AI employees for operational and back-office work
Code Quarry builds AI employees.
If I could give you additional employees without adding to your payroll, what would you have them do?
Your systems keep the information. Your AI employees carry the work. Your people get their attention back.
Where Code Quarry fits
The work between your systems is stealing the day.
Your systems may already be excellent. They hold the information and perform their specialized functions. But people are still reading, checking, entering, coordinating, and following up before, after, and between them.
The work between your systems
This is where the day goes.
Every email, document, comparison, update, and follow-up competes with the work that actually needs your people.
- Existing systems hold the information.
- AI employees do the work.
- People provide judgment and relationships.
What changes
A better business feels different.
The benefit is not more technology. It is what your people and your business can do when routine work stops consuming the day.
Capacity without automatic headcount01Save operational cost
Reduce unnecessary manual labor and operating cost. Add capacity without automatically adding payroll, so the business can grow without adding back-office headcount at the same rate.
More of the work people are best at02Give valuable people their time back
Give teams hundreds or thousands of hours back each year so good people can focus on customers, judgment, growth, relationships, and higher-value work.
Nothing important quietly slips by03Catch revenue slipping through the cracks
Continuously monitor follow-up, changes, delays, exceptions, collections, renewals, bids, quotes, and opportunities. Act quickly or alert the right person before money is missed.
The economic story
Do the math.
Who, times minutes, times frequency. Put in one process your people run by hand and see what it costs today.
3 people × 20 minutes × 40 times a week × 50 weeks, at $38 an hour. This is your number, from your inputs. It is the cost of the work as it runs today, not a prediction.
Market context: A fully burdened back-office employee often costs near $80,000 a year in service businesses.
The capacity question
What if volume doubles?
Before you add another person or automatically backfill an open role, look at the work. An AI employee may be able to absorb enough of it that your current team can handle more without adding the same payroll cost.
Manual back office
4peopleWhen the work is manual, every step of volume adds a step of headcount. At 1x, the same process needs about 4 people.
With AI employees
1personThe AI employees take the added volume. A person still handles judgment, approvals, relationships, and the exceptions that need one.
What happens to this process if your volume doubles?
If doubling volume requires doubling the back office, the business has an operational leverage problem.
The human advantage
People show up where they matter most.
AI employees handle the repeatable work inside your guardrails. Your people keep the judgment calls, approvals, relationships, and moments that deserve a human being.
“The machine handles the repetition. The person owns the moment.”
How we work
Three phases, from first look to a running AI employee.
- 1We prove what is worth doing together.
- 2We build it with you.
- 3We operate and improve it for you.
Nobody is asked to buy a proposal for work they have not seen quantified, and nobody is left running the AI on their own after launch.
- 1
Prove what is worth doing
Feasibility and business case
We come in and watch how the work actually happens. Together, we identify what an AI employee can realistically take over, where a person still needs to be involved, and what the opportunity is worth.
Step 1Watch the work
See how the process actually happens. The people closest to the work share their screens and walk through the real systems, handoffs, documents, decisions, exceptions, and workarounds.
You getA clear picture of where people are carrying work around and between the systems you already have.
Step 2Find the work
Identify the costly operational work that AI employees and automation can take over.
You getA short list of the work worth taking off your people, in your own vocabulary.
Step 3Do the math
Quantify the current state: who, times minutes, times frequency. Also delays, error risk, capacity limits, missed revenue, cash trapped, and what happens when nobody catches an exception.
You getThe cost of the work as it runs now, in numbers you can check against your own operation.
Before we recommend a build, we confirm the work is technically and operationally feasible, and we put a number on the cost, time, capacity, or revenue opportunity.
- 2
We build it with you
Collaborative build
Code Quarry owns the design and build, while working closely with your team to make sure the AI employees fit your operation. Your people help define the rules, exceptions, approvals, and human boundaries. We test the work together before launch.
Step 4Build the employee
Design what the AI employee will understand, decide, do, communicate, monitor, and escalate. Keep deterministic rules deterministic. Keep people responsible for judgment, approval, relationships, and high-risk exceptions. Then build it around the systems already in place.
You getWorking AI employees, integrated with your existing tools and tested against criteria you agreed to up front.
Code Quarry
- Design and build the AI employees
- Handle the technical work, integrations, and testing
- Fit the result to how the business actually operates
Your team
- Share how the work really happens
- Define the rules, exceptions, and approvals
- Decide where a person stays involved
- 3
We operate and improve it for you
Managed AI partnership
After launch, Code Quarry stays responsible for watching, validating, improving, and proving the performance of your AI employees. You stay focused on the business. We make sure the AI employees keep doing the job they were built to do.
