Workflow Automation
The repetitive steps your team repeats every week, handled end to end without anyone babysitting them.
AI automation for local businesses
We take the repetitive work off your team's desk with custom automation and web development, then keep improving it long after it ships.
Fixed price, quoted first
You see the number before anything gets built, and it holds unless the scope moves.
Live in one to three weeks
Measured from the discovery call to something running against your real data.
Improved after it ships
We keep tuning and extending what we have delivered as your process changes.
What We Do
Six kinds of work we take off your desk
Data & Reporting
Numbers pulled from the tools you already use into one report that arrives on schedule.
Document Processing
Invoices, forms and PDFs read automatically, with the fields you care about extracted and checked.
Custom Integrations
Two systems that never talked to each other, connected so data stops moving by copy and paste.
Web Development
Fast, responsive sites and internal tools that fit the way your business actually operates.
Ongoing Improvement
What we have already delivered keeps getting better. As your process shifts we tune, extend and fix what is running, so it stays worth having.
How It Works
What a project looks like
01
Discovery
We walk the current process with your team and pick the tasks worth automating first.
02
Build
We build around the tools and data you already have, not a platform you have to adopt.
03
Validation
We run it against real jobs from the last few months and compare output to what your team produced.
04
Handoff & Iteration
You get documentation and full ownership. We stay available as the process changes.
Under the Hood
What the work is actually built on
Every automation is real software: version controlled, tested against your own historical data, and documented so another engineer could pick it up. No no-code black boxes you can't inspect or move.
Models & reasoning
- Claude API (Anthropic)
- OpenAI API
- Structured output & tool calling
- Retrieval over your own documents
Automation & data
- Python (pandas, FastAPI)
- PostgreSQL
- OCR & PDF parsing pipelines
- Scheduled jobs and webhooks
Web & delivery
- React, TypeScript, Tailwind
- Node & serverless functions
- Google Workspace / Microsoft 365 APIs
- Version control, tests, CI
Case Study
Invoice reconciliation at a local supplier
An office manager was spending about 10 hours a week matching supplier invoices against delivery notes and purchase orders by hand, a job that was both time-consuming and error-prone. We built a pipeline that reads each incoming invoice, extracts the line items, matches them against order records and flags only the exceptions for a human to review. The weekly task now takes under 30 minutes and month-end corrections have largely stopped.
Client details anonymized at their request.
Results
Where projects have landed so far
10+
Automations Delivered
~75%
Less Manual Processing Time
1–3
Week Average Delivery
FAQ
The questions we get asked first
How much does a project cost?
Most first engagements land between a few hundred and a few thousand dollars, quoted as a fixed price once we've scoped the work in discovery. You see the number before anything gets built, and it doesn't move unless the scope does.
How long does it take?
One to three weeks for a typical automation, measured from the discovery call to something running against your real data. Larger integrations take longer, and we'll say so up front rather than after you've committed.
Do I need to change the software we already use?
No. The work is built around your existing tools: the spreadsheets, inbox, accounting package and CRM your team already knows. Replacing those is expensive and disruptive, and it's rarely what actually saves the time.
What happens to my data?
It stays in your systems. Where a language model is involved we use business API tiers that don't train on your inputs, we send the minimum needed for the task, and we can keep sensitive fields out of the request entirely. Anything specific your industry requires, tell us in discovery.
What if the automation gets something wrong?
Everything is validated against real jobs from your last few months before it goes live, and the output is compared to what your team produced by hand. Where a judgement call is involved, the system flags it for review instead of guessing, so you keep a human in the loop exactly where one belongs.
What happens after it's delivered?
We keep improving it. A process that was right in March is often not quite right by September, so we come back to what we have already shipped: tuning it as your volumes change, extending it when you find the next thing worth automating, and fixing anything that drifts. You are not buying a handover and a goodbye.
Do I own what you build?
Yes, completely. You get the source code, the documentation and the credentials at handoff. Nothing is locked to a platform of ours, and another engineer could pick it up tomorrow. We stay available for changes because clients want us to, not because they're stuck.
About
Eric Solak
Founder, Alloy
Eric is a software engineering graduate from McMaster University. He has led AI development on a production voice application used daily in the field, where the software had to hold up in environments with poor connectivity.
Alloy brings that same engineering standard to small and local businesses, at a price and timeline they can commit to.
Let's talk.
Tell us what your team repeats every week. We'll tell you honestly whether it's worth automating, and if it isn't, we'll say so.