Co-founder of SoftInstigate since 2014. Built and operated production systems since 1998: real-time distributed systems and GIS visualization at Artificial Intelligence Software, SOA and EAI integration at Sun Microsystems and SeeBeyond, enterprise content platforms at AKQA and Alfresco, and now cloud-native AI integration and RAG systems on MongoDB. On the commercial side: lead evaluation, tender assessment, partner and vendor management, contract negotiation and execution.
How I work
Commercial and technical together
Separating them is where problems start
Commercial and technical decisions are made together or they become problems for each other. A proposal that ignores technical constraints becomes a delivery crisis. The commercial side defines what gets built and the technical side determines whether it holds.
Tenders and proposals
The proposal is the first architecture decision
A tender response is a technical and commercial commitment made before the team is assembled and the constraints are clear. I assess feasibility, estimate effort, structure partnerships, and frame the technical approach so the proposal can survive delivery.
Decisions under uncertainty
You have to decide before certainty
Commercial and technical decisions are made with incomplete information. When the consequences of being wrong are visible and expensive, in the contract or in the architecture, the quality of the judgment matters more than the volume of the analysis.
What I do
Opportunity assessment
A few hours now save weeks later
Qualifying a lead takes a few hours of feasibility work and technical fit analysis. Starting a project on wrong assumptions takes months to unwind. The cheapest place to kill a bad opportunity is before the first proposal.
Technical and commercial evaluation
What to find before the commitment
Before investment or project commitment, I assess technical maturity and architecture risks. Due diligence is where structural problems surface, while fixing them is still a line item in the budget.
Partnerships and vendors
What a platform costs over twelve months
The proposal price is visible. The integration effort and the operational overhead over the life of the project are the numbers that determine whether the choice was right.
Proposals and delivery
The proposal commits more than people think
A wrong assumption in a tender response becomes a structural problem when the team starts building. Proposals that were technically sound but commercially underpriced have a way of making the delivery team pay for it.
Contracts
What gets delivered is decided here
The contract locks scope and constraints before the first line of code. When the technical reality and the commercial terms disagree at signature, the gap only widens during delivery.
Technical strategy
Architecture that holds under pressure
Architecture reviews, distributed systems, and AI integration. The decisions that matter are the ones that determine system behaviour when the load doubles or the requirements shift. Those are the decisions that are expensive to undo.
AI adoption and architecture
AI is a multiplier of what is already there. It can accelerate development, and it can accelerate decay.
AI follows a pattern: Envision, Experiment, Launch, Scale. Most startups and scale-ups are between Experiment and Launch. They have something working, but the architecture was built for speed, not for the load AI puts on it.
The transition from pilot to production is where decisions become expensive to undo: what happens when the model changes, who owns output quality, how do you handle costs, what is the fallback when the AI is wrong.
Open source
RESTHeart: Agent-ready backend for MongoDB
Facet: Data-driven web framework: turn APIs into HTML, zero code
Ermes Mail: Async e-mail library and CLI for Java
All projects on GitHub →
Teaching
Created and delivered technical courses and workshops for enterprise clients and partner networks across Italy and EMEA. Teaching forced me to articulate why certain decisions are made, which sharpened my own judgment.