Bland’s CIO explains why enterprises avoid voice AI and how its self-hosted stack solves it
Juan E. Riojas, Bland’s CIO, outlines the core barriers to enterprise voice AI adoption: trust, control, and latency. His background at Twilio, Rackspace, and Informatica shaped Bland’s self-hosted platform, which owns the entire voice AI stack—from automatic speech recognition (ASR) to large language model (LLM) inference and text-to-speech (TTS)—to eliminate third-party dependencies and ensure…
Key points
- Bland’s self-hosted voice AI stack avoids third-party dependencies to ensure sub-1-second latency and data sovereignty
- FedRAMP 20x Class A certification demonstrates compliance for federal and highly regulated industries
- Canary deployments and real-time monitoring mitigate risks in production AI agents for enterprises
Riojas highlights key challenges like latency orchestration, streaming synchronization, and GPU scheduling, which Bland addresses with custom inference engines and low-latency pipelines. The company’s FedRAMP 20x Class A certification—earned by demonstrating end-to-end data control and compliance—positions it as a leader for regulated industries. Bland’s architecture supports deployments from private cloud VPCs to air-gapped on-premises setups, balancing latency, scaling, and compliance needs. The platform also emphasizes disciplined release practices, including canary deployments and real-time monitoring, to mitigate risks in customer-facing AI agents.
Juan E. Riojas, Chief Information Officer at Bland
Unite.AI · 15 October 2026
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