Our new Instacart Ads integration is now in Beta. If you advertise on Instacart, you can bring that spend and performance data into Daasity directly from Instacart, with no more exporting and uploading files. You connect it yourself from your New Integration screen.

Instacart requires each advertiser to register their own API application, so setup includes a few steps in Instacart Ads Manager. You'll need a user with API Authentication enabled and Read access to Customer Insights Reporting.

Attributed sales are the numbers Instacart reports, using last-touch attribution. Instacart does not report order counts, so orders are not included.

Instacart Ads Integration Setup walks through each step.

Our new Walmart Connect integration is now in Beta. If you run Sponsored Search ads on Walmart, you can bring that performance data into Daasity directly from Walmart, with no more exporting and uploading files. You connect it yourself from your New Integration screen.

Walmart requires each advertiser to approve the partners that can read their advertising data. Before you connect, an admin on your Walmart Ad Center account adds Daasity as an API partner with read access. Then choose Walmart Connect in Daasity, enter your Advertiser ID and click Create.

Orders and sales are the numbers Walmart reports. This first release covers Sponsored Search. Display ads are not included.

Walmart Connect Integration Setup walks through each step.

Notifications in Daasity have been rebuilt. Every notification now tells you whether it's yours to fix or ours, explains what happened in plain language, and gives you one clear next step. A problem that keeps happening shows up once and clears itself when it's fixed.

Your notification list started fresh on October 5. Notifications from the old system were cleared automatically, and you can still find them under Resolved on the All tab for 30 days. Anything still failing has come back as a new notification. If you see one under "Needs you," that integration needs your attention. No other action is required.

AI Analyst and the Daasity MCP Server now answer using the definitions written into your data model, and tell you which ones they used. Ask about "DTC," "net sales" or "refunds," and the answer quotes your definition and names the filter it applied, so you can check the logic at a glance.

Definitions appear in views rebuilt since September 28. Run once, then ask a question you already know the answer to and compare it with your dashboard.

Loading past Pinterest data now brings in the full date range you ask for, so your Pinterest spend and performance history is complete.

Loads of past Pinterest data could miss roughly 24 days at the start of the range you requested. Some reporting periods were also dropped when Pinterest was slow to respond. New Pinterest connections could only load two months of history.

History loads now cover the full range you request and wait for Pinterest to finish before moving on. A new Pinterest connection can now load up to 900 days of history, the most Pinterest makes available.

If you loaded Pinterest history before September, run the history load again to fill any gaps. New loads are complete going forward.

Ad spend for AppLovin, Snapchat and TikTok Ads now matches what you see in each platform, so your marketing efficiency numbers (ROAS, cost per acquisition and similar) are based on the right spend.

AppLovin spend could be overstated after an ad was renamed, because the renamed ad was counted as a new one. Some Snapchat spend could be counted twice. TikTok Ads spend was being rounded, which dropped the cents. AppLovin history also only reached back 45 days.

All three are corrected, and AppLovin history now reaches back 88 days, the most AppLovin makes available.

Spend from here forward is correct. Earlier AppLovin and Snapchat spend isn't corrected automatically, so if spend on either platform has looked high, contact Support and we'll reload the affected dates.

If you replicate tables from your own database into Daasity (for example NetSuite, Postgres, SQL Server, Snowflake or BigQuery), you can now adjust what's being pulled without rebuilding the setup, and you'll be warned before a change would break it.

You can now edit an existing table replication to add a filter or bring in another column, instead of deleting it and starting over. If an edit would cause data to load incorrectly, it's stopped before it's saved with an explanation of what to change. You can also see progress while a history load is running, and you'll get a heads-up when a setup would re-read the entire table on every refresh, which slows down how quickly your data is ready.

We also fixed an issue where columns you renamed during setup were arriving empty in your reporting.

No action is required for most merchants. If you renamed any columns in a table replication, run a history load on it so earlier data fills in. Database Replicators walks through the full setup.

You can now see whether a data refresh brought in everything it was supposed to, and if it didn't, exactly which data sources and dates are missing. That means fewer surprises from reports that quietly left something out.

The refresh status page now shows each of your data sources as it loads, so you can see what's finished, what's still in progress and what failed. A refresh that finished with gaps is now clearly marked "Completed (with errors)" instead of looking complete. A single summary lists anything that was skipped and why, whether it was a problem on the source platform's side or something our Support team stepped in on.

We also changed how problems are contained. When one source has an issue, like a platform report that never finishes, that piece is skipped and the rest of your data still refreshes on time instead of everything waiting on it.

No action is required. If a refresh shows skipped data, reports that rely on that source may be missing those dates until they're reloaded. Contact Support and we'll help fill the gap.

CSV and file imports now get the same guided setup that database sources got in August. You can set up, test and manage file integrations from SFTP, S3, Daasity Storage and email without hand-configuring each step.

A List Files browser shows what's in your S3 or SFTP location, so you can confirm your source pattern matches the right files before saving. Warehouse tables are created during setup with a live progress view. Field mappings now include date-format selection. Deleting an integration or changing its sync key asks whether to keep, drop or rename the destination table. Each integration also has a file-processing log showing which files were picked up and how they loaded.

We also fixed three issues with file loads. Column formatting was sometimes switching itself on and loading dates incorrectly; it now follows only the setting on the integration. A lookback window of 0 now loads today's files only, instead of falling back to 72 hours. Files with rows that don't match the header now report which row and how many columns were off.

The update rolls out automatically and no action is required. Existing file integrations keep running unchanged. Data File Integrations covers the full flow.

Today we're launching AI Analyst and the Daasity MCP Server to all merchants. Both let you ask questions about your business in plain English and get answers built from the same governed metric definitions that power your dashboards.

AI Analyst lives inside Daasity. Ask "which products drove growth last month" or "what changed last week, and why," and you get an answer with its assumptions shown, suggested follow-ups, and a View data option that expands the underlying rows.

The MCP Server connects the AI tools your team already uses — Claude, Cursor, Codex, ChatGPT — directly to your Daasity data. One connection, and your AI answers from live, governed numbers instead of whatever spreadsheet was last exported. Build a custom report from a prompt, combine a retailer's category review with your own margins, or schedule a Monday recap that writes itself.

Same engine, two doors. The distance between a business question and an answer you can act on just got a lot shorter.

Both surfaces resolve questions against your account's governed semantic views — the metric definitions generated from your own data model, not raw warehouse tables. A question is matched against your dashboards first, then your deployed semantic views, and only falls back to generated SQL when neither covers it, in which case the answer says so.

The MCP Server is self-serve. Open the MCP screen in your Daasity profile menu, copy your connection URL, and add it as a custom connector in your AI tool. Every connection is read-only, scoped to your workspace, expires after 30 days, and can be revoked by you at any time.

Supported on Snowflake, BigQuery, and Redshift. Looker is not required — merchants without a BI tool are provisioned automatically on first login.

AI Analyst and MCP access are enabled per user. If you'd like your team turned on, send your account manager the names and emails, and for multi-brand organizations, which brands each person needs. Turnaround is same-day during this period.

A good first question: "Top ten products by net sales in the last 30 days, with units." Then open the equivalent dashboard and compare. That's what builds trust fastest.