Whatagraph
Whatagraph keeps fixing what breaks when one account runs a thousand sources.
A side-by-side editorial comparison of AgencyAnalytics and contentanalysis — 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.
A scientific-text analysis package moved from counting citations to classifying argument structure.
contentanalysis parses scientific papers from PDF and analyses their content — citation clustering, reference extraction and matching, word distribution, TF-IDF summaries by section. The most recent release adds a different kind of analysis: sentence-level classification of rhetorical moves, built on Swales' CARS model and extended to literature review and discussion sections, using rules by default with an optional Google Gemini path. PDF handling has been reworked in parallel for multi-column layouts and running header removal.
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.
contentanalysis parses scientific papers from PDF and analyses their content — citation clustering, reference extraction and matching, word distribution, TF-IDF summaries by section. The most recent release adds a different kind of analysis: sentence-level classification of rhetorical moves, built on Swales' CARS model and extended to literature review and discussion sections, using rules by default with an optional Google Gemini path. PDF handling has been reworked in parallel for multi-column layouts and running header removal.
The arc runs from surface features toward discourse structure. Early releases were about getting references matched correctly and plots readable; the current one asks what function each sentence performs in the argument, which is a categorically harder question and one the package answers with rules first and a language model second. The optional-LLM design is worth noting for what it avoids — the analysis still runs without an API key, and the package has already had to prune retired Gemini model versions once, which is the maintenance cost of depending on a hosted model. Reference parsing is being made format-aware rather than pattern-guessing, with CrossRef enrichment filling in what the PDF omits.
Expect the rhetorical move classification to widen to more section types and the rule-based path to keep being the default, given the package has already been forced to track model deprecations on the optional one.
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 contentanalysis.
Whatagraph keeps fixing what breaks when one account runs a thousand sources.
Lightdash keeps handing authoring to outside agents and keeping the governed layer for itself.
A 4.4.0 tag appears, but the feed carries only its release plumbing
distributions3 0.3.0 adds sample-based distributions and likelihood derivatives
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
See all AgencyAnalytics alternatives → · See all contentanalysis 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 contentanalysis alternatives in Analytics are ranked by recent ship velocity. Browse the "contentanalysis alternatives" section above for the current picks, or visit /alternatives/contentanalysis for the full list with editorial commentary on each.