The client is a U.S.-based technology company that designs and sells consumer-grade 3D laser printers. Operating in the desktop manufacturing space, the company serves a diverse global user base of educators, hobbyists, small businesses, and makers.
Known for its sleek hardware, intuitive software, and strong community focus, the client offers end-to-end customer service through digital support channels, including email, web forms, and help center articles. As adoption grew rapidly, the support team began handling thousands of inbound queries each month, covering topics like product setup, warranty coverage, order tracking, and returns.
To maintain its high standard of service without increasing team size, the client sought a solution that could deliver instant, reliable, and brand-consistent responses without compromising accuracy or oversight.
The client’s support team was spending too much time replying to repetitive queries — ranging from shipping delays to basic troubleshooting. Manual triage, inconsistent responses, and agent overload were affecting turnaround times and customer satisfaction.
The company reached out to Flatworld.ai to set up an automated system that could:
Inputs Provided by the Client
Deliverables Requested
Timeline for the Project
The requirement gathering and proof-of-concept phase took two months, followed by three months of weekly releases to cover all scenarios within Telena’s scope.
The Telena email automation solution was delivered through a well-orchestrated, collaborative process. With detailed planning, continuous feedback, and iterative development, the Flatworld.ai team provided consistent results across every phase of the project lifecycle.
Flatworld.ai began with a focused scoping phase that prioritized use cases based on their impact and mapped them to weekly release timelines. Input data was validated early to avoid rework, while historical ticket analysis and FAQ reviews helped identify edge cases and exceptions. The scope evolved with the client’s shifting priorities through weekly reviews. End-to-end flows were mapped and refined, and communication was tightly managed through daily updates, meeting notes, and a centralized tracker that flagged dependencies and blockers.
The development phase focused on building logic modules in a modular, rule-based format. These modules were iteratively calibrated to meet the client’s latest requirements while strictly adhering to business rules. Documentation, such as process maps and detailed user stories, was created for each feature, providing all team members, from development to QA and support, with a clear understanding of their responsibilities and expectations. When needed, new methods were introduced to optimize performance, including streamlined logic structures to handle complex queries more efficiently.
Coordinating across time zones made collaboration and approvals more complex. Transitioning from manual to automated responses also required careful oversight. Despite limited time and resources, robust QA cycles were maintained. Clear documentation, frequent team syncs, and focused backlog management helped simplify execution and maintain delivery speed.
Testing played a central role in maintaining system quality throughout rapid development cycles. Due to frequent logic updates and expanding scenarios, regression testing was performed daily to ensure stable performance. Flatworld shared test cases with the client via simple Jira cards, offering complete transparency into what was being tested and making approvals faster and more efficient. Separate QA and UAT environments were maintained to ensure clean test runs, preventing overlap and maintaining consistency across releases.
Go-lives were preceded by final test runs conducted during client working hours. Real-time support was provided during live operations with daily shift check-ins. As the system proved stable, the client began independently managing the platform with minimal assistance from Flatworld.ai. A custom dashboard offered complete performance visibility, supported by regular reporting on trends and system accuracy.
Integrations with platforms like Zendesk, Chargebee, and Shopify required multiple rounds of access approvals. Due to restricted API privileges, Flatworld.ai engineered a backend-mimicking system to deliver the required functionality without admin access. Detailed logs and reports were shared for full transparency and auditability.
While the system was deployed on time, the team encountered a few key hurdles.
The Telena deployment became a reference success within the client’s support ecosystem. Over the course of five months, Flatworld.ai delivered:
Flatworld.ai helped the client remove friction from a high-volume part of their support process — without losing human judgment where it was needed. Agents now spend less time rewriting the same answers and more time solving problems that require attention.
The client retained full control over brand voice and service quality while dramatically reducing time spent on repetitive support tasks. Ready to reduce your email backlog and improve your team’s capacity? Let’s talk about how Flatworld.ai can help you automate.
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