July 2026

Releases Shipped

Version	Released
v5.11.0	2026-07-09
v5.11.1	2026-07-13
v5.11.2	2026-07-15

Added

• PlaidCloud Git connections. Connect to your workspace’s own managed Git server with a simplified form — just an account name, memo, repository path, default branch, and optional start path — with no server URL, username, token, or SSH key to enter, because your Git server and your access to it come from your normal PlaidCloud sign-in. Point a Server Panel app’s build at a PlaidCloud Git connection to automate builds entirely inside your workspace, without an external GitHub account or access token. External Git providers (GitHub, GitLab, Bitbucket, Forgejo, Gitea) keep their full connection form. See PlaidCloud Git Connection.

• Currency — a column data type built for money. Every column data-type list — step output column mappings, the data mapper grid, a table’s Column Properties, and MCP/AI tooling — now offers Currency: an exact fixed-point type with 18 digits of precision and 4 decimal places (roughly ±100 trillion, exact to 1/10,000). It stores money in half the in-memory width of Numeric, so money-heavy dashboards and workflow steps scan about half the data and run faster; Numeric stays the high-precision default (38 digits, 10 decimal places). Currency is always your explicit choice — imports, type detection, SQL results, and derived columns still default to Numeric — and once set on a column it is remembered through reads, downstream steps, and table rebuilds. Aggregations of Currency return Numeric. The option appears once the platform update is live on your workspace. See Currency Data Type.

• Skip re-importing unchanged source files — file-import steps (CSV, Excel, Fixed Width, JSON, Avro, Parquet, Alteryx yxdb, dbf, XML, X12 EDI, Access) have a new Skip re-import if source files unchanged option. Turn it on and a workflow run skips the whole download, conversion, and table rebuild when the source files and the step’s settings have not changed since the last successful run — so a scheduled reload no longer repeats the work. On by default — untick the option on a step to always re-import; the change is detected from each file’s size and modified time, plus a content hash where the source provides one. Manual, one-off imports always run. See Import CSV.

• Machine learning in workflows — ML: Train Model and ML: Score steps. Train a model on any table — choose from seven algorithms including linear and logistic regression, decision trees, random forests, and gradient boosting — and score data with it, appending a prediction column, entirely inside a workflow. The trained model flows through the workflow like any other table, with its algorithm, settings, features, and training metrics recorded alongside, and mistyped algorithms or settings are caught when you save the step. Alteryx Assisted Modeling pipelines also convert to these native ML steps on import, with XGBoost models carrying a documented approximation note. See ML: Train Model, ML: Score, and Machine Learning Conversions.

• PlaidCloud Managed Bucket document accounts. Add fully managed file storage to Document in a single step — no cloud project, credentials, region, or storage tier to set up or tune. Available on the Business and Enterprise plans. See Add a PlaidCloud Managed Bucket Account.

• Connect a OneDrive or SharePoint site with least-privilege access. Add a OneDrive for Business or SharePoint site as a Document account that can reach only the sites your Microsoft administrator has explicitly granted — Microsoft’s Sites.Selected model — rather than your whole Microsoft 365 tenant. Choose OneDrive as the account’s service, enter your app registration’s Client ID, secret, and tenant ID, paste a granted site’s URL, and pick one of its document libraries as the starting folder. Sites you don’t grant — payroll, HR, and the like — stay completely out of reach. See Add OneDrive / SharePoint Account.

• A more capable REST Request step. REST Request can now fan a call out over the rows of a driver table — one request per row, with an optional row filter — carrying key columns onto the results, with a concurrency limit, a request-rate cap, an opt-in idempotency key for safe re-runs, a continue-on-error option, and clear per-row failure reporting. New authoring aids make requests easier to build and verify: import from a curl command, insert and highlight variable tokens (including a driver table’s columns), test the first fan-out row, preview the resolved request and its pagination before running, restore unsaved drafts, edit the selected connection in place, and confirm before saving a request you haven’t successfully tested. See REST Request Step.

• An expanded Help & Support experience. Attach screenshots and files to tickets and replies (images show inline), work tickets from a sorted, filterable support console (reply, add internal notes, claim, set priority, and escalate to PlaidCloud), route new-ticket alerts to a Slack, Teams, or email channel, email the ticket owner when a ticket gets a reply, and auto-escalate tickets left unanswered too long. See Getting Help, The Support Console, and Managing Support.

• Analysis paths for AI questions. Give the tables you analyze most a friendly name, and set one as your default, so you and your AI assistant can ask about “the Operations Results” — or just “what changed last quarter?” — without naming the project and table every time. Works across Microsoft 365 Copilot and any MCP-connected agent. See Analysis Paths.

