Law firms
Nothing AI-generated reaches a client or a court without a lawyer approving it.
MethodologyHow we build with AI
We build AI that a business can rely on every day. People stay in charge of the decisions that matter, every AI answer gets checked, costs are known up front, there's a fallback when the AI misses, and someone gets an alert the moment something breaks. Your data stays under your control.
Where we stand on AI
Now.
Building software has become fast and cheap. Getting AI past a demo and into the daily work of a real company is still hard, because AI is powerful and sometimes wrong in the same afternoon.
Next.
AI will take on more of the routine work in every operation: reading documents, answering first questions, routing requests, checking data. The companies that gain the most won't be the ones with the most AI. They'll be the ones whose AI they can trust.
How we do it responsibly.
We keep people in charge of decisions with real consequences. We say plainly what AI can't do for you. We build only what we can monitor and fix. And your data stays yours.
People decide. AI prepares.
The AI does the preparation: it reads, drafts, sorts, and flags. A person approves anything that reaches a customer, a court, an invoice, or a decision you can't undo. We decide with you, on the first call, where that line sits in your operation, and the build enforces it.
Freight
The system handles routine tracking checks, and anything it can't resolve goes to one queue a person owns.
Every build
When the AI isn't sure, it hands over to a person instead of guessing.
The method behind every build
This is the delivery framework our team follows on every project. It's written down, versioned, and tested on real client work.
01Scope before code
Every build starts with the Blueprint: a written plan and a clear definition of done.
02Risk sets the checks
We sort every change by what it could break. Anything touching money, data, or work that runs with nobody watching gets the strictest checks.
03Checks named before we build
We decide how we'll prove a feature works before writing it, and test it the way your team will use it.
04Senior review of AI-written code
A senior engineer reviews every change before it ships and has to understand it, not just skim it.
05Evaluations for AI features
We check AI output against real examples from your work, test that guardrails hold, and, for AI agents, check each step they take and alert when quality drifts.
06Known costs
We track what every AI call costs, set spending limits, and add a switch to stop runaway usage.
07A fallback for every miss
When a model is down or unsure, the system takes a simpler path or hands the task to a person.
08Monitoring we've tested
Alerts go to a named person, including an alert when expected work doesn't happen. We trigger each alert on purpose before we call the work done.
What we build with AI
Assistants and chat
Answer questions from your own documents and data
Document reading
Pull data from invoices, contracts, forms, and scans
Vision
Understand images, photos, and screenshots
Voice agents
Make and take calls, and act on what was said
Speech to text
Turn calls and meetings into searchable text
Image generation
Create visuals from a brief
Video generation
Create and edit video with AI
Knowledge search
Find the right answer across your files
AI agents
Carry out multi-step tasks with tools, within limits you set
Sorting and routing
Classify requests and send them to the right place
AI we've built
TestAImodels
Our own tool for comparing AI models side by side, now in final migration.
A logistics AI agent we co-founded, live with its first users. It watches loads, calls the driver when tracking data breaks, and sends what it can't resolve to one human queue.
Most of the products we build now include AI. Lead Agents, a client, runs on 12 n8n systems we built.
Your data, under your control
AI providers
We usually build with OpenAI and Anthropic, and we've worked with more than 10 AI providers. We use whichever one your needs and your legal requirements allow.
Where data lives
You choose where your data is hosted: the EU or the US.
Agreements
We sign an NDA on almost every project, and a data processing agreement when your data needs one.
Training
We don't train AI models on your data.
Access
Access to your systems - code repositories, no-code platforms, your project portal - is set up per client, by role. Everyone on our team works under an agreement with us, and loses access when they stop working with us.
Ownership
You own the code, workflows, accounts, and documentation.
GDPR and the EU AI Act
We don't sell certificates. We design for your obligations from the start: a data processing agreement when needed, hosting in the region you choose, and access limited by role. If what you want to build falls under the EU AI Act, we'll tell you on the first call what it means for the design, which usually comes down to human oversight and a clear record of what the AI did.
What we won't do
- Put AI in front of your customers without a way for a person to step in
- Ship an AI feature we can't monitor
- Promise results we haven't measured
- Train models on your data
FAQ