Synthflow AI has introduced a new framework designed to address one of the most persistent challenges facing organizations deploying advanced conversational technology at scale. The company announced the launch of the BELL Framework, an OpenAI powered system built to reduce failure risk and improve reliability in enterprise voice AI deployments. The framework consolidates every phase of building, testing, launching, and optimizing AI voice agents into a structured lifecycle intended to help enterprises deploy automation with greater confidence and consistency.
The launch comes as businesses across healthcare, insurance, finance, and customer operations accelerate investments in automated call handling to reduce costs and relieve pressure on contact center capacity. Synthflow AI argues that despite rapid advances in large language models, the primary barrier to production success is not model quality but operational complexity. Voice AI systems often break due to issues in routing, latency, testing gaps, compliance, and unpredictable handoffs between AI and human agents. The company says BELL, which stands for Build, Evaluate, Launch, Learn, is designed to eliminate these weak points by integrating control and measurement across the entire lifecycle.
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“Enterprises do not need more guesswork, they need guarantees,” said Hakob Astabatsyan, Co founder and CEO of Synthflow AI. “BELL ensures your voice agents behave as expected before customers ever hear them. It is the difference between hoping your AI works and knowing it will perform on every call.”
Synthflow AI’s platform has already supported more than sixty five million calls across more than one thousand active enterprise deployments, providing the foundation for the BELL rollout. Each phase introduces capabilities that address common production failure points. Teams can design logically structured agent behavior through visual flow tools, run large scale testing simulations that score accuracy and completion, launch agents on Synthflow’s proprietary telephony infrastructure rather than relying on third party vendors, and analyze real calls through granular reporting and automated quality assurance. The company reports sub one hundred millisecond latency and 99.9 percent uptime across its network.
“Most voice AI dies in production because teams cannot control the layers that define performance,” said Sassun Mirzakhan Saky, Co Founder and CTO of Synthflow AI. “By owning the telephony, testing, and orchestration layers, we have removed that uncertainty. BELL makes success repeatable.”
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Synthflow uses multiple OpenAI models including GPT 4.1, GPT 5, and GPT 5.1 depending on the reasoning requirements of the task. Eva Spannagl, Head of Startups, DACH, at OpenAI, said the partnership demonstrates what is possible when real time production systems are built on top of frontier models. “Our frontier AI models and developer tools help customers like Synthflow create enterprise grade, real time systems. Synthflow is a great example of how to build on our models to create reliable, production ready outcomes from day one.”
The company says the no code platform allows enterprises to deploy robust voice automation in weeks rather than months while maintaining compliance with SOC 2, HIPAA, and GDPR requirements. As automated calling grows central to modern customer support and operational efficiency, the ability to ensure predictable outcomes may determine which companies gain scalable advantage.
With rising expectations around reliability, speed, and compliance, Synthflow AI is positioning the BELL framework as a foundation for the next stage of enterprise voice AI, enabling organizations to move from experimentation to trusted production environments that withstand real world operational demands.
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