Basedash
Basedash keeps pushing its data out of the workspace — now to people without accounts
A side-by-side editorial comparison of AgencyAnalytics and mev — release velocity, themes, recent moves, and the top alternatives to consider.
AgencyAI got skills three weeks ago; everything since has been making them routine.
The cadence is weekly and heavily weighted toward AgencyAI. Skills landed in early August as named, runnable agency tasks; scheduling followed, so those tasks now run on their own. Around the assistant, the reporting surface keeps widening: advanced filtering on custom metrics and KPIs, client tags, a report shares view, and a MailerLite data source that brings email campaign metrics alongside every other channel.
An extreme-value toolkit reorganised its whole API into prefixed families and tripled its estimator count.
mev provides likelihood-based inference for univariate and multivariate extreme value models — threshold selection, shape estimation, tail dependence and max-stable simulation. Version 2.0 was a deliberate reorganisation: every threshold-selection routine now carries a thselect. prefix, every stability plot a tstab. prefix, and every extremal-dependence measure an xdep. prefix, with the old names deprecated but mostly still working. The same release added a large batch of estimators — Stein-weighted GPD, roughly a dozen shape estimators, second-order regular variation, L-moment GPD and Weissman quantiles.
The cadence is weekly and heavily weighted toward AgencyAI. Skills landed in early August as named, runnable agency tasks; scheduling followed, so those tasks now run on their own. Around the assistant, the reporting surface keeps widening: advanced filtering on custom metrics and KPIs, client tags, a report shares view, and a MailerLite data source that brings email campaign metrics alongside every other channel.
The assistant is being moved from something an operator invokes to something that runs on a schedule against connected client data, which changes it from a feature into part of the reporting pipeline. The integration work continues at its usual pace and serves the same end — the more channels are connected, the more a scheduled skill has to reason over. Filtering and tagging are the plumbing that lets those tasks be scoped to the right accounts.
Expect scheduled skills to gain delivery — results pushed into reports or sent to clients — rather than staying inside the assistant panel.
mev provides likelihood-based inference for univariate and multivariate extreme value models — threshold selection, shape estimation, tail dependence and max-stable simulation. Version 2.0 was a deliberate reorganisation: every threshold-selection routine now carries a thselect. prefix, every stability plot a tstab. prefix, and every extremal-dependence measure an xdep. prefix, with the old names deprecated but mostly still working. The same release added a large batch of estimators — Stein-weighted GPD, roughly a dozen shape estimators, second-order regular variation, L-moment GPD and Weissman quantiles.
The package is consolidating into a reference implementation of the extreme-value literature rather than a collection of one-off routines. Sixteen threshold-selection methods now share standardised arguments and their own plot and print methods with automatic selection, which is the tell: the goal is comparability across methods, not just availability. Dependency reduction runs alongside, with distribution functions written in-package to drop evd and Rsolnp replacing nloptr in earlier releases.
Version 2.1 continued adding threshold-selection routines within the new naming scheme, so the next release most likely follows the same pattern — more estimators fitted to the established prefixes, plus fixes to the 2.0 renaming. The entries give no sign of a further structural change.
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 mev.
Basedash keeps pushing its data out of the workspace — now to people without accounts
RStudio ships through release branches, and the notes are commit messages
dbt Fusion's second beta is adapter work: ClickHouse gets materializations, indexes, and catalogs
Fulcrum is betting its whole map stack on Esri, with a hard Google Maps cutoff on September 1.
Holistics keeps fencing in the AI layer it spent the summer building.
Dovetail spent July opening doors to other tools and August making its own rooms easier to enter.
See all AgencyAnalytics alternatives → · See all mev 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 mev alternatives in Analytics are ranked by recent ship velocity. Browse the "mev alternatives" section above for the current picks, or visit /alternatives/mev for the full list with editorial commentary on each.