Sherlock Calls
for Datadog + Granola
Datadog monitors every layer of your infrastructure with metrics and traces. Granola captures every meeting as structured, searchable AI notes on macOS. 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, Granola 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 Granola can answer alone. Datadog shows infrastructure events — not how they map to call failures or customer impact. Granola holds what was decided in every meeting — but those decisions are invisible during investigations. 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 + productivity query
2
Connected platforms, 1 Slack question
0
Code changes or webhooks required
The Investigation Gap
What's invisible when you use Datadog + Granola without Sherlock
Each platform shows you its own data. But the questions that matter most live in the gaps between them.
Datadog and Granola each hold half the picture
Datadog shows infrastructure events — not how they map to call failures or customer impact. Granola holds what was decided in every meeting — but those decisions are invisible during investigations. 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. Granola tracks its own time to reconstruct meeting context. 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 Granola, 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 + Granola
Questions that would take hours to answer manually — answered in under 5 seconds from Slack.
- SC“What's the combined activity across Datadog and Granola in the last 7 days?”
- SC“Show me events that touched both Datadog and Granola in the last 24 hours”
- SC“What's our blended cost per outcome across Datadog and Granola this month?”
- SC“Which Datadog sessions had issues that correlate with Granola events this week?”
- SC“Compare performance metrics across Datadog and Granola for the past 30 days”
Beta Setup
Connect Datadog + Granola 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 Granola
Add your Granola credentials. Sherlock indexes all AI meeting notes, decisions, action items, and summaries automatically.
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Ask your first cross-provider question. The game is afoot.
Type any question about your combined Datadog + Granola 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 + Granola
How does Sherlock Calls connect Datadog and Granola data?
- Sherlock uses read-only API access to both platforms simultaneously. When you ask a question, it queries Datadog, Granola 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 Granola?
- 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 + Granola stack?
- You can investigate anything that spans both platforms — alert rate, latency, and service health, decision quality and commitment frequency, 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 Granola 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 Granola and is accessed only during an active investigation.
How long does it take to set up the Datadog + Granola 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 + Granola
We're accepting a select group of beta users to shape the Datadog + Granola combination. Tell us about your stack and we'll reach out personally if you're a fit.
Explore individual integrations