Welcome to this episode of The New Warehouse Podcast, where Kevin chats with Audrey Djiya, CEO and Co-Founder of Handled. Audrey shares how her team is tackling one of the most overlooked areas of logistics: what happens after the customer clicks ‘buy’.

Handled is building an AI-powered operations platform focused on eliminating the manual, fragmented, and reactive work that dominates post-purchase workflows. From disconnected systems to return chaos and SLA blind spots, the conversation explores how automating manual tasks can shift 3PLs from constant firefighting to proactive execution.

The Manual Work Burden 3PLs Carry

Audrey defines the mission clearly: “Handled is an AI-powered operations platform that helps 3PLs and e-commerce brands eliminate all of the manual, tedious work that happens after a customer clicks buy or places an order.”

Audrey and her co-founder found, through their own experiences, that the post-purchase environment is broken: “We personally had to deal with the pain of what happens after a customer places an order, both working for and running e-comm brands, but then also on the tech side.” That “after buy” window is where complexity multiplies. Many eCommerce brands run 15 different apps. Some use two for customer support and three for returns. Multi-channel sellers log into separate systems for each marketplace. Meanwhile, 3PLs operate inside WMS platforms that focus on fulfillment, not communication.

Audrey explains that the environment becomes fragmented. “Everyone is constantly just switching between systems to try to piece together what’s going on so that they can do something about it.” The burden lands on the 3PL. When customers complain, brands escalate. Visibility gaps create reactive workflows. Instead of planning ahead, operators respond only after problems surface.

From Reactive to Real-Time Visibility

Handled focuses first on visibility. Audrey puts it simply: “Essentially, it’s like two. It comes down to two things. The first is real-time visibility.”

Instead of waiting for brands to flag issues, Handled surfaces shipment delays, exceptions, customs holds, and return defects as they happen. Every shipment lives in a single view. Therefore, automating manual tasks for 3PLs across carrier portals and spreadsheets.

Automation then drives the next step. “We go beyond just letting the 3PLs know that an issue has happened, but we also can then take the next step automatically.” That might mean breaking an order mid-pick when Shopify changes. It could mean automatically creating a reshipment if a package is lost.

Audrey also highlights SLA visibility. She shares an example where a 3PL averaged 95% on-time performance overall but delivered only 70% for a specific brand. That insight creates an early warning before churn happens.

AI as Deterministic Digital Employees

Handled leverages AI in a controlled way. Audrey describes it this way: “I would say it’s like the driving engine behind our platform.” The platform enables quick integration and automates repetitive workflows. But the AI is structured, not unpredictable. “So our, our models are like very deterministic, which means we like tell the AI agent exactly what to do.”

The impact becomes clear in one case. A 3PL processing 15,000 orders per month, handles 10 to 15% of international shipments. An employee spent 10 to 20 minutes per international label due to customs issues. That meant overtime and customer complaints. Automating manual tasks allowed the employee to return to his actual role, accounting.

Audrey also sees future potential in predictive analytics. Monitoring response times and complaint patterns may help 3PLs anticipate brand dissatisfaction before relationships break down.

Key Takeaways on Automating Manual Tasks for 3PLs

• Post-purchase operations automation targets the fragmented systems after checkout.
• Many eCommerce brands operate 15 apps across support, returns, and sales channels.
• Most of the workload of post-purchase operations lands on the 3PL.
• Real-time shipment visibility reduces reactive complaint-driven workflows.
• Automation can break orders, create reshipments, and trigger alerts automatically.
• International labels took 10–20 minutes each before automating manual tasks.
• SLA tracking revealed performance gaps of 95% overall, compared with 70% for one brand.
• Deterministic AI agents eliminate repetitive back-office tasks.