How Ideal Security uses AI Teammates to free its logistics team from manual work

Three times a week, a spreadsheet lands in the inbox of Svitlana Zapolska, the Purchasing and Logistics Manager at Ideal Security. It contains the latest status of every ocean shipment the specialty door hardware supplier has in transit from suppliers.

Staying on top of these updates is critical because accurate information helps Ideal Security keep inventory moving and logistics running smoothly. But until recently, updating those shipments meant a lot of tedious work for Svitlana. She had to manually open each freight file, cross-reference shipment identifiers, and update a long list of fields in Asana line-by-line.

Now, an Asana AI Teammate does it for her.

When most people think about AI right now, they think about automating work. There's this other stream of augmenting work that's more exciting for me.”

The organizational cost of manually tracking 20 shipments 

At any given time, Ideal Security has 15 to 20 open shipments moving between suppliers in Asia and two North American warehouses. Three times a week, the company’s freight forwarder sends an updated tracking spreadsheet with upwards of 30 columns of information for every active shipment. That adds up quickly, with up to 1,200 columns of data coming in each week.

Svitlana was responsible for reading through each file, matching records by bill of lading (HBL) number, and updating the corresponding Asana tasks with current status information. It was repetitive work, but it mattered: keeping shipment information accurate and up to date was essential to ensuring operations ran smoothly and the right people stayed informed.

Because every additional field meant more manual effort, the team only tracked the information needed to keep downstream workflows running. Everything else was left out, because no one had time to maintain it.

“It was busywork that was keeping [Svitlana] from doing other things,” says Liohn Sherer, President of Ideal Security. “It was a lot of time that wasn't really valuable, but it needed to happen.”

How the AI Teammate tracks ocean shipments 

To eliminate the manual work, Sherer built an Asana AI Teammate and put it to work alongside Svitlana. Now, when the freight file arrives, the AI Teammate jumps in, using the instructions stored in its memory to process every shipment automatically.

Step 1: The freight file arrives in Asana

The freight file arrives by email and is forwarded into a dedicated Asana project created for this workflow.

Step 2: A rule assigns work to the AI Teammate automatically 

As soon as the task is created, an Asana rule assigns it to the AI Teammate, adds Svitlana as a collaborator, and removes Sherer, who owns the forwarding automation but doesn't need to follow each shipment update.

Step 3: The AI Teammate matches each shipment

The AI Teammate reads through the spreadsheet, identifies each shipment, and matches it to the correct Asana task. It first looks for exact matches using HBL numbers, but if those aren't available, it can confidently match shipments using PO numbers, shipment numbers, and other contextual information. Because the AI Teammate has instructions stored in its memory, it knows which information to update—even when shipments are merged, split, or transferred.

Step 4: The AI Teammate updates custom fields for each shipment

Once a shipment is matched, the AI Teammate updates the key tracking fields in Asana, including shipment status, bill of lading, container number, and estimated departure and arrival dates. Keeping those fields current automatically triggers the downstream workflows that notify the right people at the right time.

Step 5: The AI Teammate flags outliers and asks questions in comments 

Most shipments are processed automatically. If the AI Teammate can't identify a shipment with enough confidence, it loops in a human expert. The teammate creates a subtask, tags the appropriate team member, and shares the information it couldn't resolve. Once someone replies in the task comments, the AI Teammate picks up where it left off.

From minimum viable tracking to full control over visibility

When the work was done manually, Ideal Security tracked only the information required to keep work moving. Now, the team tracks what Sherer calls the “nice-to-haves:” additional shipment data that gives the team better visibility, without creating more work.

The AI Teammate also brings consistency that's difficult to achieve with manual work.

"In many ways, it’s more reliable and more effective than a human," Sherer says, "because it doesn't get tired and it has perfect memory.”

There's a flexibility advantage, too. While traditional approaches to automating repetitive tasks  often break when spreadsheets change, the AI Teammate can adapt without requiring the process to be rebuilt.

Logistics that run without the manual work

The freight file still arrives three times a week, but now all Svitlana has to do is create the initial shipment record in Asana. From there, the AI Teammate takes over, automatically matching shipments and keeping information updated. Instead of manually updating every custom field by hand, Svitlana can focus on the work that requires her experience and judgment, while the AI Teammate handles the repetitive administrative work in the background.

Once you show people what's possible with an AI Teammate, their eyes light up. And then they can go and start rolling them out themselves. And so all of these operational friction points can now start to get addressed and solved.”