How IAG is transforming its network into a system capable of identifying and activating the relationships that can truly make a difference for a startup.
Having a network does not mean knowing how to use it. For a founder, choosing an investor also means choosing the system that will activate around the deal: one that can open up a market, reach a customer, or quickly provide access to critical expertise.
A long list of contacts remains only potential value until there is a method for identifying, at the right moment, the person best suited to address a specific need.
Because founders do not need more introductions: they need the ones most likely to turn into relevant conversations.
The Limits of the Traditional Network
In most organizations, the network still lives in people’s memories: in saved contacts, past conversations, WhatsApp groups, and the intuition of someone who “might know somebody.”
This model can work, but it depends on memory, chance, and the portion of the network that any one person happens to be able to see at that moment.
The result is a structural bias: the most visible connections tend to surface, rather than necessarily the most relevant ones. Two founders with similar needs may therefore receive very different answers within the same ecosystem, while a rich network ends up behaving like a much smaller one.
The right people are often already there. What is missing is a system capable of surfacing and activating them at the right time.
That is where IAG’s work begins.
The Network as a Graph, Not a CRM
A network is a graph: nodes - founders, angels, managers, customers, operators, experts — connected by relationships.
The quality of that graph depends on the strength of those connections, the experience each person brings, their proximity to a specific need, and the paths that lead to the right person.
Knowing that a contact exists is of limited value. What matters is understanding how to reach them: through whom, with what level of trust, and with what probability that an introduction will turn into a useful conversation.
This is where a graph differs from a CRM.
A CRM can tell us that someone exists in the database, what role they hold, or which company they work for. A graph attempts to understand what exists between people: which relationships are direct, which rely on an intermediary, which are recent, which have been cultivated over time, and which are grounded in genuinely shared experiences.
A list answers the question, “Who do we know?”
A graph allows us to address a more useful one:
“What is the most credible path to reach the person we need?”
The path to the right personWe call this work network engineering: making the network navigable, understandable, and actionable, while using human judgment more effectively rather than replacing it with an algorithm.
The goal is to remove unnecessary steps and create more room for high-quality interaction. Data does not replace relationships: it helps identify the relationships worth building.
Network engineering means giving those who know the founders, investors, and the market a broader information base on which to exercise their judgment — not assigning people a number and letting a machine make the decision.
Technology narrows the field, surfaces paths that memory alone would fail to uncover, and makes alternatives comparable.
The final decision remains human: whether an introduction makes sense, whether it creates value for both parties, how it should be prepared, and when it should happen.
What We Built That Did Not Exist Before
To make this approach operational, we built a Network Intelligence system combining data, custom-developed digital tools, and human expertise built over almost twenty years of working with founders and investors.
The first layer creates an up-to-date picture of the people who make up the network and how they participate in IAG’s activities.
It collects concrete signals: investments, participation in initiatives, training, and support provided to portfolio founders.
For a startup, this means not starting from an undifferentiated list of contacts, but knowing which members are active and in which areas they may be able to help.
These dimensions remain separate because they describe different behaviors.
Someone who invests consistently, someone who contributes operational expertise, and someone who opens commercial doors may all be highly relevant — but for different needs.
Reducing this variety of contributions to a single score would eliminate precisely the information needed to decide whom to activate.
The second layer concerns the quality of relationships.
It verifies a connection between two people using concrete signals: history of interactions, continuity, reciprocity, channels used, meetings, and shared professional contexts.
Appearing in the same database is not enough to demonstrate a strong relationship. The system looks for evidence that makes the connection credible and shows how complete the available information is.
The third layer addresses the most operational question:
Who is the best bridge to reach a specific person?
It explores the IAG network, compares possible paths, evaluates the most promising ones, and produces an explainable shortlist.
And if the data does not reveal a sufficiently reliable bridge, the system flags this, allowing human intervention to complete the last mile.
