Governed workflows for recurring reports, operations dashboards, and RPA replacement that run your Python, pause on exceptions, and ask before they write back.
A four-person operations team at a Fortune 500 retailer automated a weekly multi-file report.
Legacy RPA scripted the clicks and broke when a vendor moved a button. The weekly report still needs a human to open six weekly Excel attachments from the shared inbox. The operations dashboard shows what dropped, but finding why takes manual investigation—one recurring order issue alone had real margin impact.
Every process has a happy path and forty exceptions. Automation solved the happy path.
Give the repeatable steps to the agent. Keep the exceptions for people.
Hand Athena the click-by-click SOP and the data sources—the inbox, the SharePoint folder, the Snowflake tables, the PO system, your existing Python. The inbox, the SharePoint folder, the Snowflake tables, the PO system, your existing Python.
It becomes an Agent Operating Procedure (AOP). Triggered by the file landing, the schedule, or the PO event. Your scripts run unchanged where they exist.
Exceptions come to you. The run pauses on the step it cannot complete and asks. Heal-then-continue, not fail-and-die.
Write-back with approval. Rebalancing recommendations, PO status changes, and carrier updates are typed actions you approve. Everything is attributed and reversible.
Six weekly Excel files from partners land in a mailbox. The workflow picks them up, runs the logistics team's existing Python, and fills the 100-row output template. A four-person operations team at a Fortune 500 retailer stopped building that weekly report by hand.
Vendor fill rate, cancelled and past-due POs, rebalancing candidates, competitor coverage, on one governed dashboard with drill-through to the PO.
Brittle bots migrated to workflows that adapt within policy and pause for a human on real change. The team that built the bots does not have to maintain them.
Inventory data joined to third-party competitor stocking data: products where coverage is 0% here and 100% across the street, drillable by product.
Teams threads, Outlook, and the tracker become one status slide and an executive summary, cited.
Snowflake finance and supply data joined in a Sheet through the semantic model. A supply-chain landscape extracted from a folder of vendor decks into a comparison table.
An agent that keeps the project plan current from the conversations, files, and tickets it can see, and nudges owners.
“I'm very excited. This is something that I have been piecemealing with the limited tools that analysts get... rather than me at nine PM getting a failure email and deciding I'll just do it myself.”
“It's good to understand the capability of the platform. That how far, and how quickly you guys can get these things going [...] that has been impressive overall.”
“Lets us get a lot more out of our data than [...] We can sit on top of all of the data in [our data warehouse] as opposed to just, like, our little ingested, you know, three gigabytes semantic models. I think we have a lot of power here.”
“Gave Athena the spreadsheet, explained which column I was trying to figure out, and then ten secs it told me... exactly how the calculation was based on the other data.”
“He wrote the entire stuff. By itself. And I was there, and I was thinking, alright. If I had to write all this stuff, I mean, I would've spent days, days, days.”
“I send that to the programmer and he said, alright. I read your file. I copied the section of the code because he has the right interface, and it works. Wow. Just like magic.”
“One workspace. All different, let's say, avatars of their output data. Right? Suddenly, it's dashboard. Excel is here. PowerPoint is when it's all together. It's very impressive.”
“Use the Athena platform probably closer to the concept and how it was designed, like, with the spaces architecture where you've got a set of primitives and capabilities, and you bring together the right set of capabilities to solve a task.”
“Digital worker, it gets spun up, it gets given access to the toolkits that it needs. It gets given access to the data that it needs. Just exists for the period it needs to exist to perform the task. And then it gets torn back down again afterwards.”
“I like that direction, that concept of the agent is the agent. It becomes an entity in its own right with its own ownership and its own missioning, and you get rid of the gray area and the blurry lines.”
Verbatim from customer calls. Customers anonymized.
Agents for the ad hoc: "which POs slipped this week and why." Workflows (AOPs) for the recurring: the weekly report, the PO watch. Applications for the many: the operations dashboard every planner opens with access included in Athena services.
Snowflake, Databricks, SAP extracts, Oracle, shared M365 inboxes, SharePoint, Teams, carrier portals through a governed browser when there is no API. Runs in our cloud or your VPC.
Athena does not replace your planning or execution system. It reads from them, reasons across them, and writes back only where you allow, with approval.
Process partner files, track exceptions, monitor inventory and orders, and check that data arrived on time, so teams act on problems instead of hunting for them.
Yes. Agents can run the scripts and rules your team already relies on, inside governed workflows.
Agents flag what needs attention and route it with the evidence attached.
With one weekly report or intake process that the team rebuilds by hand.
Records every change by a person or an agent, rolls back one contributor's edits without losing anyone else's, and keeps the model, instructions, and sources behind each agent action.
How the platform is deployed: Athena's managed cloud, your cloud on AWS, GCP, or Azure, on-prem, air-gapped, or GovCloud. Same platform in every option.
Build, Work, and Data on top; 150+ connectors and every surface in and out; one map of the whole platform.
Ready-made supply chain briefs you can run on a schedule.
We will run your script on it, fill your template, and show you the exception queue.