Retell AI adds memory between conversations for voice agents
Retell Memory retains context across repeat contacts. We examine how to test a new-order scenario when a customer changes delivery instructions.
VOICEIP JOURNAL / AUTHOR
Process and analytics writer
A VoiceIP editorial profile. This collection covers business processes, analytics and performance indicators.
Retell Memory retains context across repeat contacts. We examine how to test a new-order scenario when a customer changes delivery instructions.
Historical contributions with their original publication dates and URLs.
By 2027, successful AI adoption in development will depend not on code generation speed, but on integrating AI tools into controlled testing, security, and architectural oversight processes.
Transitioning from experimental ML models to robust enterprise systems using AWS Well-Architected Framework, Google SRE, and 12-Factor App principles.
Balancing software delivery speed and system reliability using DORA metrics, 12-Factor App principles, SRE error budgets, and platform engineering.
How SRE practices, DORA metrics, and engineering discipline help prevent technical debt, while low-code platforms standardize core architecture.
Transitioning to microservices without considering operational complexity creates technical debt. We examine approaches for building stable enterprise systems.
Implementing platform engineering and an Internal Developer Platform (IDP) transforms infrastructure into a product, reducing operational complexity and improving key DORA metrics.
How to combine the flexibility of custom development with the speed of low-code while maintaining engineering discipline, version control, and robust system architecture.
Transforming a successful prototype into a stable enterprise solution using the 12-Factor App, SRE practices, and the Well-Architected Framework.
Finding the balance between rapid off-the-shelf software deployment and custom development freedom, evaluating TCO, and avoiding technical debt traps.
How to combine the flexibility of AI with the rigid logic of BPMN 2.0 and DMN to automate first-line request processing without security risks or operational chaos.
Process Mining methodology reconstructs real task flows using digital footprints, revealing hidden bottlenecks and unauthorized workarounds invisible to management.
How to avoid cementing inefficiencies, replace fragile RPA scenarios with reliable API integrations, and safely implement AI into operational workflows using BPMN and DMN standards.