AI agent development for business.
Custom AI agents that read documents and emails, extract data, draft replies, and update your systems, with a person reviewing the result before anything important happens.
Approved source
Please move delivery to Friday.
A draft, ready for a person.
Source detail
Delivery change requested: Friday.
Human review
Confirm the record and approve the next step.
Illustrative workflow
From document to reviewed action.
A document-intake agent can prepare the work while a person retains the decision. This example shows the boundaries we define with your team.
- 01 / Input
Receive an approved document.
Read a work order from an authorized source. Keep the original available for review.
- 02 / Proposal
Extract and cite.
Prepare job details with references to the source. Missing or conflicting information becomes an exception.
- 03 / Approval
A person checks the draft.
The reviewer corrects the details and approves the proposed action. Unapproved work stays pending.
- 04 / Outcome
Record what happened.
An authorized integration records the approved update and its result. Failures stay visible for retry or review.
What is an AI agent for business?
An AI agent is software that uses an AI model to read information and complete a defined task using approved data and tools. A business AI agent might sort incoming requests, extract data from documents, draft a reply, research a case, or prepare a recommendation. It should never get a vague instruction and unlimited authority.
QC Devworks builds the system around the model: the actions it may take, the data it may use, test cases, confidence thresholds, an audit trail, and the point where it hands the work to a person. That engineering is what makes AI reliable enough for daily work.
How we build AI agents you can trust.
We define what the agent receives, which data and tools it may use, the evidence it must show, who reviews its work, and when it must stop and ask a person. Some tasks are better handled by ordinary automation, and we will tell you when that is the case.
What we build
An AI agent for one defined task, with approved data sources, tool permissions, test cases, human review, a history of every run, and a documented fallback.
Where it runs
Cloud, on your own servers, or a mix, depending on your data, access, and support requirements. Hosting and AI model usage are separate monthly costs.
What we need from you
Sample tasks, examples of good and bad results, rules for data access and retention, and a person responsible for approving important actions.
What a custom software proposal from us includes.
Before any code is written, the proposal shows exactly what is and is not included.
Scope and acceptance criteria
The users, workflow, screens, integrations, and checks that define a finished delivery, plus the work that is outside the agreed scope.
Access and dependencies
Required data, vendor access, security review, stakeholder decisions, and any data migration or training that affects the timeline.
Launch, ownership, and support
Release and rollback steps, ownership of the code and data, handover, monitoring, backups, and the support arrangement after launch.
What makes an AI agent reliable.
The AI model is one part. The value comes from the data, permissions, testing, monitoring, and workflow around it.
Approved data only
Limit the agent to approved sources, current records, and the information required for its task.
Tested before release
Build realistic test cases, score the outputs that matter, and review failures before and after launch.
A person stays accountable
Send low-confidence, sensitive, or policy-bound decisions to a named person with the evidence needed to decide.
Where should an AI agent start?
Pick a narrow task where reading documents or writing text is the bottleneck, examples of good work already exist, and a person can review exceptions. Use ordinary automation when fixed rules are enough.
- 01
Define the task
Specify inputs, allowed tools, expected outputs, and prohibited actions.
- 02
Build test cases
Use realistic examples, hard edge cases, and clear success criteria.
- 03
Add controls and handoffs
Set permissions, confidence rules, review steps, logging, and safe failure behavior.
- 04
Monitor real performance
Review accuracy, exceptions, speed, cost, and business results over time.
Frequently asked
questions.
How is a custom software project priced?
We define the workflow, deliverables, integrations, acceptance criteria, and dependencies before quoting a build. Hosting, third-party licenses, AI model usage, and ongoing support are listed separately. The pricing calculator is a planning tool, not a project quote.
Do we own the source code and data?
The proposal spells out ownership of the custom code and data, access to the code repository and hosting, and any third-party licenses. Handover includes the agreed documentation and operating instructions. Confirm these terms before work begins.
Can you integrate with our existing software?
Usually. We check the available APIs, permissions, data quality, and vendor limits first. Sometimes a focused integration with a system your team already relies on is more useful than replacing it.
Do you offer software maintenance and support after launch?
Yes. The launch plan names an owner and covers monitoring, backups, recovery, and support. Ongoing maintenance and new features are scoped as a separate monthly plan so recurring responsibilities and costs are clear.
What can an AI agent do for a small business?
Common uses include reading invoices, purchase orders, and forms into your systems; sorting and answering routine email; drafting quotes or replies for review; summarizing documents; and researching a customer or case before a call. Each agent is built for one defined task.
What should not be automated with AI?
Avoid unlimited authority, irreversible high-risk decisions, poorly understood processes, and tasks nobody reviews. If a fixed rule solves the problem reliably, ordinary automation is usually the better choice.
Can you use our private business data safely?
The design can restrict data sources, user access, retention, logging, and what is sent to outside AI models. The exact controls depend on your data, vendors, compliance obligations, and where the system runs, which we review before building.
Sales automation, built the same way.
Three connected systems for teams that need pipeline without turning people into a dialing queue.
Automated Lead Generation
Define the market, verify the data, and deliver a prioritized queue into the CRM your team already uses.
AI BDR & Outbound Sales Agents
Research, preparation, routing, and CRM hygiene with a person approving what goes out.
Automated Appointment Setting
Turn real interest into correctly routed meetings without the calendar back-and-forth.
Related services and pages.
Services
Custom software development, web application development, workflow automation, API integrations, and AI agent development from QC Devworks in Moline, Illinois.
Our Work
Custom software case studies from QC Devworks, including the IntelliSee platform for camera configuration, alert review, reporting, and partner support.
Pricing
What custom software development costs, what drives the price, and a calculator that compares your current software and labor costs with building your own.
Process
How QC Devworks builds custom software: discovery, a written scope and quote, building and testing in reviewed increments, then launch, handover, and support.