Encoder on a frozen backbone
A small modality encoder projects structured events into a frozen LFM2.5-350M; LoRA plus task heads read out decisions.
The four encoder builds behind this pattern are internal demonstrations of the recipe, trained and evaluated on synthetic data. They demonstrate feasibility on this architecture — treat every number as an internal measurement on synthetic distributions.
The recipe
Tabular or event-sequence data (transactions, telematics, claims, security telemetry) is encoded per-field, projected into the backbone's embedding space via inputs_embeds, and decisions are read out by small task heads. The backbone stays frozen; the vertical lives entirely in the encoder + LoRA + heads.
The same shape generalizes across verticals — payments, mobility, claims, and cyber were built from one template with different encoders and head sets.
64 events × features → field embeddings → encoder → inputs_embeds → LFM2.5-350M (frozen) + LoRA → heads: fraud · next-event · risk · …
Recorded runs
This pattern page ships with recorded end-to-end runs rather than public live instances — the live builds sit behind the gated tier where an engineer can frame them properly.