Custom software · responsible AI · managed for your business

AI won’t care when the details are wrong. We will.

SimpleBiz builds, improves, secures, and manages software and AI systems for businesses that need the work to keep working—even when the model, provider, or process does not.

Start with an email. Scope, timing, support, and pricing are agreed before any paid work begins.

The machine can move faster than your team can review.

It can generate a thousand plausible answers without caring whether one harms a customer, exposes private data, or quietly breaks the process. Your business still owns the outcome. We help you make that responsibility practical—without asking your team to spend years learning every failure mode first.

Ways SimpleBiz can help

Bring the business problem, the rough build, or the system already in use.

Each engagement is scoped around the current state of the work. You do not need to know the right technical label before starting the conversation.

01BUILD

Custom business software

Turn a recurring business problem into software your team can actually use.

We map the people, information, decisions, and exceptions around the work, then build the smallest dependable system that improves it.

Discuss a custom system →
Common starting points
  • Internal tools and operations portals
  • Customer or partner workflows
  • System integrations and process automation
  • Reporting, intake, and approval systems

Good fit when: the current work depends on spreadsheets, repeated copying, scattered tools, or knowledge held by one person.

02POLISH

AI project finishing and hardening

Take the AI project that almost works and make it ready for real work.

We review the workflow, code, prompts, permissions, data, interface, and failure states—then fix what blocks safe, maintainable use.

Request a project review →
The polish pass can cover
  • Prompt, model, and workflow evaluation
  • Source checking and output validation
  • Permissions, secrets, and safe data handling
  • Failure recovery, testing, and documentation

Good fit when: the demo is promising, but you would not yet trust it with a customer, employee, or important decision.

03SECURE

Responsible AI workflow design

Give every AI capability an explicit boundary.

We define what the system may read, suggest, write, or trigger—and where human approval, evidence, or a hard stop is required.

Review an AI workflow →
Controls made concrete
  • Least-necessary data and system access
  • Human review for consequential actions
  • Visible sources, uncertainty, and audit trails
  • Safe behavior during outages and exceptions

Good fit when: AI touches customer communication, sensitive information, approvals, money, or operational decisions.

04MANAGE

Ongoing software and AI care

Keep the system healthy after the launch announcement is over.

We agree what matters, watch the important dependencies, handle fixes and security updates, and make deliberate improvements as the business and tools change.

Discuss ongoing support →
Managed work may include
  • Monitoring and incident response
  • Security and dependency updates
  • Model, provider, and workflow changes
  • Documentation and recovery procedures

Good fit when: the system matters enough that “find someone when it breaks” is not an acceptable support plan.

Reliability is designed before the incident

When something goes wrong, everyone should know what happens next.

Responsible AI is not a promise that the model will always be right. It is a system that recognizes uncertainty, limits damage, preserves the work, and returns authority to a person.

Example: provider returns an unreliable resultSAFE RESPONSE
  1. 01
    Stop the consequential actionThe draft is held instead of sent or applied.
  2. 02
    Preserve the request and evidenceInputs, sources, output, and system state remain available.
  3. 03
    Notify the responsible personThe right operator receives context, not a generic error code.
  4. 04
    Recover deliberatelyRetry, use an agreed fallback, correct manually, or leave the work paused.

What 9,000+ hours changes

We have seen enough AI output to be impressed—and suspicious.

01

A convincing answer is not evidence.

We check important claims against the available source and make missing support visible.

02

More autonomy creates more ways to fail.

We expand permissions only when the value is clear and the action can be observed, stopped, and recovered.

03

The model is only one dependency.

APIs, permissions, data quality, interfaces, people, and changing business rules usually matter just as much.

04

Someone must still own the outcome.

We make human authority, operating boundaries, and support responsibilities explicit.

About the usage figures: 9,000+ hours and 3B+ tokens describe SimpleBiz’s accumulated hands-on use of AI tools across software, research, content, and business work. They are experience measures, not a claim that usage alone guarantees a project result.

A visible path from problem to ownership

No black-box handoff.

  1. 1
    UnderstandMap the work, people, risk, and useful outcome.
  2. 2
    ScopeAgree deliverables, timing, support, and price.
  3. 3
    Build & testReview working slices and realistic failure paths.
  4. 4
    Launch & ownDocument operation, recovery, and next responsibility.

Before you contact us

Practical questions deserve plain answers.

Do I need to know exactly what should be built?

No. Describe the work that is slow, unreliable, confusing, or dependent on one person. The first conversation is used to understand the problem before recommending a technical approach.

Can you work with an AI project someone else started?

Yes. A review can begin with existing code, a no-code automation, a prototype, prompts, documentation, or the workflow itself. We will first establish what is inspectable and what access is appropriate.

Do you use AI everywhere?

No. We use AI where its uncertainty is acceptable and its value is concrete. Deterministic software, a simpler workflow, or no new software at all may be the better answer.

What happens before I pay?

We discuss the problem and determine whether there is a plausible fit. Scope, deliverables, timing, price, payment terms, cancellation terms, and support boundaries are agreed before paid work begins.

What happens after launch?

The agreement defines what is documented, handed over, monitored, or managed. Ongoing care can be included when the system needs a responsible technical owner after launch.

Commercial and messaging information

Clear terms before work begins.

These summaries keep the basic service terms visible. The full policies remain linked below.

01

Professional services only

Simple Biz Software Solutions provides custom software, AI, and technology consulting services. We do not sell physical goods.

02

Payment and refunds

Contracts are negotiated up front. Payments and deposits are non-refundable once agreed unless a signed agreement states otherwise.

03

Cancellation

Work must be canceled before the project or engagement begins. Once work has started, the full agreed payment amount is due.

04

SMS messages

Clients may consent to engagement-related reminders, project updates, and billing notices. Frequency varies; message and data rates may apply. Reply STOP to opt out or HELP for help.

Start with the work, not a sales script

What does your business need to depend on?

Email the rough description. We will ask the questions needed to understand the work and tell you plainly whether SimpleBiz is a sensible fit.

Project conversations begin by email.

nicholas@simplebizsoftware.com →No payment or commitment is required to start the conversation.