Sherlock Calls
for Datadog + Vapi
Datadog monitors every layer of your infrastructure with metrics and traces. Vapi runs your AI voice agents on any telephony stack. When you need to investigate across both, the evidence is split between two dashboards neither of which knows the other exists. Sherlock Calls bridges them — no code, no exports, no manual joins. Ask once from Slack and get a sourced answer in under 5 seconds.
TL;DR — What beta users get access to
- 1
Sherlock Calls connects to Datadog, Vapi simultaneously — read-only, no code changes, no webhooks — and lets you query both with a single Slack message.
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Ask questions that neither Datadog nor Vapi can answer alone. Datadog shows infrastructure events — not how they map to call failures or customer impact. Vapi shows agent sessions — not how they map to telephony errors or CRM results. Sherlock deduces the complete picture from both.
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No dashboard switching, no manual joins, no fog of uncertainty — ask in Slack and receive a sourced answer with evidence from every connected provider in under 5 seconds. The game is afoot.
<5s
Answer to any observability + voice AI query
2
Connected platforms, 1 Slack question
0
Code changes or webhooks required
The Investigation Gap
What's invisible when you use Datadog + Vapi without Sherlock
Each platform shows you its own data. But the questions that matter most live in the gaps between them.
Datadog and Vapi each hold half the picture
Datadog shows infrastructure events — not how they map to call failures or customer impact. Vapi shows agent sessions — not how they map to telephony errors or CRM results. Without correlating both, your team sees two incomplete views of the same underlying reality — and every investigation stops at the boundary between systems.
Cross-platform cost and performance remain invisible
Datadog tracks its own infrastructure operational spend. Vapi tracks its own agent compute runtime cost. Your true cost per outcome — and the performance of each component in your combined stack — requires data from both, but neither platform shows you that unified picture.
Critical events disappear at the boundary between systems
When a session, contact, or signal moves between Datadog and Vapi, the transition is recorded with different identifiers in each system. Tracing what happens across the full journey requires a manual join that takes hours you don't have.
Cross-Provider Questions
What teams ask Sherlock about Datadog + Vapi
Questions that would take hours to answer manually — answered in under 5 seconds from Slack.
- SC“What's the combined activity across Datadog and Vapi in the last 7 days?”
- SC“Show me events that touched both Datadog and Vapi in the last 24 hours”
- SC“What's our blended cost per outcome across Datadog and Vapi this month?”
- SC“Which Datadog sessions had issues that correlate with Vapi events this week?”
- SC“Compare performance metrics across Datadog and Vapi for the past 30 days”
Beta Setup
Connect Datadog + Vapi to Sherlock in 2 minutes
No code, no webhooks, no new dashboards. Beta users get direct onboarding support.
- 1
Connect Datadog
Add your Datadog credentials to Sherlock Calls. Read-only access — no code changes, no webhooks, no Datadog configuration required.
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Connect Vapi
Add your Vapi credentials. Sherlock indexes all AI agent sessions, call transcripts, and tool call logs automatically.
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Ask your first cross-provider question. The game is afoot.
Type any question about your combined Datadog + Vapi stack in Slack. Sherlock queries all connected platforms in parallel, correlates the evidence, and returns a sourced answer in under 5 seconds.
FAQ
Common questions about Sherlock + Datadog + Vapi
How does Sherlock Calls connect Datadog and Vapi data?
- Sherlock uses read-only API access to both platforms simultaneously. When you ask a question, it queries Datadog, Vapi in parallel, correlates the results by timestamp and shared identifiers, and produces a single sourced answer — the same way a good detective correlates evidence from multiple witnesses.
Do I need to set up any data pipelines between Datadog and Vapi?
- No. Sherlock Calls is entirely pull-based — it queries both APIs on demand when you ask a question. There are no webhooks, no ETL pipelines, no data warehouses, and no code changes required in any of the connected platforms.
What kinds of questions can I ask about my Datadog + Vapi stack?
- You can investigate anything that spans both platforms — alert rate, latency, and service health, conversation success rate and latency, cross-platform costs, handoff patterns, and performance comparisons. Sherlock translates your plain-English question into the right API calls and returns the deduced answer.
Is my Datadog and Vapi data stored by Sherlock?
- No. Sherlock Calls queries your data in real time and returns results directly to Slack — nothing is stored, indexed, or replicated in any Sherlock database. All data remains in Datadog and Vapi and is accessed only during an active investigation.
How long does it take to set up the Datadog + Vapi integration?
- Elementary — typically under 5 minutes total. Connect each platform with read-only credentials, install the Sherlock Calls Slack app, and ask your first question. No engineering, no dashboards, no onboarding calls required.
Apply for early access to Sherlock + Datadog + Vapi
We're accepting a select group of beta users to shape the Datadog + Vapi combination. Tell us about your stack and we'll reach out personally if you're a fit.
Explore individual integrations