01
Only two people can actually produce the result
The method lives in a spreadsheet, several applications, or one person's head. It is an asset the business depends on, but where it lives is a risk, and nobody feels safe changing it.
Business automation, carefully engineered
Turn complex processes, calculations, and expert knowledge into dependable automation systems.
When an important process depends on spreadsheets, disconnected tools, repeated data entry, or one person's expertise, it becomes difficult to scale safely. The work is mapped first, then rebuilt using the right combination of dependable software, AI, and human judgment, each where it fits best.
Prefer an automation team inside the business? See the Technology Partner Program.
- 12 years
- Automating complex, high-value business processes
- 500+
- Independently verified five-star project reviews
- 1 in 3
- Reviews that came from repeat work
Does the process depend on a workaround?
If the work still gets done, it is easy to keep adapting around the problem. The strain usually becomes visible when volume grows, an expert is unavailable, or one wrong value reaches the next system.
02
The same information gets typed in multiple times
An order arrives, then gets re-entered into a spreadsheet, accounting system, and report. Every copy is a chance to be wrong, and eventually two versions disagree.
03
Nobody can get a straight answer out of your own numbers
The data exists, but assembling it takes half a day and two people may produce different answers. The report gets argued with instead of acted on.
04
You want AI doing real work, not answering questions about it
A useful AI system needs real data, clear limits, and a person confirming consequential actions. Those boundaries make it useful beyond the demo.
Three ways forward
Start with what needs to become easier, faster, or safer.
Choose the outcome before the technology: make expert work usable by more people, connect a fragmented workflow, or give AI a defined job it can perform safely.
01
Make expert work usable by more people
Turn specialist calculations and methods into tested software without losing the logic that makes them valuable.
Common solutions
- Custom web applications
- Spreadsheet-to-web-app conversion
Explore expert process systems02
Connect the workflow from end to end
Capture information once, connect the tools already in use, and make the current state visible.
Common solutions
- Workflow automation
- API integration and systems integration
Explore workflow automation03
Give AI a real job with clear limits
Build agents that interpret information, use approved tools, and stop for confirmation when an action matters.
Common solutions
- AI agents
- AI assistants and knowledge-base search
Explore AI agents
If none fits neatly, Describe how the process works today and I will help identify the right starting point. You can also compare the services.
Two ways to work together
Rebuild one process, or embed an automation team.
A defined project suits a single process that needs to become a dependable system. The Technology Partner Program suits a business that wants an automation team embedded in the work, not another vendor for every change.
A defined project
One process, rebuilt as a system you own.
- A fixed scope, agreed before work starts
- Built in reviewable phases, then handed over
- You own the system, the code and the documentation
$10,000and up, fixed per project
Technology Partner Program
Your dedicated automation team, for one monthly fee.
- A dedicated automation team in the day-to-day work
- Finds and builds the automation that saves hours and returns money
- Any tech request goes on a shared board, with no new quote each time
US$5,000per month, 3 months minimum
How the decision gets made
Not every part of a process should be automated the same way.
Most processes contain all three kinds of work at once. Sorting them is the first thing that happens, because putting a calculation behind a language model or asking a person to re-key data that never changes are both expensive mistakes, in opposite directions.
Rules
Dependable software
Work that should produce the same answer every time, and where being wrong is expensive. This belongs in conventional software because that is what makes it repeatable and testable.
- Calculations, pricing, and quoting logic
- Validation and data-quality checks
- Permissions, approvals, and routing rules
- Integrations and transactions between systems
Interpretation
AI assistance
Work that requires reading meaning out of language, documents, or context, where the input arrives in a shape no rule can anticipate. This is where AI earns its place.
- Extracting structured data from email and documents
- Classifying and routing incoming work
- Retrieving answers from scattered knowledge, with sources
- Natural-language access to a system your team already uses
Judgment
Human involvement
Work where the decision carries a consequence, the situation is genuinely ambiguous, or a relationship is at stake. The system prepares the decision and a person makes it.
