AGI-ONE is built by a compact senior human team operating an AI-native execution model. Humans own strategy, architecture, security, quality, customer commitments and release accountability. The AI Division increases throughput and repeatability under governance.
The current structure reflects the company stage: a founder-led platform, senior contributors, advisors and an AI Division that has already produced significant technical output. The next step is to formalize roles and expand the operating team around design-partner delivery.
The platform is the product of a long runway: AI preparation before the market wave, systematic research after ChatGPT, and sustained execution on an operating layer rather than a single application.
Davide Ciliberto completes AI specializations including Machine Learning with Andrew Ng and Deep Learning / Neural Networks, years before enterprise AI adoption became mainstream.
Models, agent architectures and enterprise AI failures are analyzed. The conclusion: the missing piece is not a better model. It is the operating layer.
The first pillars take shape: model abstraction, gateways, agent patterns, knowledge and orchestration. The work starts founder-led.
Specialized agent profiles, delivery standards and documentation processes turn AI from a tool into a governed internal workforce.
CREIMS, Team Work, AI-ONE and Hermes form the request-to-production loop. The next phase is 3-5 design partners for September 2026 beta validation.
Every critical decision, customer commitment, architecture choice, security boundary and release approval remains human-owned. The AI Division adds leverage; it does not remove accountability.
Computer scientist, project manager and senior technology leader with 30+ years in digital and IT, director-level experience managing a 50+ person data management business unit, AI specialization since 2018 and multiple startup experiences. Owns product thesis, platform architecture, AI Division design and first GTM validation.
LinkedIn →PhD with international research experience and nearly ten years in IT and consulting, most recently at EY. Previously worked as Data Engineer on Davide's team. Strategic contribution: platform data area, enterprise data patterns and future design-partner data workflows.
Computer Scientist with a strong background in Natural Language Processing (NLP), Machine Learning, and enterprise data platforms. Nearly ten years of experience delivering enterprise data solutions across data engineering, streaming architectures, analytics, platform integration, and AI-driven initiatives, gained through work in consulting and enterprise environments, including roles at Oaks and Reply.
The current team shape is designed for the beta stage. The scale-up path adds dedicated execution capacity around engineering, security, product, customer delivery and go-to-market.
The first additions strengthen execution, deployment, security, product delivery and commercial validation.
Architecture accountability, platform hardening, engineering standards and roadmap execution.
Productization, frontend/backend delivery, integration and release velocity.
Deployment repeatability, reliability, security, observability and enterprise readiness.
Design-partner onboarding, workflow definition, KPI measurement and feedback loop.
Pipeline, pricing validation, partner channel and conversion from pilot to paid customer.
AI Act, GDPR, contracts, IP, procurement readiness and due diligence support.
Each staff agent has a defined scope and delivery role. Agents accelerate bounded work; humans define strategy, approve decisions, own quality and sign off releases.
AGI-ONE’s AI-native model works only when each critical area has a human owner and an AI support layer. The model is designed to increase execution capacity without losing responsibility.
Human owner: founder / product lead. AI support: product, research and documentation agents.
Human owner: founder / technical lead. AI support: architecture, gateway and platform agents.
Human owner: security/compliance lead. AI support: security, IAM and AI Act/GDPR agents.
Human owner: engineering/SRE lead. AI support: QA, release, observability and operations agents.
Human owner: product/customer success lead. AI support: CREIMS, documentation and support agents.
Human owner: founder/GTM lead. AI support: research, sales enablement and market intelligence agents.
Repository metrics show sustained internal execution. The next milestone is to translate that internal velocity into measurable value for design partners.
AGI-ONE has a working platform, a defined operating model and a clear team scale-up path. The next phase is to formalize roles, add dedicated execution capacity and run design-partner validation.