Workflow automation
Many teams spend hours every week on work a well-built automation can handle: sorting inbound requests, drafting replies, moving data between tools and preparing reports. We build automations that run reliably and hand off to a person when judgement is needed.
What is included
Automate repetitive operations with AI agents and connected tools.
- Process mapping
- The workflow documented as it runs today, with the steps worth automating marked.
- Agent and automation build
- AI agents and scripted workflows connected to the tools you already use.
- Human in the loop
- Approval steps for anything customer-facing or high-risk.
- Reporting
- A clear view of what ran, what failed and how much time it saved.
How it works
From first call to launch.
Find the riskiest assumption
We agree on what the first version has to prove.
Prototype
A clickable prototype or proof of concept, tested with real users or real data.
Build
Production code in two-week sprints, each ending in a working demo.
Launch and measure
Release, instrument, learn, then plan the next iteration together.
What a typical project looks like
A typical automation project replaces a manual process that eats several hours a week: routing inbound leads, preparing reports, processing invoices or onboarding documents, or keeping a CRM in sync with a product database.
We map the process as it runs today, measure the hours involved and pick the step with the clearest payback. Then we build the automation with tools such as n8n, Make or custom code, add an AI step where judgement is needed, and keep a human review point until the results are trusted. Most automations go live in two to six weeks.
Timeline
Typical timelines. You get a fixed written estimate after scoping, before any work starts.
- Single workflow
- Two to four weeks.
- Multi-step process with AI
- Four to six weeks.
- Support
- Monitoring and adjustments as your tools and process change.
A good fit if
- Your team repeats the same manual steps every day.
- One person holds the only knowledge of how a process works.
- You want AI to support your team's judgement, not replace it.
Questions
Do we need to change our tools?
Usually not. We build around the tools you already use wherever they allow it.
What if the automation makes a mistake?
We design with approval steps and logging, so errors are caught early and can be traced.
How do we measure the result?
We agree on a baseline before building, such as hours spent or response time, and report against it.
Which workflows should we automate first?
The ones that are repetitive, rule-based and frequent, with inputs that arrive in a consistent format. Our article on the topic has a simple scoring method.
Do you use no-code tools or custom code?
Both. We use tools like n8n or Make when they are reliable enough, and custom code when volume, security or logic demands it.
Related services
Often paired with workflow automation.
Further reading
- Blog
Which business workflows should you automate first?
A simple way to choose the first workflows to automate in a startup: score them by frequency, time cost and consistency, then keep a person in the loop.
- Blog
How to add AI features to an existing product without a rebuild
A practical approach to adding AI to a live product: choosing the right first feature, keeping costs predictable and shipping without rewriting what already works.
- Blog
No-code or custom build: when a prototype is enough
How to tell whether your startup should keep going on no-code tools or invest in a custom-built product.
Have something to build?
Tell us what you are working on. We will come back with questions, not a sales script.