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AgencyAnalytics vs distributional

A side-by-side editorial comparison of AgencyAnalytics and distributional — release velocity, themes, recent moves, and the top alternatives to consider.

AgencyAnalytics vs distributional: at a glance

FeatureAgencyAnalyticsdistributional
SectorAnalyticsAnalytics
Velocity score6.30.0
Sparks · 30d10
Top themesagency-reporting, ai-assistant, skills, integrationsr-package, probability-distributions, distribution-arithmetic, numerical-methods
Last editorial update15h ago4d ago
WebsiteVisit →Visit →

What is AgencyAnalytics?

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.

Read the full AgencyAnalytics trajectory →

What is distributional?

distributional taught + and - to work on any pair of distributions, closing the algebra it started with.

The R package providing vectorised distribution objects — the substrate that forecasting and anomaly tooling in the same ecosystem builds on. Cadence has picked up sharply, with four releases in the six months to June 2026 against roughly one a year before that. Two kinds of work alternate: adding distribution families (Dirichlet, Horseshoe, Laplace, multivariate t, g-and-k, the extreme-value pair) and deepening what can be computed generically across all of them.

Read the full distributional trajectory →

AgencyAnalytics vs distributional: editorial side-by-side

A6.3

AgencyAI got skills three weeks ago; everything since has been making them routine.

◆ Current state

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.

◆ Where it's heading

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.

◆ Prediction

Expect scheduled skills to gain delivery — results pushed into reports or sent to clients — rather than staying inside the assistant panel.

D0.0

distributional taught + and - to work on any pair of distributions, closing the algebra it started with.

◆ Current state

The R package providing vectorised distribution objects — the substrate that forecasting and anomaly tooling in the same ecosystem builds on. Cadence has picked up sharply, with four releases in the six months to June 2026 against roughly one a year before that. Two kinds of work alternate: adding distribution families (Dirichlet, Horseshoe, Laplace, multivariate t, g-and-k, the extreme-value pair) and deepening what can be computed generically across all of them.

◆ Where it's heading

The generic-computation thread is the one that matters and it has been building steadily: a Monte Carlo default method for cdf(), has_symmetry() to let algorithms specialise, hdr() moving to exact results for symmetric distributions and 4096 quantiles elsewhere, open-versus-closed support intervals. Version 0.8.0 is where that thread arrives somewhere — arithmetic on arbitrary distributions, with closed forms used when they exist and numerical convolution when they do not. The package is positioning itself as a computational layer rather than a catalogue, which is consistent with how weird and the forecasting packages consume it.

◆ Prediction

Expect the numerical machinery behind dist_convolved() to be reused for other operators, and more generics like has_symmetry() that let downstream algorithms take exact paths when a distribution supports them.

Alternatives to AgencyAnalytics and distributional

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 distributional.

See all AgencyAnalytics alternatives → · See all distributional alternatives →

Recent activity from AgencyAnalytics and distributional

Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.

  1. 1d agoAgencyAnalyticsMailerLite is now available
  2. 2d agoAgencyAnalyticsSchedule your AgencyAI prompts
  3. 7d agoAgencyAnalyticsAdvanced filtering for custom metrics and KPIs
  4. 7d agoAgencyAnalyticsOrganize your clients your way with tags
  5. 12d agoAgencyAnalyticsReport Shares View
  6. 12d agoAgencyAnalyticsSkills in AgencyAI
  7. 1mo agodistributionalConditional S3 registration so the package loads on R before 4.3
  8. 1mo agodistributionalDistribution arithmetic: FFT convolution behind the + and - operators
  9. 2mo agodistributionalVectorised p in quantile() for inflated distributions; open brackets on infinite bounds
  10. 5mo agodistributionalDirichlet and Horseshoe distributions added
  11. 7mo agodistributionalhas_symmetry() generic, exact HDRs for symmetric distributions
  12. 1y agodistributionalMonte Carlo cdf() default method; g-and-k, g-and-h and extreme-value families

Frequently asked questions

What is the difference between AgencyAnalytics and distributional?

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.

Is AgencyAnalytics better than distributional?

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.

What are the best alternatives to AgencyAnalytics?

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.

What are the best alternatives to distributional?

Top distributional alternatives in Analytics are ranked by recent ship velocity. Browse the "distributional alternatives" section above for the current picks, or visit /alternatives/distributional-r for the full list with editorial commentary on each.