Agent
01One job
A clear role, approved information, and a result a person can review.
Practical AI implementation for Central Ohio businessesFind · Build · Train
What could AI actually do for your business?
We find where AI can make money, save time, or make difficult work easier—then build it with your team.
Based in Columbus · Led by an engineer · Built around the way your team works
Repeated
Scattered
One expert
One useful workflowBuilt around the real work
More revenue
Time saved
Easier work
We compare value, available information, risk, and how your team can check the result.
Stories from the workReal projects · Client details removed
See how useful AI is built—one real problem at a time.
Four real problems. Four different systems. Every result stays connected to something a person can check.
01 · Industrial operations
Built for a client
The margin nobody trusted.
A pricing question should not trigger another round of spreadsheet archaeology.
Do not use AI to guess what the business can calculate.
Read the story02 · Civil and environmental engineering
Being built now
The process estimate that took too long to explain.
The answer was not in one file. Neither was the reasoning behind it.
A trustworthy system makes disagreement visible.
Read the story03 · Advisors and insurance
Built for a client
The carrier PDF that slowed down every client meeting.
The advisor knew how to guide the client. First, someone had to find and check the numbers.
For important work, every answer needs a way back to the source.
Read the story04 · Innovation and patents
Built for a client
The patent search that was hard to check.
A confident answer was not enough. The company needed the evidence behind it.
Good AI research preserves both the source and the uncertainty.
Read the storyThe First Project ReviewChoose before you build
One problem. Four decisions before anyone builds.
We look at the work, compare the opportunity, and recommend the smallest sensible next step.
Listen
01Bring us the list
The tasks that waste time, cause rework, or depend on one person.
Observe
02Watch the real work
Including the exceptions and workarounds a process chart misses.
Compare
03Test the opportunity
Value, available information, risk, and how the result will be checked.
Recommend
04Choose the next move
Build, buy, wait, or leave the process alone.
ExperienceJeff Myers, founder
Three decades in engineering: R&D leadership, manufacturing, product development, and IP.
Products taken from concept to market in medical devices, industrial equipment, and materials.
Granted and pending patents, written from the drafting side of the table.
A pattern we keep findingDifferent businesses · Similar problems
The details change. The pattern is often the same.
Important work is repeated, scattered across systems or documents, dependent on one person, or hard to check. We look for that pattern, solve one useful part, and only expand after it works.
Example from Industrial Operations
01A number the team kept rebuilding by hand
The facts existed in the company's systems, but the calculation lived in one person's spreadsheet. The first project made the result repeatable and easy to check.
Does this sound familiar?
What important number does your team rebuild or debate because the calculation lives outside the main system?
Example from Civil & Environmental Engineering
02A result that took too long to explain
The evidence was spread across systems, workbooks, and email. The first project connected the result to the information and decisions behind it.
Does this sound familiar?
What result takes too long to explain because the evidence is spread across files, systems, and email?
Example from Advisors & Insurance
03A document that slowed down every client conversation
Important values had to be copied from a long document before each meeting. The first project put them into a clear plan that a person could review.
Does this sound familiar?
What client conversation begins with copying information from a long document or several different sources?
Example from Innovation & Patents
04Research that had to be done again and again
Earlier answers were hard to check, update, or reuse. The first project turned the sources and findings into a searchable record.
Does this sound familiar?
What research has to be repeated because the last answer is hard to check, update, or reuse?
These examples are here to help you recognize the pattern. Your first project may come from a completely different part of the business.
Browse the examplesHow the solution growsAgent · Tools · Reuse
One useful agent can become a capability the next agent can use.
Start with one job. Improve it with real work. Reuse only what proves useful.
Improve
02Real corrections
Examples, exceptions, and expert judgment improve what happens next.
Tools
03Limited tools
Approved ways to search records, run calculations, or prepare work.
Reuse
04Reusable access
Future agents use the proven workflow without starting over.
What MCP means here
A safe connection to a proven tool.
MCP gives an agent a standard way to use an approved tool. The same access rules, source links, and review steps travel with the workflow. The agent gets the capability—not the password.
See how access and data are controlledChecking the workA rule for every project
You should be able to check every important number.
Open the source, inspect the rule, and see how the answer was produced.
Trusted sourceOpen the input
Visible rulesInspect the math
Checkable resultA person approves
Privacy & dataAgreed before work begins
You should know where your data goes.
Before work begins, we agree on access, processing, retention, deletion, and human review.
01
Your information
Documents, systems, and records
02
Limited access
Only what the task needs
03
Business AI service
Not a consumer account
04
A person checks it
Before an important action
Client content is not used to train public models. One client's information is never added to another client's tools.
See where information is stored, who processes it, how deletion works, and our current security limits.
Read about data and privacyTrainingLearn by doing real work
The tool only helps if your team knows how to use it.
People learn on work that is already due: what to give the AI, how to check it, and when to take over.
Real task
AI draft
Person checks
Improve
QuestionsPlain answers
Questions business owners ask before starting.
Need more detail? Read the data and privacy page.
What does upStreamLLM actually build?+
We build tools for reports, calculations, research, customer service, and other repeated business tasks. We can connect them to the software your team already uses. We start with one problem, not a generic chatbot.
Will our data be used to train a public model?+
No. We use business AI services whose terms say customer inputs and outputs are not used to train public models. We also do not use one client's information to improve another client's system. Before work begins, we document the providers, storage, access, and deletion rules for your project.
Do we need to know what we want to automate?+
No. Bring one problem or several. The First Project Review compares the value, frequency, available information, risk, and how easily people can check the result before we recommend what to do.
Is training available without a software build?+
Yes. We offer sessions for business owners, teams, and the person who will lead AI use inside the company. Training works best when people bring a real task and deadline.
How do you keep AI output trustworthy?+
We limit the information the AI may use, show its sources and assumptions, and have a person review important work. Regular calculations are handled by tested code when possible. Important numbers open to the original data and math behind them.
Who is the best fit?+
We are a good fit for small and midsize businesses with important work that is still handled by hand, in spreadsheets, or by one busy expert. We know industrial, engineering, advisory, insurance, and patent work especially well. If software you can already buy solves the problem, we will tell you.
Choose before you buildCentral Ohio
You do not need to know what to automate.
Tell us what is slow, repeated, expensive, or hard to check. We will compare the opportunities and explain which one deserves to come first. You do not need a presentation or a finished plan.