AI Agents for SMEs |

Custom AI agents to automate processes, reduce costs and generate measurable value.

Reduce Costs

Up to 0% savings on repetitive operations

Free Up Time

0+ hours/week for strategic activities

Increase Revenue

0x lead conversions, -0% response times

0-0
weeks for prototype
0/7
continuous operation
0%
transparency and control
0
lock-in, your code
What We Do FAQ Have you met CL-AI-RA?

What We Do

Revenue & Growth

AI Inbound Setter: Welcomes leads from website/chat/WhatsApp, asks 3-5 qualifying questions, proposes calendar slots, creates/updates CRM records.
AI Outbound Bot: Contacts outbound leads via WhatsApp/email with personalized messages, manages conversations for appointment setting and automatic qualification.
AI Cold Caller: Calls pre-qualified lists, gathers interest, classifies maturity (A/B/C) and transfers the call at the right moment.
Cold Email Automation: Multi-channel sequences with personalization, reply management, automatic stops on bounces or opt-outs.
Market Research & Lead Gen: Company/persona research, contact enrichment and CRM insertion with tags and priorities.

Customer Experience

Customer Service & Review Management: Responds to FAQs, opens/closes tickets, activates smart escalation, requests and manages post-sales reviews.
Sentiment Analysis & Social Monitoring: Monitors social mentions, analyzes sentiment, alerts on negative feedback and proactive reputation management.
Content Repurposing: From documents, videos and webinars to posts, carousels, newsletters, FAQs and knowledge base.
Onboarding & Training Automation: Interactive guides for new clients, personalized tutorials, progress tracking and automatic certifications.
Churn Prevention: Identifies abandonment signals, personalized retention campaigns, win-back automation with targeted offers.

Operations & Back-Office

CRM Data Entry & Follow-Up: Data entry, deduplication, call notes, tasks and reminders according to playbooks.
Document Processing & OCR: Automatic extraction from contracts, invoices, CVs, forms. Classification, validation and intelligent document routing.
Scheduling & Calendar: Calendar synchronization, invitations, multi-channel reminders, smart rescheduling and room/resource management.
Inventory & Asset Management: Automatic inventory tracking, reorder alerts, IT asset management, maintenance scheduling and depreciation tracking.
Workflow Automation: Multi-step approval processes, automatic escalation, intelligent task assignment and bottleneck detection.

All packages are composable and integrable with Salesforce, Google Workspace, Microsoft 365, WhatsApp Business, n8n and VoIP providers.

Have a custom AI idea? Share your vision with us and we'll craft a tailored proposal that turns your concept into reality.

Engagement Process

1

Discovery & KSI

Objectives, channels, compliance, available data. For a more in-depth preliminary phase, we recommend the CompanyTech BattlePlan.

2

Prototype (2–3 weeks)

An end-to-end use case on real data.

3

Controlled Pilot

Testing on a restricted sample of real users, human-in-the-loop, KPI dashboard.

4

Go-live & Scaling

Extension to departments/markets with scaling of cloud-native technology stack designed to grow. Team training and complete handover.

5

Continuous Improvement

Model tuning, new playbooks, A/B testing. Preparation for new iterations and advanced features.

Ready to Transform Your Operations?

Start with an assessment to identify your AI opportunities and define a clear roadmap.

Book Assessment

Discover Our Success Story: CL-AI-RA

The automated blog system that revolutionizes corporate communication.

Claira AI Blog System

We created CL-AI-RA, an AI Agent that demonstrates how intelligent automation can transform content creation. Claira analyzes authoritative sources like CIO.com, Ars Technica, The Verge, TechCrunch and Wired, selects only the most relevant news, classifies it, and synthesizes it into unique, WordPress-optimized posts.

Try it Now
Technical guide: how we build AI Agents with n8n →

One AI Agent, Multiple Applications

Internal Newsletters

Keep teams updated with weekly summaries of industry news, without manual effort.

Self-Feeding Blog

Attract and nurture customers with fresh, relevant content, positioning you as a thought leader.

Lead Nurturing via Newsletters

Send automated newsletters to partners and clients to build loyalty, inform, and nurture leads with relevant content.

Virtual Assistant on Telegram

Interacts with leads and partners directly on Telegram, answering questions and qualifying contacts in real-time.

Automated Booking Agent

Acts as a virtual assistant that books appointments, manages calendars, and sends reminders, freeing up your sales team.

Virtual Concierge

The corporate concierge that knows your company, products, and services, assisting customers 24/7.

Want this revolution for your company?

Free consultation, no commitment

Schedule an Appointment
How we do it technically

The Tech Stack: No Black Boxes

Castaldo Solutions designs and builds custom multi-step AI agents for SMEs: RAG (Retrieval-Augmented Generation) architectures on company data, language model fine-tuning and n8n workflow automation. Our AI agents integrate with existing systems and operate autonomously. Real stack: Python, LangChain, Qdrant, Ollama, OpenAI API, Anthropic Claude.

If you're a CEO or entrepreneur

You don't need to understand the technology. You just need to know we use reliable tools, your data stays under control, and the code is your property. You'll see a working prototype in 2–3 weeks.

If you're a CTO or IT Manager

Stack: n8n + Python (LangChain / CrewAI) · RAG with Qdrant · Ollama on-premise · OpenAI / Anthropic API · CRM integration via REST API. Zero vendor lock-in. Documented and delivered architecture.

