Most conversations about AI in eCommerce sound like a choice between two extremes: either you ignore it and fall behind, or you hand the keys to the machine and hope for the best. Lmo7 sits firmly in the middle. We use agentic automation to do the heavy lifting, but humans still make the calls.
For us, “agentic” simply means AI systems that can act with a goal in mind: monitor, decide, and trigger actions across Amazon, DTC and AI search surfaces. The value isn’t in replacing people. It’s in freeing smart people from repetitive work so they can focus on judgement, creativity and strategy.
**What we actually automate**
Across Amazon and AI search, we use automation to:
Collect and structure signals: search queries, category trends, Share-of-Model data, review language, competitor moves.
Run repeatable workflows: weekly AI search audits, prompt testing, listing refreshes, keyword mining, negative keyword hygiene.
Trigger fast reactions: pausing wasteful spend, raising bids on proven terms, surfacing titles that are under-performing in LLMs.
Agents handle the monitoring and “what changed?” questions. Humans handle the “what now?” decisions.
**Where humans still lead**
We keep humans in charge where it matters most:
Positioning and narrative. How your brand shows up in AI search, how it talks, who it’s for. That’s strategy, not automation.
Trade-offs. Do we chase volume or margin, hero SKUs or long tail, Amazon or retail partners? These are business choices.
Edge cases. Compliance, sensitive terms, retail politics, pricing, stock constraints. The things a model can’t see from the outside.
Every automated system we build has a clear owner on the client side. They understand what the agent is doing, what it’s not doing, and how to override it.
**How this looks in practice**
A typical workflow might look like this:
An AI agent monitors your AI search visibility and Amazon performance daily.
It flags products losing “AI shelf-space” on key prompts or slipping in paid efficiency.
It proposes a short list of changes: adjust ad structure, update copy, seed Q&A, refine schema.
A human at Lmo7 and a human on your side review, sense-check and prioritise.
Instead of wading through endless reports, you’re reacting to a handful of high-leverage decisions each week, with clear reasoning behind them.
**Why this approach wins**
Agentic automation with human judgement gives you:
Speed without chaos – fast reactions, but not blind ones.
Consistency – playbooks that run every week, not only when someone has time.
Confidence – you understand how decisions are made and can explain them internally.
We don’t see AI as a black box that magically “optimises” your business. We see it as a fleet of helpful, specialised assistants that surface what matters and leave the final say with you. That’s the version of automation we’re building at Lmo7.