Together, these tools reduce the distance between the network’s relational capital and the moment when that capital needs to become useful to a startup.
Previously, this information existed in different places, across operational sources and within people’s individual knowledge.
Today, we can connect these pieces of information and use them within a coherent process.
From network to best pathFrom Request to Outcome, Faster
For a startup, the process should be simple.
It starts with a real need: entering a new vertical, validating a sales channel, speaking with potential enterprise customers, finding an advisor with specific expertise, or preparing for international expansion.
The most delicate step is making that need precise enough to guide the search.
“We want to enter the automotive sector,” for example, is still too broad.
We need to clarify which company or profile the startup wants to reach, what role the relevant person should hold, and what outcome the startup wants to achieve.
Only then can we translate the need into search criteria, navigate the network, and activate a small number of highly targeted connections.
Fewer steps. Fewer random attempts. Greater precision.
Imagine a startup that wants to initiate a conversation with a large industrial group.
The traditional approach would be to ask several people whether they know someone inside the company and gather a list of possible names.
But knowing someone does not necessarily mean having a relationship with them that can actually be activated.
Our goal is to start with the person the startup needs to reach, explore the possible bridges within the network, and understand which relationship shows the strongest signals.
The team then adds what data alone cannot know: the value of that bridge, the founder’s background, the counterpart’s sensitivities, the company’s current situation, and the best way to frame the request based on the people involved.
At IAG, we do not automate the introduction: we improve the decision that comes before it.
The objective is not to “make more intros.”
It is to increase the probability that every introduction leads to something: a useful conversation, a pilot, a customer, a key hire, or a better-informed decision made in less time.
And for a founder, that can make a tangible difference.
From request to the right connectionTime is a limited resource: every month spent searching for the right person is a month taken away from building the product, selling, and growing.
For this reason, the value of a network should not be measured by the number of available contacts, but by the time it can give back to the founder and by the quality of the opportunities it can activate.
Network Engineering According to IAG
IAG has always had a distinctive characteristic compared with funds and other institutional players: the people who invest capital also invest experience, time, and access.
Today, we want to make that asset easier to use.
This is an important distinction.
A network made up of angel investors, founders, managers, and professionals brings with it relationships built through direct experience in the market.
It does not simply provide contacts: it provides context, credibility, and an understanding of the dynamics through which a door can actually be opened.
At the same time, the size of the network makes individual knowledge alone insufficient.
No single person, however experienced, can remember every relationship, track how each one evolves, and compare all possible paths in real time.
Our advantage lies in the combination of human experience and purpose-built tools.
We are building a more structured way to understand startups’ needs, map the expertise and relationships within our ecosystem, identify the most effective paths, and measure what happens after an introduction.
Data makes the network visible. Tools make it possible to explore it. People give meaning to what emerges and decide how to turn it into useful action for the founder.
Without people, data and tools remain inert.
A graph is not a static snapshot: the people who use it continuously enrich it.
Every new relationship and every outcome adds context and makes the system more precise. The more intentionally members use the network, the more value they can extract from it.
A network that improves with useThe outcome of an introduction matters as well.
Knowing that a connection exists is only the starting point. Understanding whether it generated a conversation, a meeting, or an opportunity enables both the system and the people using it to make better decisions in the future.
The network therefore becomes an infrastructure that improves through its own use.
For a founder, this system shortens the distance between a need and the person who can address it.
The founder does not have to navigate a complex network alone: they define a concrete priority and rely on a team that combines the depth of the IAG network with tools capable of making that network usable.
Capital opens the door. What happens next depends on the people who work within the network every day.
IAG wants to be that system: a network that does not remain on paper, but works alongside founders when they need it.
Because the value of an investor is not visible only at the moment they sign a funding round.
It becomes visible when a founder has a difficult door to open, a complex decision to make, or only a few weeks to find the right person.
It is in those moments that a network stops being a promise and becomes a tangible advantage.
