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An AI call detective in Slack. Ask about your calls in plain English — it investigates Twilio, ElevenLabs & Genesys among many other aservices and answers in seconds. Slack-native forensics for Twilio + ElevenLabs call failures
Website, pricing, platforms and company facts side by side.
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| Website | launchrender.com | usesherlock.ai |
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| Company | — | Startup from Spain · 1 - 9 employees · 2026 |
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In their own words, as submitted to SaaSHub.


No description of LaunchRender yet.
Sherlock Calls investigates failed voice AI calls and posts the findings in Slack: a correlated cross-provider timeline, root cause with evidence, and first checks in triage order — giving voice AI observability to telephony engineers and on-call SREs without new dashboards. When a Twilio,...
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As answered by people managing LaunchRender and useSherlock.ai.
useSherlock.ai's answer:
Sherlock Calls is the only tool that correlates voice AI call events across multiple providers (Twilio, ElevenLabs, Vapi, Retell AI, etc.) into a single incident case file posted in Slack. Most observability tools show dashboards. Sherlock answers specific questions like why did this call fail? The output is a Slack thread with a timestamped cross-provider timeline, root cause with evidence, troubleshooting options, and first checks in triage order, not another screen to monitor.
useSherlock.ai's answer:
Generic APM tools like Datadog and New Relic were not built for voice AI stacks. They don't understand the relationship between Twilio telephony events and ElevenLabs TTS behavior, or how webhook delivery timing affects call outcomes. Sherlock is purpose-built for cross-provider voice call correlation. Setup is OAuth-only. 60 seconds, no code changes, no agent installation.
useSherlock.ai's answer:
Engineering teams running voice AI in production: telephony engineers, on-call SREs, voice AI operators, and technical founders whose product relies on AI phone agents built on Twilio, Genesys, ElevenLabs, Vapi, or Retell AI, among others.
useSherlock.ai's answer:
Built by Borja, Jorge and Jose after years working in the voice AI and telephony space. Every call failure investigation followed the same pattern: open the Twilio console, open the ElevenLabs dashboard, pull webhook logs, reconcile timestamps manually, guess at the root cause. Two to three hours per incident. They kept asking why no tool just answered the question. When they looked and found nothing purpose-built for voice AI stacks, they built it themselves.
useSherlock.ai's answer:
Next.js, TypeScript, Supabase (PostgreSQL), All major LLMs, Slack API, Stripe, Vercel, Resend, Supabase
useSherlock.ai's answer:
We are our own first clients and we are seeking other like-minded individuals and teams facing the same problems that could try our product and provide us with some feedback.
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