• Smarter, more honest AI allocation cost-tracing. When you ask an MCP-connected AI agent why an allocation result changed, the answer now carries a plain-language confidence level and caveats — flagging when a cause is a mix of overlapping factors, when it depends on current hierarchy or driver weights, or when part of the change may just be an unfinished data load, and these trust signals travel with the answer even when a follow-up agent summarizes it. Administrators can also turn on an optional check that lowers confidence and flags an answer when the pool or driver data behind it hasn’t been reloaded recently. For a result built from several allocation branches, the confidence now weighs each branch by how much of the change it accounts for, so one small, shaky branch doesn’t drag down an otherwise-clean answer. You can also ask driver-reweight what-if questions (“what if this cost centre’s headcount doubled?”), and the full root-cause analysis can now be driven over the REST API, not only through an AI agent. See Tracing Allocations with an MCP-Connected AI Agent.

• A written trace summary you can trust — and your AI can check. When you ask an MCP-connected AI agent why an allocation result changed, it can now return a plain-language summary built directly from the analysis: it states the confidence level, carries every caveat, and cites no figure that didn’t come from a real query. A companion faithfulness check lets the agent confirm its own reworded version kept the confidence and every caveat and invented nothing — so the narrative is provably faithful, not just fluent. Each summary also suggests the natural next question — scope to a single member, break the change down by a dimension, or point at a specific producing step when a result table is built by more than one — so you can drill in without knowing the exact wording. See Answers You Can Trust.

• Preview step data in the Visual Workflow Designer. See a step’s output in place, without opening a new window — dock a preview of the first 100 rows, with typed columns, row and column counts, and a selector for multi-output steps, at the bottom of the canvas. Clicking another step retargets the preview, it refreshes when a run finishes, and you can open the full Table Explorer in one click. See Preview Step Data.

• Lock a Panel app against accidental changes. A lock icon on each row of My Panel Apps protects an app the way the existing workflow and step locks do: while locked, editing, removing, and rebuilding it refuse to run — and a git push to a server app’s branch no longer rebuilds it — while opening the app, its logs, and its usage metrics keep working. It’s a guard against accidents, not a security control: anyone who can edit panel apps can unlock them. See Locking an App.

• Workflow steps are auto-numbered. Every step now carries a number — a badge on the visual canvas, the leading column of the steps grid, and the same “Step 7” in run logs, workflow documentation reports, and AI assistant listings — so you can point a teammate or an AI agent at “step 7” instead of describing a step by name in a tangled imported workflow. Numbers follow the flow (a step always numbers after the steps it feeds from), canvas position breaks ties left-to-right then top-to-bottom, and everyone’s canvas renumbers live as the workflow is edited, with a brief highlight on steps whose number changed. Right-click a step (or click its badge) to copy a ready-to-paste reference like “Step 7 — Clean Customer Names”. See Step Numbers.

• Two new workflow steps — Directory Listing and Row Count Assert. Directory Listing writes a table of the files in a document directory (with an optional file pattern and a subdirectory option) so downstream steps can act on whatever files are present. Row Count Assert is a data-quality gate that fails the workflow when two tables have different row counts. See Directory Listing and Row Count Assert.

• Jump to a workflow’s logs from the Visual Workflow Designer. A View Logs button on the canvas toolbar opens the project Log view already filtered to the workflow you have open — the same full run log you’d otherwise reach from the Project area. See Advanced Workflows.

Changed

• Pick the repository, branch, and folder for a Git connection. The Git connection form no longer asks you to type a repository path, branch name, or start path — you choose them from live lists. Enter the server and credentials (nothing to enter for a PlaidCloud Git connection), click Refresh to list the repositories the connection can reach, pick one to load its branches, then browse its folders to set an optional start path — so a mistyped name can’t quietly break the connection. Editing an existing connection browses without re-entering the stored password. Applies to PlaidCloud Git and every external provider (GitHub, GitLab, Bitbucket, Forgejo, Gitea). See PlaidCloud Git Connection.

• AI cost-tracing is more accurate and harder to mislead. What-if estimates are now real per-target numbers that add up across a fan-out, rather than upper bounds, and can be scoped to a single target — and pointed at a driver or basis table instead of the input pool, the agent declines the estimate and explains why. Driver-reweight what-ifs are exact: they move only the amount the driver actually splits and leave any pass-through cost untouched. The agent now recognizes and lowers its confidence on misleading shapes — a total whose large ups and downs offset to a small net change, or a change that is mostly pass-through rather than driver-governed — naming how much the driver-controlled amount actually moved and no longer overstating a single “dominant factor” when the split is unreliable. It also explains dimension-hierarchy allocations instead of leaving them unattributed. Data-freshness checks now cover the driver and basis tables, results produced by more than one allocation step can be traced by picking the step — or automatically when a filter narrows to rows only one step produced — and a year-over-year comparison with no prior-year data now says so rather than calling the change “normal”. See Tracing Allocations with an MCP-Connected AI Agent.

