A design studio for Generative AI systems in public administration, finance and industry — not a software house, not an agency, not a course.
We design and bring into production reliable AI systems for real processes: integrated with existing systems, with data under control, human oversight on every assisted decision, and concrete KPIs from the Assessment onward.
Bring us a process. In two weeks we'll tell you if AI makes sense, what architecture it needs, and what return to expect.
Technology-agnostic: we adapt to your specifications
Before any development commitment: one high-impact process analyzed to see whether, where and how AI creates value — including the answer no.
Process mapping
How the analyzed process works today: activities, roles, systems involved, timing and critical points.
Feasibility assessment
Whether AI is the right answer to the problem, or whether simpler, more effective alternatives exist.
High-level architecture
Which of our systems (Document Intelligence, AI Agents, Enterprise Search...) would be needed, and why.
Indicative estimate
Expected impact, realistic complexity, intervention priority, and roadmap.
AI cannot be improvised. It must be designed.
A discipline that combines research, engineering and business.
Applied research
Researcher in Data Science: scientific method to define hypotheses, metrics, evaluation datasets and reliability criteria.
Executive education
Teaching at Bologna Business School and continuous dialogue with managers, CIOs and innovation leaders.
Production engineering
Software systems that stay in daily use, integrated with the management systems, databases, APIs, document systems and IAM already in place. Not lab prototypes.
Partners & programs
AWS Partner · ART-ER · NVIDIA Inception Program · Emilia-Romagna Region
Futura AI is not a startup experimenting with artificial intelligence. It is a specialized team that designs and ships Generative AI systems into production, for real processes and complex organizations. And the reasons clients call, in the end, come down to four.
Automating complex document processes
Case files, contracts, CAD drawings, payment references: documents read and transcribed by hand, with long turnaround times and errors paid for downstream. We read, classify and extract them automatically, with human review on uncertain cases.
Automating operational work with AI Agents
Repetitive sequences that read data, consult documents and execute steps within defined rules: payment reconciliation, recurring-call handling, case preparation. With confidence thresholds and human escalation.
The method
Making company knowledge queryable
Internal regulations, technical manuals, procedures: archives where people know where to look but take too long to find and verify. Enterprise Search with sources always cited, coherent permissions and verifiable answers.
Taking AI to production in regulated environments
Where sensitive data, audit trails and AI Act compliance are non-negotiable: cloud, on-premise or hybrid architectures, application guardrails, decision traceability and KPIs monitored after go-live, not just in a demo.
The method
The value of an AI project is measured in its effects, not in the technology used.
Reduced time
From 4-5 person-hours to a few minutes per quote in a verified project with Gruppo SAG; from days to an immediate chat-based view in a verified project with FBS SPA.
Reduced costs
The process cost baseline — person-hours, volumes, cost of error — is measured during the Assessment; the actual savings are verified after release on the same indicators. We don't publish an aggregate figure here, because it varies from process to process.
Fewer errors
86% accuracy in automatically extracting dimensional data from CAD drawings, measured on a verified project with Gruppo SAG.
Controlled automation
Payment reconciliation and handling of recurring calls, with confidence thresholds and human escalation on uncertain cases.
Productivity
Measured by comparing requests, cases or activities handled with the same resources before and after release, on the indicators defined in the Assessment — consistent with the time savings and automation measured above, without an aggregate figure valid for every process.
ROI
Economic and operational indicators defined during assessment and monitored after release, not estimated only at project end.
We measure what we can prove.
Published results start from verifiable processes, not generic benchmarks.
Find out if your process is readyEvery number stated on this site has an article explaining the sample, the method and the limits of the measurement. It is the text a procurement team can verify point by point.
Not lab prototypes. Generative AI systems integrated into our clients’ daily operational workflows.
Industry & Manufacturing
Manual reading of dimensional callouts and ISO compliance verification on complex engineering drawings.
86%
dimension extraction accuracy
4–5h → min
quote turnaround time
Banking & Finance
Unstructured free-text payment descriptions matched against debtor registry across hundreds of thousands of annual flows.
92%
automated reconciliation
8%
routed to human verification
Technology & Services
High-volume repetitive calls during peak hours and weekends overloading support teams.
90%
calls resolved autonomously
70%
correct escalation on edge cases
Music & Consumer Tech
Collaborative filtering failing on new releases, newly onboarded users, or niche tracks without listening history.
85%
relevance judged by real users
65%
catalog coverage achieved
Generative AI systems for environments where processes, data, and compliance cannot be an experiment.
Systems
not chatbots
Architectures connected to your processes, data and existing systems — not an isolated assistant plugged into a model.
Governance
not black boxes
Audit trails, guardrails and human oversight on every assisted decision: designed for regulated contexts, not added later.
Results
not promises
Processing time, avoided errors, freed hours: every project has indicators agreed from the Assessment onward.
We work in contexts with regulated processes, sensitive data and high security requirements. Each sector has different operational problems, priority systems and KPIs.
Every project follows a precise framework, designed to reduce risk and make results measurable from the very start.
This is not a theoretical method: it is the sequence we apply, adapted to each client's technical, regulatory and organizational constraints.
For us, security is not a final chapter of the project: it is a design requirement. An AI system that exposes data, can be manipulated by malicious input, ignores permissions or leaves no trace of its decisions is not ready for production.
Application guardrails
Input and output filtering, response validation, limits on executable actions and explicit handling of cases where the system must stop.
Prompt injection defense
Every retrieved piece of content from documents, pages, emails or knowledge bases is treated as untrusted input: instruction isolation, sanitization and action control.
Data governance
No training on client data without explicit authorization, environment separation, permissions aligned with existing roles and policies.
On-premise & hybrid
Cloud, on-premise or hybrid deployment based on data residency, operational continuity, audit requirements and existing infrastructure.
Audit trail & human-in-the-loop
Decisions, sources and relevant steps are traced; high-impact actions remain subject to human review or confirmation.
AI Act & compliance alignment
Risk classification, technical documentation, transparency and operational accountability are considered from the design phase.
Red teaming, adversarial testing and edge-case behavior checks are part of validation: a system goes into production only when accuracy, robustness, security and traceability have been tested on realistic cases.
Before designing guardrails and audit trails, the process itself has to be checked for AI readiness.
Find out if your process is readyAn assessment on a single high-impact process, not a generic demo: in two weeks you'll know if AI makes sense, what architecture it needs, and what return to expect.
Request an AI AssessmentNo price list: the quote is built around the process. An AI Assessment starts indicatively at €20,000.
You don't always need a custom-built project.
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