Enterprise AI advisory
Aevum Cognitive helps mid-size manufacturers and CPG brands find where AI pays off, build agents on the systems they already run, and train their teams to keep it going.
From data to working agents
How an engagement works
Every engagement begins with one process, a clear owner and a measurable outcome. Scope is agreed before anything is built.
01 / Understand the work
Find the slow step
Map the process, the people and the systems, and find the step where time is lost.
Decide what the agent does, what data it can touch, and where a person approves.
Run the agent on real cases, on your existing tools, with the people who will use it.
Hours saved, errors avoided and an honest view of whether to expand.
Extend to more sites or the next workflow, and train the team that owns it.
What we do
We help you decide what is worth doing, put agents into production and train the teams that run them.
We sit with your teams, see how the work really runs, and pick the few places where AI clearly pays off, each with a target set up front.
Agents that work on top of Oracle, SAP or your spreadsheets, connected to your contracts and SOPs. The agent drafts and flags; your people approve.
Leadership sessions and hands-on workshops with Claude, ChatGPT and Copilot on real work from your business, so your people can carry on without us.
Our work
Renora, our own product, and the agents we build for supply chain and CPG teams. Pick one to see how it works.
Our productIn development
A kidney wellness app for people living with chronic kidney disease or on dialysis.
Renora helps with the day-to-day. Patients log meals and fluids, see what still fits the limits their care team set, and note how they feel. Its assistant, Nira, answers everyday questions between appointments. Before each visit, it puts together a clear summary for the care team, who make the final decisions.
Prototype screens with example information.
Supply chain planning
A late purchase order sends a planner through the ERP, the inbox and a round of calls just to learn what happened. The agent does that legwork first.
When the ERP flags an exception, the agent pulls the order, reads the supplier's latest emails, checks stock at every site and finds the customer orders at risk. The planner gets the cause, the impact and two or three options with their cost. Once the planner picks one, the agent emails the supplier and updates the ERP.
Example data
CPG sales
New retail accounts open up in short windows: a category reset, a store expansion, a new buyer. Most brands notice after the shelf plan is already set.
The agent watches retailer news, category review calendars, store openings, distributor announcements and buyer moves. It matches each signal to your categories, ranks the accounts worth calling this week and finds the right buyer. Then it drafts a first note that gives the reason to talk now. Your team reviews the note and sends it from the CRM.
"Ahead of your March snack reset, here is how our sea salt line performed in comparable Texas stores…"
Launched a natural foods division last month
Adding better-for-you snacks at checkout
Example data
CPG pricing
Your prices and your competitors' change every day across Amazon, Walmart, Target and grocery sites. Most brands hear about it in a weekly report, or from a buyer.
The agent checks every listing in your category several times a day, including your products, your competitors' and private label. It flags price cuts, promotions, out-of-stocks and listings below your minimum advertised price, and shows what each change does to your price gap. Then it suggests a response for your pricing team to decide on.
Example data
About
Aevum Cognitive is an independent AI advisory in Naperville, Illinois, for mid-size manufacturers and CPG brands whose work runs through ERP systems, spreadsheets and inboxes. We are not tied to a software vendor, so the only question is what pays off for you: a late order caught in time, a promotion that earns its spend, a team that can run the agent after we leave.
Founder
Enterprise by design
Guardrails are agreed with your team before implementation, not added later.
Data access, providers and deployment requirements are set before any build.
Actions with real consequences wait for a person to approve them.
Integration starts from your current ERP, APIs, data and security rules.
AWS, Azure, OpenAI or Anthropic, chosen to fit the work.