed in March 1965.
Since then the plant has grown into one of Uzbekistan’s largest chemical producers. It turns natural gas into mineral fertilizers, acids, reagents, industrial chemicals, technical gases, textile materials, resins and polymers: more than 70 products in all, sold at home and to customers in ten countries.
It is still investing. Its projects include new ammonia and urea production, a nitric acid plant, and a complex for polyvinyl chloride, caustic soda and methanol, which adds capacity for 100,000 tonnes of PVC, 300,000 tonnes of methanol and 75,000 tonnes of caustic soda a year.
The company describes those projects as part of modernising its technology and re-equipping its production, so that its products stay competitive at home and abroad through better quality and lower cost. The ammonia project, for example, is meant to replace ammonia units first put into operation in the 1960s.
Copy, paste, check
At that scale, sales information is usually spread across many systems and files. Orders, customers, shipments and product data each tend to live where they were first created, and each system answers only part of a question. Building a picture of one customer or one product line by hand means exporting, copying and checking.
The result is stale as soon as it is finished. By the time a combined file has been reconciled, the source systems have moved on, and the next question starts the process again. People with sales and commercial roles end up spending their time moving data instead of using it.
Copying by hand also introduces errors. A row pasted into the wrong place or a figure taken from an old export can travel through every report built on it, and the more sources there are, the harder it is to know which version to trust.
For a company that sells to customers in ten countries, the number of sources only grows. Each market, each product group and each team can end up with its own files, and the effort of combining them grows with them.
Routine work that waits
Alongside the data sits a steady stream of routine work: a task for a new order, an update to the person responsible, a record that needs to change when something else changes. None of it is difficult, but all of it depends on someone noticing that it is needed.
When that work waits for a person, it waits for their attention. Steps happen late, or twice, or not at all, and nobody can easily see which. For a company with many products and customers, those small delays add up across the business.
None of this is unusual for a large producer. It is simply what happens when data and the work around it are kept apart, and when the steps that follow a change depend on someone remembering to take them.
The PromptLab moment
Navoiyazot did not want another system to fill in by hand. It wanted its existing data to arrive in one place on its own, and the routine work around that data to happen without waiting for someone to start it. PromptLab offers both: integrations, webhooks and an API to bring data in, and workflow automation on every plan to act on it.
Navoiyazot connected its data sources to PromptLab. The data now arrives in the platform on its own, and automation can act on it from there. The approach suits a company with established systems. Nothing has to be switched off on day one, and the sources that already work keep working. PromptLab becomes the place where their data meets, rather than one more source to keep in step.
How Navoiyazot uses PromptLab
For Navoiyazot, PromptLab is where data from several sources comes together and where routine steps are handled automatically. The work falls into three parts.
Each part supports the others. Connections supply the data, automation acts on it, and a single platform makes it possible to see and report on everything together.
Connections that bring the data in
Connections take data from the sources Navoiyazot already uses and put it into PromptLab, so nobody has to enter it again. PromptLab can sync with other CRM and ERP systems, watch spreadsheets, import files and receive data through webhooks and its API, so the source systems keep doing their job while the data gathers in one place.
Because the data arrives on its own, it stays current. A change in a source shows up in PromptLab without an export, and the team works from what is true now rather than from the last time someone copied a file.
Records that arrive this way are ordinary PromptLab records. They can be linked to accounts and contacts, filtered in saved views and picked up by workflows, exactly like data entered by hand.
Automation for the routine steps
Workflows in PromptLab start from a trigger, such as a new record arriving or a field changing, and then take the next step. When new data arrives, an automation can create a task, update a record or notify the person responsible, without waiting for someone to notice.
Ready-made templates cover common cases, and each workflow can be adjusted to how Navoiyazot works. Every run is logged, so the team can see what happened and when, instead of wondering whether a step was done.
The result is that routine steps happen when they are needed rather than when someone has time. People stay responsible for the decisions, and the platform takes care of the steps that follow them.
Every product line in one platform
With data from each source in the same platform, fertilizers, industrial chemicals and polymers can be reviewed side by side. A question about a customer or a product line starts from one place instead of several files.
Reports and dashboards read from that combined data. The team can group figures by product, customer or period, save the reports it uses most and place them on a shared dashboard, so everyone looks at the same numbers.
Reports can also be scheduled, so the figures a team reviews regularly are refreshed without anyone rebuilding them. A review starts from the numbers instead of from the work of collecting them.
Built to grow with the plant
Navoiyazot’s investment projects will add new products and new capacity, and with them new customers and more data. A setup where data arrives on its own and routine steps run automatically scales with that growth, instead of asking more people to copy more files.
Each new source can be connected in the same way, and each new routine step can become another workflow. The work of keeping data together moves from people to the platform, and people get back to the customers. For a plant with six decades of history and a full programme of investment ahead, that is a practical way to modernise: keep the systems that work, and connect them.
