Sherlock Calls vs Grafana
Grafana is the world's most popular open-source observability stack — with Grafana Cloud, Loki, Tempo, and Mimir used by millions of engineers to visualize and alert on any data source. Sherlock Calls is purpose-built for the operational layer Grafana dashboards don't reach: investigating production voice calls from Twilio, ElevenLabs, Vapi, and 12+ providers in plain English, from Slack.
TL;DR — The short answer
- 1
Grafana is the leading open-source observability platform — powerful for engineering teams who need flexible dashboards, alerting, and log/trace/metrics correlation across any data source.
- 2
Sherlock Calls is purpose-built for voice operations: investigating real production call failures, pulling transcripts, and correlating costs and errors across 15+ voice providers from Slack — zero setup beyond API keys.
- 3
If your team runs voice AI on Twilio, ElevenLabs, Vapi, or Genesys, Sherlock fills the operational gap Grafana dashboards were never designed to cover.
Understanding both tools
Sherlock Calls
AI-powered voice call investigation
Sherlock Calls is a Slack-native AI investigator purpose-built for voice operations teams. Connect your existing providers — Twilio, ElevenLabs, Vapi, Genesys, and 12 more — and ask questions about your calls in plain English. Sherlock autonomously gathers data across all connected services, correlates events, and delivers a sourced answer in under 5 seconds. No new dashboards. No SDK. No code changes.
- Works inside Slack — no new UI to learn
- Connects to 15+ voice providers in minutes
- Investigates calls autonomously with AI
- Free tier — 100 credits per workspace
Grafana
The open and composable observability and data visualization platform
Grafana is an open-source observability platform that provides dashboards, alerting, and data visualization across any data source — with Grafana Cloud extending that capability with managed Loki (logs), Tempo (traces), Mimir (metrics), and a growing AI/ML observability layer.
- Open-source dashboards and alerting with 300+ data source plugins — Prometheus, Loki, Tempo, Elasticsearch, PostgreSQL, and more — unified in a single visualization layer
- Grafana Cloud: fully managed observability with Loki (logs), Tempo (distributed traces), Mimir (metrics), and Grafana OnCall for incident management
- AI observability: Grafana AI/ML Observability module (in active development) for tracking LLM performance, cost, and quality within the Grafana ecosystem
- Grafana Incident and Sift: AI-assisted incident investigation that surfaces correlated signals from logs, traces, and metrics to accelerate root cause analysis
Feature comparison — General APM & DevOps
Sherlock Calls vs Grafana & peers
All tools in the General APM & DevOps category — so you can compare both head-to-head and within the landscape.
| Feature | SherlockCalls | Grafanathis page | Datadog LLM Observability | New Relic | Sentry |
|---|---|---|---|---|---|
| AI call investigation | |||||
| AI agent & LLM tracing | |||||
| AI governance & compliance | |||||
| Offline LLM evaluation | |||||
| Provider integrations | 15+ (all voice) | 300+ (~2 voice) | 600+ (~5 voice) | 700+ (~4 voice) | ~100 (~3 voice) |
| Cross-provider correlation | |||||
| Natural language queries | |||||
| Zero-code setup | |||||
| Per-call cost tracking | |||||
| Free tier available |
Scroll horizontally to compare all tools →
Key differences
Why teams switch from Grafana to Sherlock
Voice Call Investigation vs Dashboard Visualization
Sherlock Calls
Sherlock investigates specific voice call events — dropped calls, ElevenLabs latency spikes, Twilio billing anomalies, cross-provider transcript gaps — in plain English from Slack, with answers in under 5 seconds and no dashboard configuration required.
Grafana
Grafana is a powerful visualization layer: it can display any metric or log you send to it. But building dashboards that surface call-level voice intelligence — specific transcript failures, per-call costs across Twilio and ElevenLabs, correlated provider timelines — requires significant engineering effort to instrument, ingest, and visualize.
Plain English Q&A vs PromQL and LogQL
Sherlock Calls
Ask Sherlock 'Why did our voice calls fail last night?' in Slack and get a sourced, multi-provider answer in under 5 seconds — no query language, no panel configuration, no on-call engineer required.
