Blog
Practical guides, tutorials, and field notes for teams running voice AI in production. No fluff, no slides — just what works.
RSS feedWeek 3 of building Sherlock Calls: AES-256-GCM credential encryption at rest, ClickHouse + PostgreSQL integrations, 4 free voice AI tools, transparent per-message token billing, and a real-time admin activity monitor.
Voice AI costs spiral fast across ElevenLabs, Vapi, and Twilio. This practical guide covers the 5 biggest cost traps and exactly how to fix each one.
Learn how to set up cost monitoring for voice operations across Twilio, ElevenLabs, and Vapi — with practical alerts that catch spend anomalies before the invoice arrives.
Twilio per-minute fees are just the surface. Here is how compounded telephony, TTS, and orchestration costs silently inflate your voice AI bill — and how to audit and cut them.
Week 2 of building Sherlock Calls: the interactive demo shipped, 9 viral growth loops designed, Slack responses made production-grade with full thread history, and 300+ SEO combination pages generated.
Industry benchmarks for voice AI call failure rates across Twilio, ElevenLabs, and Vapi — plus how to measure your own failure rate correctly and what to do when it's too high.
A practical playbook for diagnosing Twilio call failures in production: error codes, silent failures, webhook debugging, and cross-provider correlation with ElevenLabs and Vapi.
A practical guide to minimizing ElevenLabs text-to-speech latency in production voice AI — model selection, streaming optimization, connection pre-warming, and Twilio silence threshold tuning.
2025 was the year voice AI moved from proof-of-concept to production operations. Here is what the year taught operators about running these systems at scale.
A step-by-step guide to diagnosing failed or poor-quality Vapi calls — from reading Vapi logs, to identifying handoff failures, to correlating against your downstream systems.
How high-performing engineering teams use Slack as their incident response command center — the patterns, workflows, and tools that work, and the anti-patterns to avoid.
What we shipped in the first week after Sherlock Calls launched: 9 provider integrations, Stripe live mode, competitor comparison pages, GDPR compliance, and the interactive demo in progress. The full evidence file.
A technical guide to reducing ElevenLabs latency in production voice AI deployments — from understanding the latency breakdown to configuration changes that reduce response time by 40–70%.
A practical guide to webhook failure detection and recovery for voice AI teams — why call data silently disappears, how to detect it, and how to build a reliable webhook pipeline.
A complete guide to debugging Vapi webhook failures — delivery timeouts, retry patterns, silent failures, and how to correlate webhook events with call outcomes.
Ad-hoc debugging catches problems after customers have experienced them. A three-layer quality framework catches them before. Here is what each layer monitors and why.
Practical strategies to reduce voice AI infrastructure costs — ElevenLabs plan optimization, failed call detection, Twilio per-minute rate reduction, and cost-per-successful-call tracking.
Why time-to-first-byte is the most important metric in voice AI, how to measure it across Twilio + ElevenLabs, and optimization strategies that cut TTFB by 60%.
The case file on how we built Sherlock Calls: an AI that investigates production voice call failures in Slack. Multi-provider correlation, Anthropic AI, and a Slack-native UX — launched in one sprint.
Voice AI systems that perform perfectly in staging fail in production for reasons that have nothing to do with model quality. Here is what actually breaks and how to see it coming.
Voice AI costs compound across multiple metered providers and are notoriously hard to predict. Here is how to build a cost monitoring practice that catches overruns before they become crises.
Voice AI incidents are team events, not solo debugging sessions. The operations tool that lives where the team already works will always outperform one that requires a context switch.
ElevenLabs voice AI agents fail for well-defined reasons — latency spikes, character budget exhaustion, audio codec mismatches, and webhook timeouts. Here is how to find the root cause in under 60 seconds.
Dropped calls in voice AI production environments have five primary root causes, each requiring a distinct investigation path. Here is the framework for determining which one you have.
Call volume and aggregate success rate are the metrics that are easy to collect and useless for diagnosing operational problems. Here are the five that actually matter.
Most teams running AI voice agents in production are flying blind. Here is exactly why traditional dashboards fail voice AI, what real observability looks like, and how to get there without a six-month project.
ElevenLabs TTS latency spikes above 800ms trigger Twilio silence timeouts in a significant share of deployments. How to diagnose, attribute, and fix the failure most teams never see.
Direct telephony costs are the visible tip of the iceberg. The true cost of a failed voice AI call multiplies through churn, support overhead, and eroded brand trust.
A voice AI operation without observability is not an operation — it is a gamble. Ten questions your team must be able to answer in under 30 seconds, without a dashboard.
Voice AI incidents span three or more providers simultaneously — yet most teams can only investigate one at a time. Here is what that gap actually costs.