• Alteryx import ends on a conversion report. Importing an Alteryx workflow now summarizes how many steps mapped with high confidence and how many need review, and lists the lower-confidence steps with notes so you can check them before running; each imported step also carries its confidence as a memo on the canvas. Packaged report macros now import as hand-editable Report steps, and a new guide plus a downloadable workflow batch-convert AMP-format .yxdb files to CSV so their data imports losslessly. See Migrate Alteryx Workflows and Convert .yxdb Files for Import.

• External Tables: refresh a single table’s columns from the source. On the Import and Export External Tables steps, the per-table Inspect Source button now reads the selected table’s current columns straight from the connected database and updates just that table’s mapping in place — handy when a source table’s columns have changed since you built the step, without re-running discovery over the whole connection. See Import External Database Tables.

• Presence in the Visual Workflow Designer now shows real avatars. When several people have the same Advanced workflow open, the toolbar’s presence row now shows each person by their gravatar (or their initials if they have none), and a person appears once no matter how many browser tabs they have it open in. See Advanced Workflows.

Fixed

• Clearer error when an import can’t read any columns. When you set up or auto-create a CSV or text import and PlaidCloud can’t read any columns from the source file — for example some Microsoft Access text exports, or a file whose delimiter or quoting doesn’t match — it now tells you right away, as you save or create the import, instead of letting the step run and fail later with a confusing message. Adjust the delimiter, quote, and escape settings or fix the file, then try again. See Import CSV.

• Managed bucket name collisions now explain themselves. Creating a PlaidCloud Managed Bucket document account with a bucket name that’s already in use previously failed with a generic “Internal server error”. The Bucket Name field now flags the collision directly and explains that bucket names are globally unique, with guidance on picking a more specific name — for example, adding your company as a prefix. See Add a PlaidCloud Managed Bucket Account.

• Deleting a table an import reads from now warns you. When you delete a table that an Import: External Project Table step reads from, PlaidCloud now recognizes it as in use and makes you confirm a force-deletion — ticking Force the delete of the table? — instead of offering a plain delete, so a table another project depends on can’t be removed by accident. This includes references from a step in a different project that shares this project’s data; those are shown in the confirmation without the other project’s step details (you may not have access to it). See Import Project Table.

• Join steps — Output Columns fixes. For Inner, Outer, Anti, and Cross Join, the Output Columns tab now lists only the columns you mapped from the two sources and drops stale rows when you remove a mapped source column; the column-mapper toolbar and multi-row selection are back; and Summarize is now a toggle that’s off by default, so a join no longer forces its output to be grouped — and when you turn it on, new columns default to an aggregation based on their data type, which you can override per column. Multi-Table Join output columns now follow renames and removals in the join-graph designer. See Table Inner Join and Multi-Table Join Step.

• REST Request reliability fixes. Variables now substitute reliably in JSON request bodies, per-request timeout and retry settings are honored (retries limited to idempotent methods, so a POST/PUT/PATCH is never re-sent), rate-limited responses are retried with backoff, and request credentials are masked in any captured raw JSON. A test request now shows the response status code even on success, and a single-object response imports as one row. Sensor- and webhook-triggered workflows can also read the trigger’s metadata and inbound payload as variables. See REST Request Step.

• AI cost-tracing fixes. Cost-tracing now handles model column names that contain spaces or symbols, resolves tables given by their friendly name, works on results from model-run steps and project copies, and works across all workspace types. Anomaly detection now flags unusually large swings and keeps quarter-labeled periods in real-time order across a year boundary, and two mislabeling bugs — a “from zero” jump when the weighting basis started empty, and a wrong-signed percentage change when the prior value was negative — are corrected.

• Create and Open now opens the right view for a DAG workflow. Using Create and Open Config on a new Advanced (DAG) workflow opened the classic steps grid instead of the Visual Workflow Designer canvas. It now opens the canvas, matching what you get by double-clicking the workflow. See Advanced Workflows.

• Panel app dependencies can live next to the app. A server-side Panel app built from a Git repository now installs a requirements.txt kept beside its entry point, not only one at the repository root — so an app stored in a subfolder of a shared repository can declare its own packages (for example plotly, holoviews, or hvplot) and no longer renders blank from a missing library. See Creating a Panel App.

Removed

• Retired legacy import and export steps — the SAS7BDAT import, HTML import, and HTML export steps have been removed. Use the current import and export steps for these formats instead.

• Retired the in-app Reset Password option — the Reset Password item has been removed from the account (avatar) menu. To reset your password, use the Forgot Password? link on the sign-in page.