Why teams switch from Affinity to Attio

Affinity pioneered relationship intelligence for investors. The core idea is that every email and meeting your team has ever had is data: Affinity reads it and builds a map of who in the firm has the strongest connection to any given person or company. When you want a warm intro to a founder, it tells you which partner should send it. Contacts and activity are captured automatically, so the CRM stays current without anyone updating it, and enrichment comes from premium data partners like PitchBook and Crunchbase. Roughly 45% of the top 100 VC firms use it.

Attio is built around a flexible data model. You create custom objects, define how they relate, and shape the system around how the firm actually works — portfolio companies, LPs, the fundraising pipeline, the co-investor network and operational work, each with its own structure, in one system. AI sits in the data layer rather than beside it, and you can start free and grow into paid tiers without a sales call.

We are not going to pretend this gap does not exist. Affinity's relationship scoring is its real moat.

Attio syncs email and tracks interaction history, so you can see the firm's communication with any contact. What it does not do is score relationship strength algorithmically or rank intro paths automatically. You can get partway there with custom attributes and automations tracking last contact, frequency and owner — useful, and enough for many funds, but not the same as Affinity's graph.

If your sourcing motion depends on systematically working a warm network, weigh this carefully before you switch.

Affinity is shaped for deal flow. That focus is a strength for sourcing and a limit everywhere else: when the firm needs to track things that are not deals, you are working against the grain of the tool. In practice that is why portfolio support, LP relations and fund operations so often end up in spreadsheets sitting next to Affinity.

Attio lets you model any of those as a first-class object — portfolio company health, LP commitments and reporting, talent networks shared with founders, fund operations — in one structured system. For a fund that wants a single source of truth across the whole firm rather than just the deal pipeline, this is the deciding factor.

Affinity uses AI mostly to keep the relationship graph current and to enrich records.

Attio builds AI into the data model. AI attributes are custom fields that fill themselves: one that summarises a company, one that classifies it into a tier, one that runs a web-research agent to pull funding stage and headcount from outside sources. Call intelligence joins meetings, transcribes them and writes the results back onto records. AI workflow steps let automations classify and route without a human.

For a fund, that means an analyst stops doing the manual research and data entry the CRM can now do on its own.

A migration is not an export and an import. The real work is mapping contacts, organisations, deals and interaction history across; rebuilding deal flow as a pipeline that matches how the firm sources and decides; modelling portfolio, LPs and co-investors as their own objects; setting up enrichment and AI attributes so records stay current without manual work; recreating the reports partners actually open; and being honest about the relationship-intelligence gap while building the closest practical version. The goal is not to rebuild Affinity inside Attio — it is to build a CRM that fits the whole firm at a fraction of the renewal.

• Move to Attio when the CRM needs to cover more than deal sourcing, when the Affinity renewal is large and the team is small, when you want portfolio, LP and operational work modelled in one system, when you want AI doing research and data entry inside the CRM, or when you would rather redesign than carry years of CRM debt forward.
• Stay on Affinity when warm-intro sourcing is the core of how you win deals, when the relationship graph alone justifies the contract, or when premium funding-data enrichment is non-negotiable.