No-Code and Low-Code AI
We design and build the logic; you keep the ability to change it. Workflows you can open, read and adjust yourself, without waiting in a development queue.
Automation you can still change
The usual complaint about custom automation is not that it fails. It is that changing it requires someone else. A threshold needs adjusting, a new person joins the team and should be in the routing, the wording of a confirmation is wrong. Each of those is a five-minute change that becomes a ticket, a queue and a two-week wait.
No-code and low-code platforms move that boundary. The logic sits on a visual canvas, and the parts that need to change most often are the parts you can reach. We do the design and the build, including the awkward integration work, and you keep the ability to adjust the things that keep moving.
What we build and what you own
We build the structure: the triggers, the integrations, the branching, the AI steps and their prompts, the error handling. That part benefits from experience, because most of the difficulty in these projects is not the automation itself but the systems it has to talk to and the exceptions nobody mentioned in the first meeting.
You own the operational surface. Which conditions route where. Who gets notified. What the AI step is asked to do and in what tone. What the thresholds are. These are business decisions, and they change more often than the structure does, which is exactly why they should not sit behind a development queue.
Approval points matter more than the automation
The most consequential design decision in any of these workflows is where a human still presses something.
An enquiry can be classified and routed unattended, because a misrouted enquiry costs a forwarded email. A generated product description going straight to a live shop is a different risk, so it goes to a named person first. A refund triggered by an AI classification should not happen without review at all. We work this out with you explicitly rather than defaulting to full automation and discovering the limit through an incident.
Getting this line right is also what makes the automation trustworthy internally. A team that has watched a workflow publish something wrong will route around it for months afterwards.
Choosing a platform
The platforms are not interchangeable, and the differences show up later rather than during a demo.
Zapier and Make are the fastest to get running and have the widest catalogue of ready connectors, which matters if you use a lot of mainstream SaaS. Their pricing is per task, so a workflow that fires thousands of times a month can become surprisingly expensive. n8n can be self-hosted, which changes both the cost curve and the data question, at the price of somebody having to run it. Power Automate makes sense when you are already deep in Microsoft 365 and want the licensing and identity handled in one place.
We will recommend one and explain the tradeoff. If the honest answer is that a scheduled script would be simpler and cheaper than any of them, we will say that too.
Knowing when to move on
No-code has a real ceiling. A flow with forty nodes and several nested branches is harder to reason about than the equivalent hundred lines of code, and when something goes wrong at three in the morning, the visual canvas stops being an advantage. Volume pushes in the same direction.
That is not an argument against starting here. It is an argument for starting here deliberately: prove the process works, learn where the exceptions actually are, and move the logic into code once you know what it needs to do. Migrating a proven workflow is a far smaller job than specifying one from scratch.
What you get
Form and enquiry handling
Submissions get read, classified and routed to the right person, with a confirmation going back to the sender. Nothing sits in a shared inbox waiting to be noticed.
Email triage with drafted replies
Incoming mail is categorised, the relevant data is written to your system, and a reply is prepared for approval. The routing rules stay visible and editable.
Ticket classification and routing
Customer reports are sorted by type and urgency, then pushed into the right support flow. Misclassifications are easy to correct because the rules are in front of you.
Product content pipeline
A new product lands in the system, a description is generated, and it goes to a named person for approval before it can publish. The approval gate is not optional.
Failure handling and alerts
Every workflow gets retry rules and a notification when something stops. Silent failure is the main way automations quietly cost you money.
Documentation and handover
Named steps, a written explanation of what each branch does, and a session with the people who will maintain it. Editability you cannot use is not editability.
How we work
- 01
Map the process as it actually runs
We follow the real path, including the exceptions people handle informally. The documented process and the practised one are rarely the same thing.
- 02
Choose the platform honestly
n8n, Make, Zapier and Power Automate differ on price at volume, self-hosting and how well they handle branching. We pick for your case rather than our preference.
- 03
Build with approval points
We decide together which steps run unattended and which need a human to press something. That line matters more than how much of the flow is automated.
- 04
Run it alongside the manual process
For the first stretch the workflow runs in parallel so you can compare its output against what your team would have done, before anything depends on it.
- 05
Hand over and stay reachable
You get the walkthrough, the documentation and the credentials. We stay available for the changes that turn out to be harder than expected.
Tools and technology
Where a solid open-source tool exists, we choose it over a closed one. No lock-in to a single vendor, and costs you can actually predict.
- n8n
- NocoDB
- Appsmith
- Directus
- Make
- Zapier
- Microsoft Power Automate
- Airtable
- Retool
- Notion
- OpenAI
- Anthropic Claude
Frequently asked questions
More services in this category
Basic AI Implementations
Not every AI project needs to be a platform. The fastest return usually comes from a few narrow tools that take one repetitive task out of someone's week.
Process Automation
If someone does the same thing the same way for the third time, it probably should not be manual. We automate the repeatable part and leave the judgement where it belongs.
AI Agents
An agent decides its own steps instead of following a fixed script. That makes it useful for work that varies, and it makes the permissions around it the most important part of the build.
Read testimonials from companies that trusted us
Delivered well ahead of the deadline.
ZanReal's individual approach is impressive.
Knowledge and business intuition make them a valuable partner.
Quick solutions that reduced costs by 99%.
Latest
Technical guides, security insights, and what we've learned building with AI.
Want workflows your own team can edit?
Message usDescribe the process you want to automate and the tools you already use, and we will recommend a platform and a handover plan your team can run with.
Can't keep up with changes in AI world?
Let us do the heavy lifting. Every week we distill the most important AI developments into a focused 5-minute briefing — so you stay ahead without the noise.
Find out more