Grafana
Grafana's natural language features (via Grafana AI and Sift) help engineers explore dashboards conversationally, but the underlying workflow still requires PromQL, LogQL, or TraceQL for precise data retrieval — query languages designed for engineers, not voice operations managers who need instant answers.
Minutes to Value vs Days of Setup
Sherlock Calls
Sherlock connects to your Twilio, ElevenLabs, Vapi, Retell, Genesys, Amazon Connect, and HubSpot accounts via API key — no SDK, no data pipeline, no schema design. Operational in under 2 minutes.
Grafana
Grafana requires a data pipeline: your voice providers must send telemetry to Grafana via agents, exporters, or custom instrumentation. Building and maintaining dashboards for voice call data across multiple providers is a multi-day engineering project — and dashboards go stale as providers evolve.
Which tool is right for you?
When to choose Sherlock vs Grafana
Choose Sherlock Calls if…
- Your team operates voice AI in production and needs to investigate specific call failures without building Grafana dashboards or writing PromQL
- You want cross-provider correlation across Twilio, ElevenLabs, HubSpot, and your CRM with no data pipeline setup
- Your operations or support team needs call intelligence in Slack without Grafana expertise
- You need per-call cost breakdowns and transcript analysis on demand across your voice provider stack
Consider Grafana if…
- Your engineering team needs flexible, open-source dashboards and alerting across any data source — infrastructure metrics, logs, traces, and custom telemetry — with full control over the visualization layer
- You already run a Grafana stack and want to extend it with AI observability via Grafana Cloud rather than adopting a separate tool for voice call intelligence
Pricing
Cost comparison
Sherlock Calls
Free to start
100 credits per Slack workspace. Team plans from $50/month. No credit card required to start.
- Free tier — 100 credits/workspace
- Team: $50–$5,000/month (usage-based)
- Enterprise: custom pricing
- No sales call required to start
- Cancel anytime
Grafana
Open-source free + Grafana Cloud free tier
Grafana OSS is fully open-source and free to self-host with no feature restrictions. Grafana Cloud offers a free tier with 10,000 active metrics, 50 GB of logs, 50 GB of traces, and 500 VUh of k6 testing per month. Pro plans start at $8/user/month with pay-as-you-go data pricing.
* Pricing sourced from public information. Contact Grafana for current rates.
FAQ
Frequently asked questions
What is Grafana used for?
Grafana is an open-source observability and data visualization platform that connects to 300+ data sources — Prometheus, Loki, Tempo, Elasticsearch, PostgreSQL, and more — to provide unified dashboards, alerting, and log/trace/metrics correlation. It is designed for engineering and DevOps teams, not for voice call investigation or operational Q&A from Slack.
Can Grafana investigate voice calls from Twilio or ElevenLabs?
Grafana can visualize any data you send to it — including telephony metrics if you build a pipeline to ingest them. However, it has no native integrations with Twilio, ElevenLabs, Vapi, or Genesys, and does not natively correlate call transcripts, per-call costs, or cross-provider voice events. Sherlock Calls provides native integrations with 15+ voice platforms — no code or pipeline required.
Is Sherlock Calls a Grafana alternative?
They solve problems at different layers. Grafana is right for engineering teams who need flexible open-source dashboards and alerting across any data source. Sherlock Calls is right for voice operations teams who need to investigate production voice calls and get instant answers from their telephony stack — without building dashboards, writing PromQL, or maintaining a data pipeline.
How do I migrate from Grafana to Sherlock Calls?
No migration needed — Sherlock and Grafana serve different teams with different workflows. Sherlock complements Grafana: if you use Grafana to monitor your voice infrastructure, Sherlock adds the call-level intelligence layer — specific transcript failures, cross-provider cost correlation, and natural language investigation — that Grafana dashboards don't expose without significant custom engineering.
Does Sherlock Calls replace Grafana?
No. Grafana is the right choice for engineering teams who need flexible open-source observability, dashboards, and alerting across any data source. Sherlock Calls is the right choice for voice operations teams who need to investigate voice calls and get instant answers from their telephony stack — without writing PromQL or building a data pipeline.
Ready to investigate your calls the smarter way?
Join teams who left Grafana for an AI-native, voice-first investigation tool. Connect in 2 minutes, no credit card required.
No credit card required · 100 free credits · Setup in 2 minutes