Protect high-trust healthcare workflows.
Customers buy products and systems where uptime, compliance, documentation, and support quality shape renewal and expansion.
OpenNash
Prepared for
Solventum · July 2026
A working hypothesis for Solventum operations and customer-support teams
Help Solventum's field, coding, and support teams close each request with the source record already attached.
Since spinning out of 3M in 2024, Solventum has focused on wound care, infection prevention, dental solutions, and health information systems, all sold into regulated, documentation-heavy healthcare settings. The open roles cluster around field service, medical coding, quality, and sales support, where every answer has to carry its product history, quality record, or regulatory reference. The first useful OpenNash workflow would assemble that context into a reviewed packet so a specialist can decide the next step faster.
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 Solventum workflow we can map in plain English.
Read Zero to Agent
Built by engineers from GoogleMetaSnowflakeDatabricks
Business thesis
Solventum makes money by turning healthcare technology into reliable clinical and operating outcomes.
As a newly independent healthcare company, Solventum’s public thesis is focus: wound care, oral care, and health information systems for regulated customers. Reliability and documentation matter.
Solventum SEC filingsReduce regulated support friction.
Support teams need product history, quality context, customer records, regulatory language, and escalation paths. Agents can prepare the reviewed response packet.
Standardize evidence-heavy work.
A source-linked workflow can help teams answer, document, escalate, and learn without skipping human review where risk matters.
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 Solventum appears to be adding people
The open roles cluster around clinical field support, medical coding and health-information services, quality and regulatory work, and sales operations, functions where context has to move cleanly between systems and people. This is our read of public postings, not a confirmed org chart, so treat it as a starting hypothesis an operator can correct.
Open roles reviewed
395
From healthcare.wd1.myworkdayjobs.com and related public postings.
Largest work pattern
251
General & other roles
To a working pilot workflow
14 days
No charge. On-site if useful. Staff approve everything.
395 open roles pulled from healthcare.wd1.myworkdayjobs.com · July 6, 2026
Three problems worth solving
Three problems worth solving.
GENERAL OPERATIONS SUPPORT
Repeated review work should become a measured workflow.
Solventum has 248 visible open roles in this pattern, including Acute Wound Healing Specialist (Pensacola, FL), Product Owner, and Manager, Events & Healthcare Conferences. That points to repeated work where context has to move cleanly between people and systems.
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.
“Post-Acute Wound Healing Specialist (Pensacola, FL)”
SALES, ORDERS, FIELD SERVICE
Sales and field teams lose time turning messy notes into next steps.
Solventum has 61 visible open roles in this pattern, including Inside Sales Representative (CST, MST or PST), Dental Practice Sales Specialist (Los Angeles), and Field Service Representative I - Lenexa, KS. That points to repeated work where context has to move cleanly between people and systems.
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.
“Inside Sales Representative (CST, MST or PST)”
SOFTWARE & IT QUALITY
Evidence work should be assembled before it reaches the reviewer.
Solventum is hiring across software and IT quality, including IT Quality and Testing - Automation Specialist and Principal Software Quality Assurance Engineer. These roles turn scattered test records, defect logs, and release checks into decisions someone has to document and defend.
Our point of view
OpenNash can collect source records, compare them to standard work, and prepare an exception packet with an audit trail.
Cleaner reviews, fewer missing fields, and a better record of why decisions were made.
“IT Quality and Testing - Automation Specialist”
How OpenNash would help
Turn a recurring operating exception into a reviewed, source-linked workflow.
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
Solventum reviewed operating exception workflow
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 395 Solventum 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.
395 of 395 roles shown
| Role | Work Pattern | Location | OpenNash Fit | Source |
|---|
No roles match that search.
Pulled from Solventum 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.