AfterShip has launched AfterShip Intelligence for post-purchase e-commerce operations. The platform brings agentic automation and predictive intelligence to tracking, returns, and shipping. AfterShip supports branded customer experiences for more than 20,000 brands globally. Since 2012, the company has powered shipping, tracking, and returns across e-commerce. Over the years, AfterShip built one of the industry’s largest post-purchase datasets. Its proprietary data covers 14 years of shipping activity and more than 11 billion shipments.
The dataset also includes nearly 110 billion delivery checkpoints and more than 1,400 carriers. AfterShip has standardized this information through a single operating engine. That data now supports AfterShip Intelligence and its proprietary domain models. These models focus on delivery prediction, exception forecasting, and return intelligence.
It’s not a platform built on repurposed general AI for retail. Instead AfterShip created models around post-purchase operations. That allows retailers to automate operational tasks and detect problems earlier. They can also solve problems before customers have them. The platform also enables brands to turn every order into an opportunity. It helps protect customer relationships, while supporting revenue growth.
“For years, post-purchase has been treated as a cost center, but it’s one of the most valuable moments in the customer journey,” said Teddy Chan, Founder and CEO at AfterShip. “As customer acquisition gets more expensive, brands can’t afford to treat tracking and returns as back-office operations. We built AfterShip Intelligence to automate the work that slows teams down, predict issues before customers feel them, and give operators AI they can trust because they stay in control.”
Brands Report Faster Post-Purchase Operations
Launch partners Dr. Squatch and Naked Wardrobe have already reported measurable results. Both brands use AfterShip Intelligence across important post-purchase workflows. Dr. Squatch deployed AfterShip Agent for exception handling. Since then, the brand improved exception resolution time by more than 58%. It also reduced its most frequent “where is my order” tickets by 25%. Meanwhile, positive sentiment increased by 42% on agent-initiated conversations. The brand also adopted AfterShip’s predictive delivery tools within weeks. Its previous provider required more than four months for a similar deployment.
The solution achieved 94% on-time estimated delivery accuracy for 99.98% of the orders. This performance gives teams better insight into what outcomes are to be expected of delivery. AfterShip Agent helps Naked Wardrobe manage RMA reviews. Return reviews used to take 5 to 10 minutes to complete. And now, those reviews take about 40% less time. Risk Assessment and Customer History also appear in the workflow itself. The agent can recognize RMAs that are safe to approve. This allows 15% to 20% of RMAs to be processed without any manual review. Such automation is a big efficiency gain for a small customer service team.
AfterShip Agent Automates Key Workflows
AfterShip Agent is the core of the company’s new platform. This is the first AI agent AfterShip has built for post-purchase operations. The Agent starts with Exception Handling and Return Merchandise Authorization (RMA) Review. It automatically detects shipment issues and collects the right order context. Then it suggests appropriate resolutions and performs the necessary tasks. Operators today jump between three to five disconnected systems to process one order.
That operational complexity is what AfterShip Agent is trying to reduce. You can still explain what you do and have it reviewed. Plus, there’s still human sign-off on financial or customer-facing decisions. This gives operators more control over automated workflows. The wider platform also deploys AI throughout the post-purchase journey. Predictive Estimated Delivery Dates Use carrier data and real-time shipment intelligence.
The system can also flag at-risk orders before traditional tracking signals appear. In addition, it provides personalized product recommendations for customers. AI-powered exchange recommendations can further help brands retain revenue. These recommendations provide alternatives instead of immediately directing customers toward refunds.
AfterShip Connects AI With Commerce Tools
The growth of agentic commerce has largely focused on product discovery and purchasing. AfterShip is expanding that conversation into the post-purchase experience. The company supports agent-first Application Programming Interfaces (APIs), Model Context Protocol (MCP) servers, and one-click connectors.
These integrations allow merchants to bring post-purchase intelligence into existing AI tools. Supported platforms include Shopify Sidekick, Claude, and ChatGPT.
“As AI continues to reshape how brands operate, we see a real opportunity to apply that intelligence to the moments that happen after a purchase,” said Joan Park, Senior Customer Experience Analyst at Dr. Squatch. “AfterShip Intelligence gives our team the context and automation to resolve delivery issues more efficiently, while keeping our focus on delivering a great customer experience. It’s an important step toward making post-purchase a more intelligent part of the customer journey.”
Naked Wardrobe also highlighted the importance of practical automation. The company sees returns as an important part of its overall customer experience.
“Returns are an important part of the customer experience, and we want our team spending its time where human judgment adds the most value,” said Jackie Avila, Head of Customer Service at Naked Wardrobe. “AfterShip Intelligence features help us automate the straightforward decisions while giving our team the context they need when a return requires a closer look. As AI becomes a bigger part of retail operations, this is the kind of practical automation that can make a meaningful difference for both teams and customers.”
With AfterShip Intelligence, AfterShip is positioning post-purchase operations as a growth opportunity. The platform combines predictive analytics, AI automation, and shipping intelligence.
It also gives e-commerce teams tools to improve efficiency and customer experiences. At the same time, brands can protect revenue throughout the post-purchase journey.
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News Source: Businesswire.com