Continuous monitoring, weekly validation, tested changes, monthly improvement, and a written report that proves the value.
The managed AI partnership
You are in good hands after launch.
Code Quarry stays responsible after launch, so managing the AI does not become another job for your team.
Once your AI employees go live, you should not have to wonder whether they are still working the way they should. Code Quarry continuously watches performance, validates real work every week, tests changes before they reach production, and improves the system each month. You stay focused on the business. We stay responsible for the AI employees.
Software, models, business rules, documents, and real-world inputs change over time. That is exactly why the partnership exists. Our operating process catches changes early, corrects them, and keeps performance within the agreed expectations before they quietly become your problem.
Hover or select each commitment to see it in practice.
We monitor availability, errors, integrations, exceptions, performance, security signals, and operating cost, so anything unusual is seen by us first.
Every week we audit samples of real work, confirm the output is right and the tasks are complete, look into exceptions, and adjust workflows, prompts, rules, or data before small drifts become visible to your customers.
Model, software, rule, and integration changes are tested before they reach production, versioned, and kept reversible, so an update never surprises your team.
We use what we learn in production and reserved monthly capacity to improve quality, performance, cost, usability, and controls, or to take on the next highest-value part of the workflow.
Every month you get it in writing: what the AI employees did, the value they created, what exceptions came up, what we handled, and what we recommend next.
If nothing needs fixing, Code Quarry does not sit idle. That month's capacity goes toward testing, optimization, cost reduction, documentation, security review, roadmap analysis, and visible improvement.
You are not paying us for repair hours. You are paying us to make the performance of your AI employees our responsibility instead of yours.
Every month, in writing
- 1Work completed by the AI employees
- 2System reliability and task-completion performance
- 3Exceptions and human escalations
- 4Issues detected and resolved
- 5Output quality or accuracy measures
- 6Infrastructure and model cost
- 7Estimated time, cost, or revenue impact
- 8Improvements completed that month
- 9Recommended next priority
The recurring relationship must produce its own evidence.
Three ways to work together
- Managed OperationsRun the supported systems.
For stable, lower-complexity systems that mainly need reliable operation.
- Managed Intelligence PartnershipRun it, prove it, and improve it.
The recommended relationship for active systems that will continue evolving.
- Strategic Intelligence PartnershipOperate and advance the AI roadmap across the business.
For clients who want Code Quarry to act as an embedded AI operating and strategy function.
The signed statement of work controls scope, term, usage limits, and service commitments. The right relationship depends on what the AI employees are expected to save, find, or protect, so the place to talk about it is a conversation.
Industries
Different systems. The same work between them.
The core message does not change by industry. Only the examples change.
Transportation & Logistics
3PLs, fulfillment, brokerages, carriers, and warehousing. The WMS and the TMS do their jobs. AI employees handle the operational work happening around them.
WMS, TMS, email, phones, customer and carrier communication, documents
Trades & Construction
The work before, during, and after the job: chasing information, moving field updates to the office, and getting completed work billed and paid.
estimating, project management, field operations, accounting, customer communication
Other Operations-Heavy Businesses
Distribution, property services, manufacturing, professional services, and other businesses where good people still carry work between systems.
different software, the same manual work between systems
The people behind the work
Built by people who understand both sides of the room.
Code Quarry brings together operating leadership, product strategy, enterprise architecture, and hands-on engineering. We have run operations inside real businesses and we have shipped software that holds up in production, so we can find the real work and build something dependable around it.
- 01
Operating leadership
Years running operations inside real businesses, the side of the problem most technical teams never see.
- 02
Product and strategy
Turning messy operational reality into clear, buildable systems with a measurable result.
- 03
Enterprise architecture and engineering
Building dependable software and integrations that hold up in production.
The range
Simple automations
A single handoff that should never have needed a person: a document that gets read and filed, a follow-up that gets sent, a record that gets updated.
AI employees
A complete process run end to end: understanding requests, gathering information, deciding within your rules, acting across your systems, and bringing in a person when needed.
Custom software
Interfaces, integrations, and deterministic systems built when the work needs something your existing software cannot do.
The same team covers all three. The work decides which one you need.
Your first step is a conversation.
Let's talk about the work.
A practical conversation about where your people are doing manual work today, and whether AI employees can take it over.