Consulting

Technology in service of business processes

We support businesses in evaluating, designing and implementing advanced technology solutions. We don't propose off-the-shelf products: every engagement begins with a concrete analysis of the company's actual situation.

Process analysisAI solutionsAgentic systemsSensor integrationTechnology selectionOn-premise & Cloud

01 — AI Consulting

Identifying where AI can create real value in your business

Before any implementation, it is essential to understand where and how artificial intelligence can deliver a real and measurable benefit. This requires a structured analysis that goes well beyond simply adopting a tool.

01
Business process mapping

We analyse the internal organisation, workflows, repetitive activities and bottlenecks. The objective is to identify precisely which processes — from document management to production, from customer support to logistics — can be made more efficient or partially automated with AI.

02
Available data analysis

Effective AI depends on the quality and availability of data. We assess existing databases — ERP systems, CRM, document archives, system logs — analysing their quality, completeness and structure. We identify any gaps and the strategies to address them.

03
Regulations, compliance and confidentiality

We verify the compatibility of the proposed solution with GDPR, sector-specific regulations and internal data management policies. We assess which data can be used for training or inference, and which requires on-premise solutions or anonymisation.

04
Infrastructure requirements study

We define hardware and software requirements: servers, GPUs, connectivity, storage, API access. We compare cloud options (AWS, Azure, GCP) with on-premise solutions, evaluating costs, performance and long-term sustainability for the specific business context.

05
Custom solution development

Based on the analysis, we design and implement the most suitable solution: a RAG prototype for querying internal documents, a predictive model for stock management, an automatic classification system for requests, or whatever application emerges as the priority.

Consulting is not separate from development: every phase of analysis directly feeds into design decisions. The goal is to deliver solutions that work in the company's actual operational reality, not technology demonstrations that are ends in themselves.

Measurable ROI

We define concrete KPIs before we begin: hours saved, errors reduced, volumes processed. Success is verifiable.

Privacy by design

Sensitive data protection is a project requirement, not an afterthought. We design with privacy at the centre.

Iterative approach

We develop in phases with continuous feedback: every intermediate release is functional and verifiable against the objectives.

Training included

The team that will use the solution is trained on how it works, its limitations and the correct way to use the delivered system.

02 — Agentic systems & integration

Beyond passive AI: systems that act, integrate and automate

The latest generation of AI solutions don't just answer questions: they act autonomously, collect data from external sources, interact with existing business systems and coordinate complex sequences of operations. This level of integration requires careful design and cross-disciplinary expertise.

Autonomous AI agents

Systems capable of planning sequences of actions, using tools (web search, APIs, databases), executing code and making intermediate decisions without human intervention at every step.

Sensor data acquisition

Integration of data streams from IoT sensors, industrial monitoring systems, cameras, weather stations or any real-time data source, to feed decision-making or alerting models.

ERP/CRM integration

Connection with ERP, CRM, MES, ticketing systems and any business application via APIs, webhooks or custom connectors. AI becomes part of the existing operational workflow without replacing it.

Multi-agent orchestration

Design of pipelines where multiple specialised agents collaborate: one retrieves data, one analyses it, one produces structured outputs, one verifies result quality before delivery.

Document workflow automation

Automatic processing of invoices, contracts, reports, emails and forms: classification, structured data extraction, routing to the correct systems and generation of consequent responses or actions.

Monitoring and alerting

Systems that continuously analyse operational data, identify anomalies, forecast critical issues and send notifications or trigger automatic procedures before a problem becomes an emergency.

Agentic systems are not suited to every context: they require careful design of autonomy boundaries, control mechanisms and fallback procedures. Our consulting always includes defining these operational limits, so that automation increases rather than reduces control over the process.

Integration technologies

REST APIWebhookMCP (Model Context Protocol)LangChain / LangGraphn8nMQTT / IoTPostgreSQLSQLiteFastAPIDockerRaspberry Pi / Edge

03 — Technology selection

Identifying the right solution in a rapidly evolving landscape

The AI market today offers dozens of different approaches, tools and architectures. The wrong choice can lead to oversized solutions, high maintenance costs, or simply the wrong fit for the problem to be solved. Our technology consulting helps you navigate this landscape with objective criteria.

Machine Learning
Predictive models and classifiers

Ideal when you have structured historical data and want to predict a numerical value, classify items or detect anomalies. Algorithms like Random Forest, XGBoost or lightweight neural networks deliver high performance with modest resources. Suited to: sales forecasting, customer scoring, quality control, fraud detection.

Supervised learningForecastingAnomaly detection
AI Agents
Complex process automation

When a task requires multiple sequential steps, the use of external tools (APIs, databases, browser), or conditional decisions, an agentic system is better suited than a simple LLM. It requires careful design but offers significantly superior automation capabilities. Suited to: document workflows, analysis pipelines, operational assistants.

LangGraphTool useOrchestration
On-premise
Data that stays in-house

When data confidentiality is a non-negotiable requirement — sensitive data, trade secrets, information subject to specific regulations — on-premise is the only option. Through Ollama and open source models it is possible to run powerful LLMs on company hardware without data ever leaving the perimeter.

OllamaLlama / MistralAir-gapped
Cloud
Scalability and cutting-edge models

When performance is the priority and data can be shared with reliable providers, cloud APIs offer access to the most advanced models with usage-proportional costs and zero infrastructure to manage. Suited to: rapid prototyping, applications with variable volumes, access to multimodal models.

Claude APIOpenAIGemini
Hybrid approach
The most common solution

In most real projects, the optimal solution combines multiple approaches: a local ML model for fast classification, a cloud LLM for text generation, and an agentic system for orchestration. Consulting exists precisely to design this architecture in a coherent and efficient way.

ML + LLMCloud + EdgeMulti-model

There is no universally superior technology: there is the right one for the specific problem, available budget, internal competencies and compliance constraints. Our role is to help you make this choice based on data, without conflicts of interest tied to selling a specific product.

Have a project to assess?

Tell us about your situation in a free initial call. We analyse the needs together and give you an honest assessment of whether and how technology can help.

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