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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)

Paper ID
13690
Venue
VLDB
Year
2024
Pagerank
5.2422003e-05
Overall Rank
9,654 | 33.77%
DOI
10.14778/3681954.3681964

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{wornow_vldb24,
        title = {{Automating the Enterprise with Foundation Models}},
        author = {Wornow, Michael and Narayan, Avanika and Opsahl-Ong, Krista and McIntyre, Quinn and Shah, Nigam and Ré, Christopher},
        journal = {PVLDB},
        series = {{VLDB} '24},
        volume = {17},
        number = {11},
        pages = {2805--2812},
        doi = {10.14778/3681954.3681964},
        url = {https://doi.org/10.14778/3681954.3681964},
        year = {2024}
}

Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank Citing Paper Year Venue Pagerank
8,906 Unveiling Challenges for LLMs in Enterprise Data Engineering 2026 VLDB 5.3483178e-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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