Protect fulfillment speed.
Faster handling of receiving, inventory, and support exceptions helps customers get the parts they need on time.
OpenNash
Prepared for
Digi-Key Electronics · July 2026
A working hypothesis for Digi-Key receiving, warehouse, and logistics teams
Keep parts moving through receiving and the warehouse so every order ships on the shift it's promised.
Digi-Key moves millions of electronic components through its Thief River Falls distribution center, where same-day shipping lives or dies on receiving, put-away, and warehouse work. Almost every one of the 14 open roles we read sits right there: receiving, general warehouse, maintenance, and logistics. The first useful OpenNash workflow would help those teams clear a receiving or inventory exception faster, with an operator reviewing every step.
OpenNash builds custom 24/7 AI agents for customer support, back-office, and operational work. We automate workflows end to end inside the systems your team already uses: secure, auditable, and human-reviewed where it matters.
Engineers who build AI agents that work.
Start with the Zero to Agent guide, then bring one real Digi-Key Electronics workflow we can map in plain English.
Read Zero to Agent
Built by engineers from GoogleMetaSnowflakeDatabricks
Business thesis
Digi-Key makes money when parts, orders, and fulfillment stay fast and reliable.
Digi-Key's promise of fast, same-day shipping depends on tight execution across receiving, inventory, and warehouse operations at its Thief River Falls distribution center. OpenNash would help those teams resolve the exceptions that slow parts from moving, without replacing the systems they already use.
About DigiKeyReduce warehouse and support rework.
Better context up front means fewer repeated checks, handoffs, and manual status hunts.
Make every operations reviewer faster.
Source-linked packets help teams clear more exceptions while keeping approval, edits, and accountability human.
What OpenNash is
Reliable, auditable AI workflows for the work that actually runs the business.
We study how your best humans solve hard work, replicate the skill, and build AI agents that automate the repetitive parts while keeping people in control of exceptions, approvals, and judgment calls.
M.01
Time to production: 4-8 weeks
We do the workflow audit, build the agent, connect the tools, write evals, and launch against real operating cases.
M.02
14-day no-charge pilot
Forward-deployed engineers embed with your team, watch the best operators work, and prove one workflow before you commit.
M.03
Built on your software
APIs, CRMs, data warehouses, dashboards, spreadsheets, inboxes, browser-only portals, and legacy systems.
M.04
U.S.-based, on site if useful
We will fly to you, work with the people doing the work, and price the pilot risk so you do not have to.
Zero to Agent
We teach the basics, then build inside your real work.
Step 01
Learn
We explain the pieces in plain English: models, tools, context, approvals, evals, and why reliable agents need more than a prompt.
Step 02
Build
We connect to the tools that finish the work today and replicate the process against real test cases before automation.
Step 03
Launch
Human-in-the-loop review, monitoring, audit logs, recovery paths, and automated tests keep the agent reliable in production.
Evaluations are the difference between a demo and a production workflow. We write test cases for incomplete requests, unusual documents, portal errors, approval paths, and edge cases so the agent can fail safely, ask for help, and improve from real reviewer feedback.
Research snapshot
Where Digi-Key Electronics appears to be adding people
Almost every open posting sits inside the Thief River Falls distribution center: receiving, general warehouse, and facilities work, with a smaller set of maintenance and logistics roles behind it. That points to a business where inbound parts and warehouse exceptions decide how fast an order ships. Treat it as a hypothesis from public postings until an operator confirms the real workflow.
Open roles reviewed
14
From digikey.wd5.myworkdayjobs.com and related public postings.
Largest work pattern
9
Receiving and warehouse operations
To a working pilot workflow
14 days
No charge. On-site if useful. Staff approve everything.
14 open roles pulled from digikey.wd5.myworkdayjobs.com · July 6, 2026
Three problems worth solving
Three problems worth solving.
RECEIVING AND WAREHOUSE
A short or mismatched shipment should not stall the parts behind it.
Digi-Key has 9 open roles in receiving and warehouse work, including Facilities Associate, Receiving Associate, and Receiving Support Associate. These are the people who catch damaged pallets, short counts, and PO mismatches before they slow put-away and picking.
Our point of view
OpenNash would pull the PO, packing list, item record, and supplier notes into one reviewed packet so a receiving lead can settle the exception in a single place.
Fewer held pallets and a clearer record of which suppliers cause the most rework.
“General Warehouse Associate”
MAINTENANCE AND RELIABILITY
When a sorter or conveyor goes down, every order behind it waits.
Digi-Key has 3 open roles tied to keeping the automated warehouse running: Automation Maintenance Technician, Manager, Maintenance & Reliability, and Resident Maintenance Technician. Their work depends on fast, well-documented handoffs when equipment faults interrupt the flow.
Our point of view
OpenNash would assemble the asset history, recent alerts, parts availability, and prior fixes into a reviewed packet so a technician starts with context instead of hunting for it.
Shorter downtime and a running record of which failures keep repeating.
“Automation Maintenance Technician”
LOGISTICS AND BACK OFFICE
Logistics and finance decisions stall while someone rebuilds the numbers by hand.
Digi-Key has 2 senior openings that sit over the flow and its finances: Sr. Manager, Logistics Operations and Senior Director, Accounting. Both rely on pulling status and figures together from several systems before a call gets made.
Our point of view
OpenNash would gather shipment status, carrier performance, and cost detail into a source-linked packet so a decision is backed by current numbers, not a manual pull.
Faster decisions and less time spent reconciling the same data twice.
“Sr. Manager, Logistics Operations”
How OpenNash would help
Turn a receiving or warehouse exception into a reviewed, measured handoff.
The first pilot should make the messy handoff visible, reviewable, and measurable without replacing the systems staff already use.
- The workflow stays inside the operating workflow.
- Every recommendation links back to source context.
- The pilot measures whether the workflow is worth expanding.
How the first 14 days run
One workflow, live in two weeks, measured honestly.
First workflow we would test
Digi-Key receiving and warehouse exceptions - short shipments, PO mismatches, and equipment holds
Day 1
Watch the work
Sit with the team that owns the workflow and record the decision points, source systems, exceptions, and approval rules.
Day 3
Map the packet
Define what context the reviewer needs, what OpenNash drafts, and what must stay human-approved.
Day 8
Run live examples
Turn real requests into source-linked packets inside a small review workflow.
Day 14
Measure honestly
Review cycle time, approval rate, edits, rework, and the exceptions that should stay manual.
No charge for the pilot. U.S.-based team — we fly to you. OpenNash connects to the systems your teams already use; nothing is replaced. Every draft, summary, and routing decision lands in a simple review flow where your staff approve, edit, or reject it, with a link back to the source and an audit trail of every action.
Structured role evidence
All 14 Digi-Key Electronics roles on this page, searchable.
Search by title, location, work pattern, or how OpenNash would help. This is the full role list behind the hypothesis above, not a curated sample.
14 of 14 roles shown
| Role | Work Pattern | Location | OpenNash Fit | Source |
|---|
No roles match that search.
Pulled from Digi-Key Electronics public postings on July 6, 2026 · every source link goes to the original posting where available.
The ask
Show us one real workflow from this week.
We will map where an AI agent can help, what should stay human-approved, and what test cases would prove it works.