AI systems · Automation · Content production
Codelab designs and implements AI-powered workflows, content systems and custom software that connect models with your data, your business rules and the people who sign off on the result. Not a prompt bolted onto a spreadsheet — a system you can run every day, check, and correct when it gets something wrong.
What we build
Most AI projects stall between the demo and the day job. The demo answers one question well; the business needs the same answer a thousand times, on real data, with someone accountable for what goes out. Both of our capabilities are about closing that gap.
Finding the processes worth automating, then building them: model steps wired into your data and APIs, output constrained to a schema, checks that catch a bad answer, and a person in the loop wherever judgement is required.
Content operations that run on a system rather than on heroics: newsroom and editorial workflows, marketing production at channel scale, and AI-assisted video — each with source grounding, style rules and an editor who approves before anything ships.
What that looks like in practice
Concrete shapes of work, not industry categories. If your process resembles one of these, there is usually a system worth building.
A database or feed updates; a person rewrites the same summary every week. The system drafts it from the current figures, checks the numbers against the source, and puts it in front of an editor.
Invoices, contracts, forms and reports arrive as files. Fields are extracted to a defined schema, anything uncertain is flagged rather than guessed, and a reviewer resolves the exceptions.
Enquiries, tickets or submissions land in one queue. The system reads them, labels them, routes them to the right place, and escalates the cases it is not confident about.
Gathering sources, extracting the relevant passages and assembling a grounded brief — so the drafting step starts from cited material rather than from the model's recollection.
A campaign or announcement adapted into the formats each channel needs, held to a brand and style guide, with the variants tracked back to the original.
Turning a report, article or product update into a script, a storyboard, generated assets and an assembled cut — versioned per channel, approved before release.
How we deliver
The same sequence whether the output is an automated workflow, a newsroom pipeline or a video production system. Nothing starts until step one is written down.
The process as it runs today, who it serves, what constrains it, and what actually goes wrong.
The workflow, the data it needs, where a model helps, and the criteria that define a good result.
Integration with your systems and APIs, the model steps, and the software around them.
Run it against real cases, including the awkward ones, and measure where it fails before anyone relies on it.
Put it into use with the review gates and approvals the work actually warrants.
Watch what it produces, handle the exceptions it surfaces, and tighten the rules that need it.
Why this is more reliable
A language model is a capable and unreliable dependency. Treated like any other unreliable dependency — constrained, validated, observable, reversible — it becomes something a business can depend on. Treated as an oracle, it produces work nobody can stand behind.
The engineering underneath
An AI workflow is only as good as the application around it: the integrations, the queues, the admin screens, the error handling. Codelab has been building conventional server-rendered software for years, and that is the layer these systems run on.
Also available
A specialist capability we continue to offer: speech and language data collected, transcribed, annotated and independently checked against a written specification, with Brazilian Portuguese as the core locale. Useful if you are training or evaluating a model, or need audio turned into structured, reviewed text.
Start a project
Describe the process as it works today, what breaks, and what a good result looks like. We will reply with questions, a proposed shape for the system, and what we would need from you to start.
