DataExplorer
- Company
- DoorDash
- Approach type
- Agent
- Work
- Data
- Human involvement
- Unknown
- Invocation
- Interactive
- Deployment stage
- Deployed
- Evidence strength
- Detailed primary
- Entry reviewed
Purpose
DataExplorer helps DoorDash employees explore internal data by selecting tables and generating grounded starter SQL.
How it works
Representative workflow: employee data question → grounded starter SQL. Research details
The agent calls DescribeTable to gather candidate tables and schema context.
It proposes relevant tables and starter SQL grounded in their schema.
Where people stay involved
Each scope pairs its normal attention boundary with supporting evidence. See the supervision definitions for the level mapping and limits.
Unreported: The source does not establish the required human review boundary.
employee data question → grounded starter SQL
Unknown · Level unknown
Catalog interpretation: Unclassified for employee data question → grounded starter SQL; human attention boundary: unknown.
Observed in 11 November 2025
Implementation details
- Model
- Not reportedNot documented for this subject in the reviewed source.
- Harness
- Runs on DoorDash’s analytics AI Marketplace.
- Sandbox
- Not reportedNot documented for this subject in the reviewed source.
- Tool access
- DescribeTable and schema-aware SQL tools.
- Knowledge
- Not reportedNot documented for this subject in the reviewed source.
- Context management
- Not reportedNot documented for this subject in the reviewed source.
- Credentials
- Not reportedNot documented for this subject in the reviewed source.
- Interfaces
- Not reportedNot documented for this subject in the reviewed source.
Validation and failure handling
The platform applies SQL checks and EXPLAIN validation with feedback for correction.
Reported observations
The catalog records what the sources report, with the scope and the denominator of every figure. A qualification below limits the figure it sits under.
Unreported: The reviewed source does not document this for the named subject.
Lessons
Unreported: The reviewed source does not document this for the named subject.
Sources and research details
Citations link to the original publisher. Each source also keeps a preserved copy in the repository, so a changed or removed page stays checkable.
- Beyond single agents: DoorDash's collaborative AI ecosystemhttps://careersatdoordash.com/blog/beyond-single-agents-doordash-building-collaborative-ai-ecosystem/
Question coverage and scope
- purpose
- Reported
- workflow
- Reported
- human involvement
- Unreported: The source does not establish the required human review boundary.
- implementation
- Reported
- validation
- Reported
- observations
- Unreported: The reviewed source does not document this for the named subject.
- lessons
- Unreported: The reviewed source does not document this for the named subject.
Research details for every claim on this page
- Summary
- Statement type
- Fact
- Provenance
- Reported
- Confidence
- High
- Confidence reason
- A linked first-party source states the claim.
- SupportsBeyond single agents: DoorDash's collaborative AI ecosystemIntroducing dynamic reasoning with agents, Figure 4; Taking a high-level look
- Harness
- Statement type
- Fact
- Provenance
- Reported
- Confidence
- High
- Confidence reason
- A linked first-party source states the claim.
- SupportsBeyond single agents: DoorDash's collaborative AI ecosystemIntroducing dynamic reasoning with agents, Figure 4; Taking a high-level look
- Tool access
- Statement type
- Fact
- Provenance
- Reported
- Confidence
- High
- Confidence reason
- A linked first-party source states the claim.
- SupportsBeyond single agents: DoorDash's collaborative AI ecosystemIntroducing dynamic reasoning with agents, Figure 4; Taking a high-level look
- Inspect schema
- Statement type
- Fact
- Provenance
- Reported
- Confidence
- High
- Confidence reason
- A linked first-party source states the claim.
- SupportsBeyond single agents: DoorDash's collaborative AI ecosystemIntroducing dynamic reasoning with agents, Figure 4; Taking a high-level look
- Generate SQL
- Statement type
- Fact
- Provenance
- Reported
- Confidence
- High
- Confidence reason
- A linked first-party source states the claim.
- SupportsBeyond single agents: DoorDash's collaborative AI ecosystemIntroducing dynamic reasoning with agents, Figure 4; Taking a high-level look
- Validate queries
- Statement type
- Fact
- Provenance
- Reported
- Confidence
- High
- Confidence reason
- A linked first-party source states the claim.
- SupportsBeyond single agents: DoorDash's collaborative AI ecosystemIntroducing dynamic reasoning with agents, Figure 4; Taking a high-level look
- Operating model assessment
- Statement type
- Inference
- Provenance
- Catalog judgment
- Confidence
- Unverified
- Confidence reason
- The source describes DataExplorer and its work, but does not establish whether a person must approve or inspect each successful output.
- Observation date
- 2025-11-11
- SupportsBeyond single agents: DoorDash's collaborative AI ecosystemIntroducing dynamic reasoning with agents, Figure 4; Taking a high-level look