Agent-Powered Software: AI Agents and People, Working Together

The key design decision in agent-powered software is the split of work. In the systems we build: Agents handle

• collecting and combining information from documents, emails and systems
• repetitive multi-step tasks such as data entry, reconciliation, checks and follow-ups
• first drafts of quotes, reports, replies and summaries
• watching for events and starting the right workflow People handle
• setting goals and priorities
• approving actions with real cost, risk or customer impact
• exceptions, edge cases and anything the agent isn't sure about
• relationships, negotiation and final decisions Getting this split right is what turns AI from a demo into hours saved every week.

We focus on workflows with a clear business case:

• Document-heavy operations. Agents read contracts, invoices, specifications and tickets, extract what matters and answer questions with sources, using agentic RAG over your own documents.
• Back-office automation. Order handling, data reconciliation, reporting and follow-ups that used to take hours run as agent workflows, with people approving the exceptions. When a simple workflow tool is enough, we'll say so. See n8n vs custom AI automation.
• Internal copilots. Agents that work inside your ERP, CRM or custom tools, preparing actions for your team to confirm in one click.
• New agent-powered products. For founders and product teams, we act as the senior engineering partner that designs, builds and launches an agent-native product.

A clear job and the right tools

Every agent has one well-defined job and a small set of tools it's allowed to use: specific APIs, database queries, document search, sending a draft. Narrow agents are easier to test, cheaper to run and far more reliable than one agent that tries to do everything.

Grounded in your data

Agents are only as good as the information they work with. We build clean data pipelines and retrieval over your documents and systems, so agents answer and act on your real data, with sources people can check.

Human-in-the-loop by design

We design the approval points before writing any code. Low-risk actions run automatically; higher-risk actions wait in a review queue; uncertain cases go straight to a person. People see what the agent proposes, why, and what data it used.

Guardrails, permissions and audit trail

Agents get the minimum access they need. Spending limits, rate limits and validation stop them acting outside their job. Every step is logged, so you always know what happened, can explain it, and can undo it.

Measured and improving

We test every agent against real scenarios before launch and keep measuring in production: accuracy, cost per task, time saved and how often people correct the agent. Those corrections become the data that makes the agents better.

Built on solid software engineering

Agents still need good software around them: APIs, interfaces, security and deployment. We build on modern web application frameworks and deploy to AWS, Vercel, Cloudflare, Railway or on-premise, with tracing and cost dashboards from day one.

• Senior, hands-on team. Your agents are built by engineers who ship production AI, not by juniors learning on your budget.
• Engineering, not prompt-only work. We write tests and evals, own the infrastructure, and care about cost, speed and security.
• People-first design. We design the work for agents and people together, so your team trusts the system and actually uses it.
• Bilingual, Europe-based delivery. Our head office is in Italy. We work in English and Italian, under EU contracts and GDPR.
• Production track record. See our case studies for AI and automation systems we've shipped.

Tell us about a workflow that eats your team's time. In a short call we can usually tell you which parts an agent can take over, where people should stay in control, and what the fastest path to value looks like. Talk to us and we'll tell you straight, no sales theatre.