17 sep
|
Allie - Ai For Manufacturing
|
Xico
17 sep
Allie - Ai For Manufacturing
Xico
About us We build AI agents for manufacturing.
Allie integrates intelligence into factory operations: learning from machines, sensors and systems to detect problems, recommend actions and coordinate responses in real time.
Our platform connects to PLCs, MES and ERPs through secure edge gateways.
It transforms raw data into operational decisions that improve availability, quality and throughput.
We work with large manufacturing groups in the food, beverage and CPG industries deploying AI agents that embed into production lines and scale across sites.
Allie is built to act, not just report.
From real-time monitoring to autonomous control, we help your factory think and self-optimize.
Sales, rebuilt as an engineering discipline.
One operator, one agent stack, the entire revenue machine — for an AI company selling into the factory floor.
FULL-CYCLE · AI-NATIVE · BUILD THE MACHINE, OWN THE NUMBER 01 · THE THESIS This role didn't exist three years ago The old playbook — hire SDRs, buy twelve tools, pray the CRM stays clean — is being replaced.
In its place: one or two operators who build the machine instead of being the machine.
They map the ICP and TAM programmatically.
They watch every named account for signals and react the same day.
They run outbound, inbound, events, and deal support as maintained systems, not repeated tasks.
They spawn agents that verify their own output and loop until the outcome is achieved.
And they do it for a fraction of what the equivalent sales-tool stack costs.
The profile is scarce: full-cycle sales fluency, technical instinct, and AI-native operation rarely live in the same person.
This charter exists because Allie runs GTM this way — and is looking for the operator who wants to own it.
02 · THE ROLE One operator, the entire top-of-funnel Allie sells an operational copilot to Tier-1 manufacturers.
The buyers are plant directors, VPs of operations, and CTOs at general brewers, food producers, and CPG companies — people who don't respond to spray-and-pray.
They respond to precision.
This is not an SDR job and not a marketing job.
It is one operator running the entire acquisition machine as a system: every list, every signal, every sequence, every call, every event, every piece of reporting — designed, automated, and maintained by you, with Claude Code and a small set of external APIs doing the work a six-person growth team used to do.
You own the number that matters: qualified hand-offs to technical sales.
Everything below exists to feed it.
03 · WHAT YOU OWN Six systems, one owner SYS 01 · ICP refresh continuously, not quarterly Track every champion who changes jobs and route them as a new account Own CRM architecture and reporting — pipeline truth lives here, and it is your truth to keep clean SYS 02 · Signals you run those end to end and build the calendar forward from what they produce Pre-event: named-account target list per show, booking sequences 4–6 weeks out, meetings landed before the doors open — a booth with no calendar is a cost center On-site: every conversation captured into CRM same-day with context, not badge scans Post-event: 100% of captured contacts in sequence within 48 hours; qualified ones handed off within a week Report pipeline generated per event and kill the events that don't pay for themselves SYS 06 · Deal support Rooster is where it lands.
Every workflow is a system you build once and maintain, not a task you repeat.
You spawn subagents that verify their own output, you loop until the outcome is achieved, and you treat "I did it manually" as a bug report against your own tooling.
Nothing client-facing auto-sends.
You review and approve every external touch.
Automation buys you volume; judgment is still the job.
05 · WHO YOU ARE Three non-negotiables TRAITWHAT IT MEANS HERE Full-cycle sales fluency You understand the whole cycle — prospecting through close through expansion.
You've carried a number, or sat close enough to one to feel it.
Technical by instinct You can read an API doc, reason about a data model, and debug your own workflow at 11pm before a launch.
You may not call yourself an engineer; you build like one.
Al-native operation You run AI as an operating discipline — agents that verify their output, loops that run until the outcome is achieved, workflows that cost a fraction of the equivalent SaaS stack.
Strong signals: you've built a growth system solo that a team later inherited; you've sold into manufacturing, industrial, or another long-cycle technical buyer; you've worked an event circuit and can show pipeline per show, not photos of the booth.
06 · THE FIRST 30 DAYS The engine gets built.
All of it.
Not phased, not sequenced, not "foundations first."
By day 30, every system above is live: ICP universe in CRM, signal watching running, mail infrastructure warm and sequences shipping, the calling engine dialing, inbound pipeline producing, event calendar locked with meetings booked, pre-call briefs generating for every calendar meeting.
Built locally with Claude Code, migrating into Rooster as each workflow proves out.
From day 31, the conversation is results.
The measurement framework already exists — a weekly growth scorecard, built and run by the CRO, with qualified hand-offs and closes as the north star.
You don't design the measurement system; you feed it.
07 · WHERE THIS GOES The machine you build becomes the org you run This role grows into technical sales leadership: managing both the growth function and the technical-sales AEs who carry deals from demo to close.
The path is direct — first you build the acquisition machine, then you own the people and the machine together.
Most companies split this work across six tools and four people.
Here it is one operator, one agent stack, and full ownership — and the ceiling on the role is whatever you make the machine capable of.
📌 The Gtm Engineer (Xico)
🏢 Allie - Ai For Manufacturing
📍 Xico