Technologies we use (and why)

Technology What it does
n8n Low-code workflow automation, system integration
Python + LangChain / CrewAI Multi-step AI agent orchestration
RAG + Qdrant (vector DB) Information retrieval from company knowledge base
Ollama (on-premise) LLM models on your servers, data stays within the company
OpenAI / Anthropic API Cloud LLMs (GPT-4, Claude) for high-quality output
Fine-tuning Training the model on specific company behavior

Real Projects: The Technology Behind the Numbers

Credit Mediation

On-premise RAG Bot: Ollama + Qdrant

Challenge

The client was using Gemini with Firebase to respond to customers, without data privacy control and without AI Act compliance.

Stack used

Ollama · Qdrant · RAG · 60 best practices (20 per service)

Privacy guaranteed, AI Act compliance achieved, response quality improved.

Credit Mediation — Phase 2

Fine-tuning on proprietary business processes

Challenge

The RAG bot was working but responses were slow and not aligned with the company's tone.

Stack used

Fine-tuning · AI Act risk table · Best practices as training data

-40% response times, customer satisfaction increasing for consistency and speed.

Manufacturing

RAG bot for automatic ticket classification

Challenge

The technical office was spending 20+ hours/week on manual management of support tickets.

Stack used

CompanyTech BattlePlan → process PDFs → RAG knowledge base · automatic classification

20 hours/week saved, tickets classified with over 90% precision.

Frequently Asked Questions - AI Services

AI agents are autonomous software systems that perceive context, reason and take actions to achieve defined goals — without continuous human intervention. Unlike a simple chatbot, an AI agent can read emails, update a CRM, classify documents, schedule appointments and coordinate other agents in sequence. At Castaldo Solutions we build custom AI agents for Italian SMEs: integrated with your existing systems (Salesforce, n8n, email, WhatsApp Business), trained on your processes and delivered with code you own. Zero lock-in, measurable ROI in 90 days.
The time required to obtain measurable results depends on the type of implementation, the complexity of business processes, and the volume of data the AI must handle. After the AI project goes live, the first tangible results are already visible within 3 months. Our iterative approach with a rapid prototype (2-3 weeks) allows you to validate the solution's effectiveness before full deployment.
Implementation costs vary based on the complexity of the processes involved and specific business needs. Projects start from a few thousand euros for simple automations, up to several tens of thousands for complex enterprise solutions. During the Discovery phase (free), we analyze your specific case together to provide a detailed and transparent quote, with expected ROI.
Yes, but the exact percentage depends on your business and the processes you automate. Cost reduction comes from eliminating repetitive tasks, reducing human errors, and optimizing workflows. Use our free AI ROI Calculator to discover the specific potential savings for your company and which areas guarantee the highest return on investment.
An AI prototype is a working agent capable of performing a specific task in a controlled environment. In 2-3 weeks, we develop a demonstrative version that allows you to concretely test the solution's effectiveness. The prototype is not yet ready for full production: it requires optimizations for security, scalability, and exception handling. This rapid approach allows you to validate the investment before proceeding with enterprise deployment.
Absolutely! Integration with existing business systems is at the heart of our work. We connect AI Agents with CRM (Salesforce, HubSpot, Pipedrive), ERP, databases, communication tools (email, Slack, Teams), and any other platform via API. You won't need to change your tools: AI adapts to your current technology ecosystem.
AI can exhibit bias and make mistakes, just like humans. For this reason, responsible adoption requires governance, monitoring, and supervision. Our services include not only technical implementation but also strategic guidance for AI Adoption: we define usage policies, supervision workflows, fallback mechanisms, and training for your team together. The goal is to maximize benefits while minimizing risks.
Vertical technical skills are not necessary in your team. However, it is essential to have clear governance on AI tools and knowledge of data sharing policies, especially when interacting with external AI providers. During our AI Adoption journey, we train your team on best practices, responsible data management, and effective use of implemented tools.
RAG (Retrieval-Augmented Generation) retrieves information from a company knowledge base in real time: ideal for internal documents, operational procedures, and frequently evolving FAQs. Fine-tuning adapts the model's behavior to the company's specific style and processes: ideal when consistency of tone, fast responses, and reasoning "like the internal team" are needed. The two techniques are not mutually exclusive: in several of our projects — such as the RAG bot for a client in the credit mediation sector — RAG is implemented first and fine-tuning added in a subsequent phase to improve speed and precision. During the discovery call, we evaluate together the right approach for your case.
Yes. For clients with privacy requirements or AI Act compliance obligations, we implement on-premise solutions with Ollama: the model runs on your company servers, and data never leaves your infrastructure. We have already implemented this architecture (Ollama + Qdrant) for clients in the credit mediation sector, where client data could not be sent to external cloud services. For less sensitive use cases, we use cloud APIs (OpenAI GPT-4, Anthropic Claude) with GDPR-compliant data processing agreements. The choice of architecture always depends on the sensitivity level of the data and compliance requirements.
This is the most common case, not an obstacle. The first phase of our work is always an assessment of existing data: we identify what's there, what's missing, and how to structure it. Data usually already exists — in PDFs, emails, CRM, Word documents — but has never been organized for AI use. The CompanyTech BattlePlan maps these information flows and transforms them into the AI system's knowledge base. For the ticket management bot we built for a manufacturing client, the knowledge base was created from process PDFs extracted during the BattlePlan: zero new data to produce, just existing data organized the right way.

Have more questions about our AI services?

Contact Us for a Free Consultation