tidytext
Finished, widely taught, and shipping roxygen fixes.
A side-by-side editorial comparison of AgencyAnalytics and mlr3cluster — release velocity, themes, recent moves, and the top alternatives to consider.
Reporting features now exist mainly to feed the AI layer sitting on top of them.
AgencyAnalytics is shipping steadily across two tracks. The visible one is reporting ergonomics for agencies managing many clients: regex and contains filtering on custom metrics, client tags applied in bulk, and a Shares tab exposing every way a report has been sent. The second, and the one the roadmap language keeps pointing at, is AgencyAI — which gained saved reusable Skills in August, while the client Data tab was consolidated in July explicitly to give those answers more context to draw on.
mlr3cluster went from a handful of clusterers to covering the field
mlr3cluster supplies clustering learners to the mlr3 framework. Over three releases it added roughly a dozen learners — CLARA, k-prototypes, spectral, then a batch of nine covering finite mixtures, spherical and directional families, self-organising maps, spatio-temporal DBSCAN and robust trimmed clustering. The newest release fixes predict-time behaviour across the hierarchical learners.
AgencyAnalytics is shipping steadily across two tracks. The visible one is reporting ergonomics for agencies managing many clients: regex and contains filtering on custom metrics, client tags applied in bulk, and a Shares tab exposing every way a report has been sent. The second, and the one the roadmap language keeps pointing at, is AgencyAI — which gained saved reusable Skills in August, while the client Data tab was consolidated in July explicitly to give those answers more context to draw on.
The company is converting a reporting tool into an analysis layer, and monetising the AI separately — AI Tracker went to open beta as a metered add-on at twenty-five dollars per 250 credits rather than as an included feature. Each structural change now gets justified by what it gives AgencyAI to work with, which suggests the reporting surface is being reorganised around the assistant rather than the other way round. Data-source maintenance continues underneath, including removing a Microsoft Ads metric the upstream API could not support accurately.
Expect the Data tab to keep absorbing client context types as promised, and further metered AI capability to follow AI Tracker out of beta on the same credit model.
mlr3cluster supplies clustering learners to the mlr3 framework. Over three releases it added roughly a dozen learners — CLARA, k-prototypes, spectral, then a batch of nine covering finite mixtures, spherical and directional families, self-organising maps, spatio-temporal DBSCAN and robust trimmed clustering. The newest release fixes predict-time behaviour across the hierarchical learners.
The package is at the tail end of a coverage push, and the emphasis has shifted from adding algorithms to making the ones it has behave correctly at prediction time — cutting trees at the current k, reclustering coresets, failing informatively on unsupported metric combinations. That is the normal sequence after a rapid expansion.
Expect further predict-path corrections and parameter-set alignment across the newly added learners before any more algorithms arrive.
Other Analytics products tracked by Sparkpulse, ranked by recent ship velocity. Each card links to a full editorial trajectory and lets you pivot into a head-to-head comparison with either AgencyAnalytics or mlr3cluster.
Finished, widely taught, and shipping roxygen fixes.
Text features finally stay sparse all the way to the model.
The package that made calibration a step instead of an afterthought.
workflowsets keeps widening what counts as a model worth comparing.
The tidymodels pipeline grew a third stage, and it happens after the model runs.
Posit's MLOps package went quiet for two years, then came back to keep up with recipes.
See all AgencyAnalytics alternatives → · See all mlr3cluster alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. AgencyAnalytics is currently shipping more aggressively (velocity 6.3 vs 0.0), with 1 editorial sparks in the last 30 days against 0. See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. AgencyAnalytics is currently shipping more aggressively (velocity 6.3 vs 0.0), with 1 editorial sparks in the last 30 days against 0. For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.
Top AgencyAnalytics alternatives in Analytics are ranked by recent ship velocity. Browse the "AgencyAnalytics alternatives" section above for the current picks, or visit /alternatives/agencyanalytics for the full list with editorial commentary on each.
Top mlr3cluster alternatives in Analytics are ranked by recent ship velocity. Browse the "mlr3cluster alternatives" section above for the current picks, or visit /alternatives/mlr3cluster for the full list with editorial commentary on each.