AI Agents
AI that carries out tasks from start to finish: looking things up, checking, planning and preparing. Your team approves what matters.
- First agent liveIn about four weeks
- Works withYour email, calendar, documents and systems
- AlwaysA person approves decisions
An agent schedules the yearly lift maintenance for three sites: it checks the contract, finds free slots, arranges access and drafts confirmations that your team approves.
Can you schedule the yearly maintenance of the lifts for three sites, before 1 December?
- Maintenance contract checkedContractLift maintenance falls under contract LO-2025, once a year
- Free slots foundPlanningEngineer available on 18, 20 and 25 November
- Access arrangedSitesKey management and a contact person per site
- Confirmations draftedMailThree draft emails to the site managers
- Waiting for your approvalApprovedApprovalNothing goes out until you approveConfirmations sent to three locations
An agent is only valuable if you can trust it. That is why your team sees every step.
We pick tasks where the work is predictable but the execution takes time, and build agents with clear limits and a log.
Tasks nobody finishes
Looking things up, following up, planning. Work that sits because it is always slightly less urgent.
Waiting for the right person
A task goes from inbox to inbox before anyone picks it up.
Steps that get skipped
When it is busy, a check gets dropped. You only notice later.
How we solve it
The solution follows from the problem, not the other way round. These are the building blocks we use most often.
Research and preparation
Gathering, comparing and summarizing information before anyone makes a decision.
Planning and coordination
Matching appointments, technicians and locations to each other.
Checks against your rules
Contracts, limits and terms are checked at every step.
Working in your systems
The agent works through integrations in the tools you already have.
Approval by a person
What matters only goes out after sign-off.
A log of every step
You can read back what the agent did, when and why.
You are not buying an AI agent. You are buying a result.
Up front, we agree what has to improve and how we will measure it. Afterwards, we show you what it delivered.
Tasks finished faster
Measured in turnaround time per task.Less work in the pile
Measured in open tasks.Consistent execution
Measured in skipped steps and corrections.Capacity without extra people
Measured in tasks per employee.Outcome agreement
per processMeasure. Build. Own.
After each step, you decide whether to continue.
Measure
The efficiency audit. We map your processes, take a baseline and show you where it pays off, and where it does not.
Build
We build inside your existing systems, in short rounds your team tests itself. The work carries on as normal.
Own
You get everything in your hands. We measure what it delivers against the baseline and adjust. You can leave maintenance with us or run it yourself.
What we build is yours.
No platform you rent and no costs that grow with your usage. You get the software itself, with everything needed to understand and run it.
- Source codein your repository
- Integrations and workflowsdocumented
- Prompts and rulesreadable and editable
- Log of every actionin your own environment
- Maintenancewith us or with you
Frequently asked questions
Not seeing your question? Ask it in the audit.
A chatbot answers questions in a conversation. An AI agent autonomously executes tasks: collecting data, analyzing it, making decisions, and controlling systems. Chatbots are reactive, agents are proactive. For example, an agent can scan your competition every Monday, detect price changes, and put a report with recommendations in your inbox, without you asking for it.
Think of tasks that have structure but are too complex for simple automation: lead qualification (researching companies and assessing fit), market research (monitoring competitors and analyzing trends), invoice processing (reading documents, validating data, flagging exceptions), and reporting (combining data from multiple sources and generating insights). If your team does it every week but it doesn't require strategy, it's suitable for an agent.
A process is suitable if it's repetitive, has clear end results, and is based on data or logic you can explain. We always start with an analysis of your workflow: what are the steps, where does time go, where do errors happen? Then we determine whether an agent is the right solution, or if simpler automation or a chatbot would be better.
Yes, just like humans. That's why we always build human-in-the-loop checkpoints for critical decisions. The agent flags uncertain cases and lets you do the final review. We also log every action and train the agent with feedback, which rapidly reduces the error rate. The goal isn't 100% autonomy from day one, but a system that handles 95% of the work flawlessly within weeks.
Costs depend on complexity: a simple agent for one task is a smaller investment than a multi-system agent that manages multiple processes. Payback time depends on time savings: in the free consultation we calculate this upfront, so you know what to expect.
Start with the efficiency audit.
We look together at what costs you the most. You get a baseline, an overview of where it pays off and where it does not, and a proposal for the first step.