Automating the Enterprise with Foundation Models
Summary: ECLAIR uses multimodal foundation models to automate enterprise workflows end-to-end, replacing brittle RPA by interpreting natural-language workflow descriptions for instant setup. Experiments report 93% workflow-understanding accuracy and 40% zero-shot completion; highlights human-AI validation, monitoring, and self-improvement as core data-management research problems. (summarized by gpt-5-mini on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Michael Wornow
- 2. Avanika Narayan
- 3. Krista Opsahl-Ong
- 4. Quinn McIntyre
- 5. Nigam Shah
- 6. Christopher RĂ©
Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 8,736 | Unveiling Challenges for LLMs in Enterprise Data Engineering | 2026 | VLDB | 4.456315e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 13 of 13 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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| 6,656 | Process Automation as the Foundation for E-Business | 2000 | VLDB | 4.9723035e-05 |
| 3,995 | How Large Language Models Will Disrupt Data Management | 2023 | VLDB | 6.5513237e-05 |
| 517 | Can Foundation Models Wrangle Your Data? | 2023 | VLDB | 0.00021169035 |
| 11,317 | Data Management Opportunities for Foundation Models | 2022 | CIDR | 4.1945683e-05 |
| 8,736 | Unveiling Challenges for LLMs in Enterprise Data Engineering | 2026 | VLDB | 4.456315e-05 |