Keep commodity and member workflows moving.
When grain, energy, agronomy, or financing work stalls, revenue and member experience suffer. Faster handoffs protect throughput.
OpenNash
Prepared for
CHS Inc. · July 2026
A working hypothesis for CHS Inc.
Keep grain, fuel, and crop nutrients moving for the members CHS Inc. serves, with fewer handoffs stuck between the field and the back office.
CHS Inc. runs grain elevators, agronomy centers, refined-fuel and propane delivery, and Cenex convenience stores, all owned by the farmers and local cooperatives it serves. The 257 open roles we read skew hard toward truck drivers, grain and plant operators, applicators, and store clerks, the people who keep product moving when weather, harvest timing, and market swings turn ordinary days into exceptions. The first useful OpenNash workflow would help those operators clear one recurring handoff, like a grain ticket, delivery, or agronomy work order that has to move cleanly between the field, the scale, and the back office.
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 CHS Inc. workflow we can map in plain English.
Read Zero to Agent
Built by engineers from GoogleMetaSnowflakeDatabricks
Business thesis
CHS makes money by moving grain, energy, agronomy, and financial services through a farmer-owned network.
CHS public financial materials point to commodity movement, logistics, energy, crop inputs, cooperative ownership, and volatile market conditions. The AI wedge is exception handling across documents, shipments, contracts, and member service.
CHS financialsReduce document and logistics rework.
Contracts, tickets, invoices, delivery status, compliance checks, and customer notes are fertile ground for reviewed agent packets.
Help operators handle volatility.
Agents can gather source context and draft next steps when markets, weather, shipments, or customer requests create exceptions.
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 CHS Inc. appears to be adding people
The open roles cluster around store and plant operations, driving and dispatch, and agronomy sales, which is what you would expect from a business that receives grain, delivers fuel, and applies crop nutrients on a tight seasonal clock. This is a read from public postings, not a claim about any one team, but it points to where recurring handoffs tend to pile up.
Open roles reviewed
257
From jobs.chsinc.com and related public postings.
Largest work pattern
123
General & other roles
To a working pilot workflow
14 days
No charge. On-site if useful. Staff approve everything.
257 open roles pulled from jobs.chsinc.com · July 6, 2026
Three problems worth solving
Three problems worth solving.
GENERAL OPERATIONS SUPPORT
The everyday store and plant work carries a lot of repeated coordination.
CHS Inc. has 121 visible open roles in this pattern, including Store Clerk, Agricultural Applicator, and Food Service Clerk. Much of it is Cenex retail and field work where a clerk or lead has to reconcile inventory, deliveries, and customer questions on the spot.
Our point of view
OpenNash can gather context from existing systems, draft the next step, and show staff exactly why the recommendation was made.
Less manual coordination and a clearer view of where work gets stuck.
“Store Clerk”
OPERATIONS, DISPATCH, SUPPLY CHAIN
A stalled shipment should not wait while someone rebuilds the context by hand.
CHS Inc. has 107 visible open roles in this pattern, including Truck Driver/Operations Specialist, Hazmat Truck Driver, and Grain Operations Specialist. These are the people moving grain, fuel, and crop nutrients, where a missed ticket or late dispatch shows up as a truck waiting and a member on the phone.
Our point of view
OpenNash can watch the workflow, gather route, order, inventory, or shipment context, draft the next step, and keep operators in control.
Faster handoffs and fewer unresolved exceptions at shift change.
“Truck Driver/Operations Specialist”
SALES, ORDERS, FIELD SERVICE
Agronomy and field teams lose time turning visit notes into the next step.
CHS Inc. has 21 visible open roles in this pattern, including Outside Sales Representative, Agronomy Sales Representative, and Field Service Technician. Field and agronomy teams spend real hours turning orders, visit notes, and service calls into follow-up work that has to be right.
Our point of view
OpenNash can convert orders, quotes, visit notes, warranty details, and customer updates into reviewed next-step packets.
More time with customers and fewer dropped follow-ups.
“Outside Sales Representative”
How OpenNash would help
A stuck grain ticket or delivery becomes a reviewed, measured workflow.
The first pilot should make one messy handoff visible, reviewable, and measurable without replacing the systems staff already use.
- The handoff stays inside the systems operators already use.
- 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
Grain and agronomy handoffs - tickets, deliveries, work orders, and member follow-ups
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 257 CHS Inc. 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.
257 of 257 roles shown
| Role | Work Pattern | Location | OpenNash Fit | Source |
|---|
No roles match that search.
Pulled from CHS Inc. 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.