- Exceptions the process did not anticipate
- Approving anything financial, external, or irreversible
- Negotiation and sensitive communication
- Strategic calls that change how the work is done
What should not be automated
Some steps are worth leaving exactly as they are. A judgment call made a few times a month, an exception that needs someone who knows the customer, or a process still changing too quickly to be worth fixing in software. Deciding what to leave alone is part of the work, and saying so early is usually cheaper than discovering it during a build.
Selected work
See what changed once the right system was in place.
These teams began with slow quoting, repeated data entry, or work hidden behind too many screens. Each project shows the starting problem, the system that replaced it, and the measurable difference once it was in use.
Custom windows and doors manufacturing · Australia
Producing a single customer quote took two to three hours and passed through four separate people or systems, each one a chance to mistype a number that the whole price depended on.
View the full project2 to 3 hours to ~10 minutes
Quote production time
Food and produce distribution · United States
The same order details were being entered by hand into several disconnected spreadsheets, and every report was assembled manually from whichever copy happened to be current.
View the full project95%+ reduction
Data-entry error rate
Business-management and financial software · Belgium
Customers were losing hours to questions the product could already answer, and to administrative tasks that took several screens to complete.
View the full projecthours to seconds
Time to a sourced answer
What partners notice
Your business should not need translating into developer language.
The person building the system should understand how the work runs, notice what is missing, and explain the tradeoffs clearly. These excerpts from 500+ independently verified five-star reviews show what that feels like in practice.
“Samer was the only one who truly took a deep dive into the process we were hoping to automate. He studied the files and asked questions that showed he fully grasped every detail.”
Victor G. “He often envisions a more elegant solution than yours. Your challenge is to understand what he's suggesting and why it's better.”
Simon L. “That demanded different kind of skills in programming, math, design, creative thinking and problem solution. He excelled in all of them.”
Joao
A clear path from today's process to the system you need
Get clarity before committing to implementation, then review useful work at each phase. See the paid Process Audit & Solution Blueprint, full process, and typical costs on How I work.
- 01
Understand and de-risk
Start with how the work runs today. Resolve the important unknowns before committing to a large build.
- 02
Build in reviewable phases
Review useful working parts early, while assumptions are still inexpensive to correct.
- 03
Launch with ownership
Receive tested software, documentation, handover, and 30 days of post-launch support.
What you need to know before deciding
The practical details that make it easier to decide whether this is the right path: cost, timing, ownership, and what happens next. If your question is not here, send it with your process description.
Ask a questionWhat does a project typically cost?
Projects start at $10,000, and most land in the range of $20,000 to $50,000. Cost depends mainly on the number of systems involved and how much of the current process is already documented. Once the scope is understood, you get a real number rather than a broad range.Should I start with a project or the Partner Program?
Start with a project when there is one defined process to rebuild and you want a fixed scope, a fixed price, and a system you own at the end. Start with the Technology Partner Program when the business needs a dedicated automation team: people who map the workflows, find and recommend automation ranked by hours and money, build it along with internal tools, and stay, for US$5,000 a month. Many businesses begin with a project and join the program once there is a steady stream of work worth owning.Why would I pay for a Audit & Blueprint before implementation?
You may not need one if the path is already clear. When it is not, the Process Audit & Solution Blueprint audits one defined, high-value business process and defines the scope, workflow, architecture, risks, phases, and implementation range before either side commits to a build. It also states what belongs in dependable software, where AI genuinely helps, what should stay with a person, and what should not be automated at all. It takes one to two weeks, costs a fixed $3,000, and is credited toward implementation started within 30 days. You keep it either way, and it is useful even if another team does the build.How long does it take?
Implementation usually takes 6 to 16 weeks. Work is delivered in phases, so you can review useful parts of the system before the entire project is finished. If a Audit & Blueprint is needed, add one to two weeks before implementation.Who owns the code and the system?
You do. The code, infrastructure, and documentation are handed over at launch. There is no proprietary platform you have to keep paying for, and the system does not stop working if our work together ends.