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AI for Operations

Automate the operational work that doesn't scale.

Order processing, vendor management, scheduling, exception handling, reporting — we connect your systems and put an AI layer on top so your ops team manages by exception instead of doing everything by hand.

ERP · spreadsheets · email · Slack · APIs · human-in-the-loop on exceptions

Operations scales with headcount — until it can't.

When volume doubles, ops teams usually hire. But much of operational work is rules plus judgment on the edge cases — the rules are automatable, and AI is good at triaging the edges.

We automate the predictable middle of your processes and route the genuine exceptions to a person with full context. The result is a team that manages by exception: the routine flows through untouched, and human attention goes to the cases that actually need it.

How we approach an ops process.

01

Map the process

We trace the real workflow — including the undocumented steps and the spreadsheet glue.

02

Separate rules from judgment

Identify what's deterministic (automate) versus what needs a human (route).

03

Connect the systems

ERP, spreadsheets, email, and SaaS wired together via secure integrations.

04

Automate the middle

The routine path runs end-to-end with validation and logging.

05

Exception queue

Edge cases land in a fast review UI with AI-drafted recommendations.

06

Monitor + expand

Track throughput and error rates; automate the next process once one is proven.

Common operations wins.

Orders

Order + fulfillment ops

Process, validate, and route orders; flag the ones that need a human.

Vendors

Vendor + procurement

Onboarding, document checks, and PO matching with approvals.

Data

Data entry + reconciliation

Eliminate manual re-keying between systems that don't talk.

Scheduling

Scheduling + dispatch

Optimize and automate scheduling with constraints and exceptions handled.

Reporting

Operational reporting

Auto-generated ops reports with AI commentary and anomaly flags.

Support

Internal request handling

Triage and fulfill internal requests across teams.

Ways to engage.

One Process
3–6 weeks
from $24,000
  • One workflow automated
  • System integrations
  • Exception queue + audit
Start a Process
Ops Platform
8–12 weeks
from $70,000
  • Multiple processes
  • Shared integrations + copilot
  • Monitoring + controls
  • 30-day support
Plan a Platform
Embedded Team
monthly
from $13,000/mo
  • Ongoing automation
  • Backlog with your ops lead
  • Weekly releases
Discuss a Team
Show, don't tell

Automate the middle. Route the exceptions.

The routine path runs untouched; genuine edge cases land in a review queue with an AI-drafted recommendation.

process.tstypescript
for (const order of await intake()) {  const v = validate(order, rules)  if (v.ok) {    await fulfill(order)                       // routine path — no human  } else {    await queue.exception(order, v.reasons, { suggest: recommend(order) })  }}
Run summary
processed: 612 · auto-fulfilled: 587
exceptions queued: 25 (with recommendation)
throughput: 4.1× manual baseline

Your team manages by exception — the predictable volume flows through, and human attention goes only where it's actually needed.

Start where it's undocumented

We map the real process — spreadsheet glue and all.

Most operations run on an undocumented workflow held together by a power-user and a 40-tab spreadsheet. That's our normal starting point.

We separate the deterministic rules (automate) from the judgment calls (route to a human), then prove throughput gains before expanding.

Automate operations

Common questions.

Our process is messy and undocumented — can you still help?
That's the normal starting point. Part of our work is mapping the real process, including the undocumented steps, before automating it.
What happens to the edge cases?
They route to a fast review queue with AI-drafted recommendations and full context, so a human resolves them quickly instead of doing everything manually.
Do you replace our ERP?
No — we connect to and orchestrate across your existing systems. We add the automation and intelligence layer on top.
How do you prove ROI?
We baseline throughput, error rate, and hours spent before rollout and report the change. We expand only on proven wins.

What process would break if volume doubled?

Tell us the operational workflow that's most manual today. We'll show you what automating it looks like.