We put artificial intelligence inside how your business actually operates.
We look at how your team works, design the system, and leave agents, skills, and AI workflows running in the tools you already use.
Our approach is agentic: agents with context, procedures, and permissions, not a loose chat window.
Free · 25 to 30 minutes
Initial AI diagnostic
A call to understand your case and see whether there's a real opportunity. If there is, we tell you what the first step would be; if there isn't one yet, we tell you that too.
Book an initial diagnostic — Contact usIt doesn't replace an audit: no detailed architecture, no technical documentation.
The services in this track
- 01
AI agents for WhatsApp
Answers, sorts and follows up on WhatsApp, and knows when to step aside and hand the chat to a person.
An agent built on the official WhatsApp Business API, wired into your systems, with written limits on what it can do and metrics from day one.
- 03
AI workshop for teams
Your team already tried AI. What's missing isn't a better tool: it's the work written down.
Two to four weeks, four to twelve people, working on processes from your own operation. Your team walks out with the company's first written procedures and at least one of those processes running with AI.
- 04
AI audit
Half of what you're paying for is being told where AI doesn't belong.
Fieldwork inside your operation: who does what, where it jams, and what the jam costs. Out comes a ranked list, a roadmap and a cost estimate for whatever sits at the top.
- 05
Agentic architecture
An agent with no control points is like an intern nobody supervises.
The full blueprint before anything gets built: which agents exist, what each one can do, what systems they're allowed to reach, and where the work stops to wait for a human yes.
- 06
First working agent
One agent wired into one real task, not four departments at once with nothing finished.
The real way in: we pick a task that's eating someone's week, build the agent on the tools you already run, and put a number on it before and after.
- 07
A whole department, running on agents
Bolting an agent onto the old process doesn't change a department. Redrawing who does what does.
A whole department (marketing, sales, support, finance, operations) ends up running on several agents, written procedures, and a person who signs off before anything leaves.
- 08
AI across the whole company
No company flips overnight. One area at a time, and each one stands on its own before the next starts.
The biggest scope in this track: several areas, agents that hand work to each other, clear rules about who's allowed to do what, and whatever software is missing. Always after an audit.
The initial diagnostic is a short, free call. Everything else is quoted by scope, with the proposal in writing before we start.
The implementation path
You can come in at whatever stage makes sense for your company. The one thing we don't recommend is implementing before understanding the process: automating a mess just makes it faster, not better.
- 01
Understand
Before automating anything, see how the team actually works. More often than not, the biggest saving on the list doesn't need AI at all, and that has to be said out loud.
- Free initial diagnostic
- AI workshop with your team
- Operational audit
- Opportunities identified and prioritized
- What needs AI and what has a simpler answer
- 02
Design
The system on paper before it exists. Which agents there are, what each one knows, what it's allowed to touch, where it stops to ask, and how you know it did the job right.
- Agentic architecture and specs
- Agents, skills, and knowledge sources
- Integrations, MCPs, and tools
- Permissions and approval points
- Metrics, success criteria, and a rollback plan
- 03
Implement
One agent, one task, one team. Running alongside the old process until it stands on its own, with a screen where your people see what it did and approve it.
- First working agent
- Rollout across one team
- Supervision and approval interfaces
- Integration with your current tools
- Training for whoever works with it
- 04
Scale
What separates a pilot from an operation: knowing what it costs, who's allowed to do what, what broke, and what actually improved. And being able to switch off whatever didn't earn its place.
- Observability and cost control
- Evaluations and versioning of prompts, specs, and skills
- Security, permissions, and governance
- New areas and continuous improvement
- Maintenance and ongoing support
The concept
What a skill is
A skill is a reusable capability that teaches an agent how to carry out a task in your company the same way every time.
A skill contains
- Instructions
- Context
- Procedures
- Tools
- Examples
- Constraints
- Validations
- Quality criteria
- Input and output formats
- When it must stop
- When it needs human approval
For example
- Qualify a lead
- Draft a proposal
- Review a piece of content
- Build a report
- Summarize a conversation
- Classify a request
- Query a system over MCP
- Prepare a reply for approval
- Check that a task meets its spec
We don't build agents that hang off an improvised prompt. We design capabilities that are documented, reusable, testable, and wired into the operation.
The method
Every workflow starts from its spec
Before setting up an agent we write down what it has to achieve, what goes in and what comes out, what context it needs, which tools it can use, what it's allowed and not allowed to do, when it counts as done, what happens in the odd cases, who reviews it, how it's measured, what it does when something fails, when it stops, and how to roll the whole thing back.
What it buys you
- Testing the agent against cases, not impressions
- Getting the same result again tomorrow
- Versioning the work and seeing what changed
- Catching when something that worked stopped working
- Training people from the same document
- Swapping models without losing the operational knowledge
It isn't a trend and it isn't an automatic guarantee of quality. It's what lets you argue about a result with something in your hand.
Included in everything
These four rules apply to everything we set up, whatever the size. They're not an add-on: they're the difference between automation and a blind spot.
Human review where it counts
Nothing that leaves the building (sending, paying, publishing, deleting) happens without a person saying yes. That isn't textbook advice: it's the rule our own company runs on.
Measured before and after
We measure the process before touching it. Without that baseline, any result shown afterwards is just a story. And the option to switch it off stays on the table.
Explicit permissions and limits
Every agent knows which data it can reach, which actions it can take, how much it can spend, and when it has to stop and ask. Written up front, not discovered later.
Traceability
There's a record of what the agent did, with what data, and why. An automated process nobody can audit isn't automation: it's a blind spot with good presentation.
Or is yours the other one?
Specialized software development
We design and build complete digital products: from a custom landing page to the systems that run your company (CRM, ERP, MRP, CMS, dashboards), visual editors, mobile apps, and IoT systems.
Where does AI fit in your operation?
Tell us which process is eating your team's time. In half an hour we'll tell you whether there's a real opportunity, what the first step would be, and if the answer is not yet, we'll tell you that too.
We reply within one business day