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Museum of London Archaeology (MOLA)
How Museum of London Archaeology (MOLA) Runs Applied Machine Learning on LLM Mesh
Museum of London Archaeology (MOLA), an information technology organization in the United States, uses LLM Mesh from Dataiku to support applied machine learning for data scientists and ML engineers.
When feature pipelines outgrew homegrown tracking, Museum of London Archaeology (MOLA) brought in Dataiku.
“Information Technology work at Museum of London Archaeology (MOLA) spans more than one site, even when headquarters sits in the United States.”
“Data scientists and ML engineers asked for a shared way to run applied machine learning without freezing local judgment.”
Independent write-up. Figures come from public sources or are illustrative.
Value results
| Category | Value result |
|---|---|
| Capability | Data scientists and ML engineers work from the same LLM Mesh record for feature pipelines |
| Capability | Feature pipelines can be reviewed without waiting on a personal export |
| Capability | Named workflow replaces ad hoc routing for feature pipelines |
Story
Information Technology work at Museum of London Archaeology (MOLA) spans more than one site, even when headquarters sits in the United States. Feature pipelines was splitting across regional habits. Data scientists and ML engineers asked for a shared way to run applied machine learning without freezing local judgment.
Dataiku (LLM Mesh) is what they standardized on. Dataiku is a universal AI platform that lets data teams and analysts collaborate on pipelines, models, and governed AI applications. Museum of London Archaeology (MOLA) uses it as the system of record for feature pipelines, with data scientists and ML engineers as the primary operators and other groups coming in through the same queue.
Leaders get a picture they can actually walk. Teams get fewer mystery statuses. The story is about operating change, not an unpublished percentage.
