SERVICES
We automate end to end the process that takes up most of your hours, with agents, skills, MCP servers on top of your APIs, assistants that cite the source and models that read and predict. People only review the exceptions, and we measure the result.
Invoices, delivery notes, orders or case files that someone copies by hand from a document into a system.
Regulations, procedures and documentation that nobody can find when it is needed.
But it fails with real documents, ignores permissions, or nobody knows what it costs at scale.
HOW WE HELP
«We know AI can help us, but we don't know where to start.»
«We have too much manual, repetitive or administrative work.»
«Information is scattered across documents, emails, people and systems.»
«We want to use AI and automation to sell better, operate with less friction and be more productive.»
AI AUTOMATION
They query, decide and carry out tasks on your ERP, CRM, email or WhatsApp, with human oversight where needed.
Answers from your documentation (RAG), citing the source and respecting each user’s permissions.
Reading and extracting invoices, delivery notes and contracts, and classifying and routing incoming email.
We build MCP (Model Context Protocol) servers on top of your systems' APIs so Claude, ChatGPT, Copilot or your own agents can query and operate them with permissions and traces.
We turn your team's procedures and know-how into skills that agents reuse, and produce ready-to-use artifacts: reports, documents, tables or small applications.
Flows between ERP, CRM, email, WhatsApp and spreadsheets with n8n or code.
Demand forecasting, scoring, anomaly detection and computer vision when an LLM is not the right tool.
Test bench, traces, review by exception, security and measured cost per operation.
Not everything is solved with AI. We advise you on the best solution for each process: sometimes it is an AI agent, and sometimes RPA, a machine learning model, data integration between your systems or improving the process itself is enough. What we are after is the result, not using AI at any cost.
The one that takes the most hours, with volume and clear rules, and we measure its starting point.
First real documents and cases to set the accuracy rate.
Integration with your systems, permissions, review by exception and traces.
Hours saved and cost per operation; if it works, on to the next process.
Savings measured in hours and cost per operation, and a way to scale process by process without depending on a single model.
Documented architecture, code in your repository, automated tests and traces of every operation.
Data processed where you decide, never used to train models, with a record of every decision and human oversight.
Technology
TECHNOLOGY
The engine is chosen by data, cost and ecosystem. A single orchestration layer means switching models doesn't force you to rebuild anything.
Agents in production on frontier models when answer quality matters most.
The natural route if you already work on Azure, with identity, network and data governance sorted.
Open-source models on your infrastructure, no per-token cost and data kept in-house.
Switching models doesn't mean rebuilding the automation.
FAQ
Straight answers to what we're asked most.
Repetitive, high-volume ones: reading documents, incoming email, quotes, case file checks, internal or customer queries, system data entry and order and incident tracking.
No. We analyse each process and recommend what solves it best: generative AI, RPA, machine learning, data integration or a change to the process. Often the best solution combines several.
Whichever best fits the case: Claude, ChatGPT, Gemini, Azure AI Foundry or open-source models on your infrastructure. Our own orchestration layer lets you switch models without rebuilding the solution.
Model Context Protocol is the open standard AI assistants and agents use to connect to external systems. An MCP server on top of your APIs lets Claude, ChatGPT, Copilot or your agents query and operate your ERP, CRM or in-house applications in a controlled way, without a custom integration for each tool.
A skill packages instructions, templates and scripts so an agent performs a specific task the way your team would; it is reused across many cases. An artifact is the ready-to-use output the agent delivers: a report, a document, a table or a small application.
No. We work with enterprise services that do not train on your data, or with local models, and we document it in the contract and in the system record.
The case goes to a person with all the information ready. The final decision stays human where it needs to.
We measure the process before we start and after automating it: hours, errors and cost per operation.
A first 30-minute conversation, no strings attached.
