# Athos — full brief

> Forward-deployed engineering for manufacturing and logistics. AI and ops systems on the plant floor.

Source of truth site: https://www.athosinfra.com  
Contact: graham@grahamfleming.com (Graham Fleming)

## One-liner

Athos implements AI and ops systems on the plant floor — on systems manufacturers already run. No rip-and-replace. Start small, prove value, ship something that holds up mid-shift.

## Problem

Industrial ops still run on paper, tribal knowledge, and brittle glue between ERP / WMS / MES / email and the floor — even when the machines are modern.

- People burn shifts on retype and spreadsheet chase.
- When a line stops, docs are hunted instead of found.
- Status, recalls, and exceptions get reconstructed from binders after the fact.

## How engagement works

1. Short call — hear the plant and the painful workflow; decide if paid discovery is worth it.
2. Paid floor discovery (days to ~2 weeks) — walk the flow; map systems/paper/tribal knowledge; name one workflow, success metric, and fixed build quote.
3. On-site pilot (~4–6 weeks; one-time fee) — ship one painful workflow; working software mid-engagement; no obligation to expand.
4. Optional expand — more role apps on the same data model; light retain for connectors, model refresh, new workflows.

CTA: short call → paid discovery. Not “buy a platform.”

## Dual arcs (in order)

1. Digital foundation: paper → station capture → connect ERP/WMS/QMS/email → machines/sensors/cameras where it pays.
2. AI on that foundation: cited search → agents that draft/act with approval → scheduling / quality / shortage intelligence.

Never sell Arc 2 without a credible path through Arc 1 for that site.

## Example capabilities

Mapped to customer pain after discovery — assemble commercial, enterprise, and open-source tools on their stack:

- Station capture / kill paperwork retype
- Live ops visibility (line / dock / cold room)
- Plant search with citations (SOPs, quality, ERP/WMS, docs)
- Order / inventory exception queues
- Scheduling & quality assist (planner approves)
- Traceability / lot genealogy
- Edge inference + computer vision (inspection, labels, dock OCR) when it pays

## Who it’s for

Mid-size manufacturing, packaging, logistics / 3PL, food / cold chain, wood / industrial — physical ops + software glue.

Primary geography: Vancouver / Lower Mainland → BC → similar plants in Canada / US.

Not a fit for: pure tech startups, vanity AI demos, multi-year digital transformation theater, or full ERP/WMS rip-and-replace as the default pitch.

## Principles

1. Go on-site — start on the floor
2. Start small — prove value first
3. Only win if they win
4. Remove busywork, not people — humans stay in the loop
5. No rip-and-replace by default
6. Ship where it’s used — mid-shift must work
7. Cite, then act — agents propose; people approve
8. Built for legacy / family / mid-size plants — not consultant dashboards

## About

Athos is led by Graham Fleming — a forward-deployed engineer who sits with operators and ops leads, hears the real work, and ships hard technical systems (AI implementations, infrastructure, and glue that has to hold up mid-shift).

Early-stage and honest. No fake case studies. Prefer paid discovery, fixed-scope pilots, and working software over decks.

## Contact

- Email: graham@grahamfleming.com
- Site: https://www.athosinfra.com
- LinkedIn: https://www.linkedin.com/company/athos-ai
- X: https://x.com/AthosAI
- GitHub: https://github.com/athos-engineering