Most venture capital firms have a CRM problem they do not talk about. The partners use it inconsistently. The associates maintain it out of obligation. And when it is time to find out who introduced that promising founder three years ago, everyone ends up searching through email.
The irony is that VCs understand better than anyone that relationships are the product. Eighty percent of funded deals come through warm introductions. The firms that track those relationships systematically have a measurable edge. Yet most funds run on some combination of spreadsheets, Notion databases, and whatever CRM their ops person set up years ago.
We have helped emerging managers and established funds move to Attio, and the pattern is consistent: the flexibility to model your actual fund structure - not some generic sales pipeline - changes how your team thinks about relationship data. Here is what we have learned about building CRM infrastructure for VC.
The problem with generic CRMs for venture capital
Salesforce was built to track linear sales pipelines: leads become opportunities become closed deals. That mental model does not map to how venture works. A founder you pass on today might be your best portfolio company in three years. An LP relationship spans decades and multiple funds. A co-investor on one deal becomes a competitor on another.
When we audit VC firms existing CRM setups, we typically find the same issues. Deal records exist in isolation, disconnected from the funds they will draw from. LP information lives in a separate spreadsheet because the CRM cannot model capital commitments and drawdowns. Portfolio company tracking happens in yet another tool because the CRM treats everything like a sales opportunity.
The result is fragmented data that requires constant manual reconciliation. Your ops team becomes a human API, copying information between systems. And the relationship intelligence that should be your competitive advantage stays locked in individual inboxes.
Attio flexible data model solves this by letting you create the objects and relationships that actually exist in your business. But flexibility without intention just creates a different kind of mess. The key is designing your workspace around how your fund actually operates.
What VC teams actually need to track
After working with multiple funds, we have identified the data relationships that matter most. This is not about features - it is about modeling the complexity that already exists in your business.
Fund structures as separate entities
Fund I, II, and III are legally distinct. Your CRM should reflect that. Each fund has its own LPs, capital commitments, investment pace, and reporting requirements. When you make an investment, you need to know which fund it draws from.
LP relationships across time
An LP is not just a contact - they have commitment amounts, capital called to date, distribution history, and communication preferences. Some LPs are in multiple funds. Your CRM should show you the complete relationship, not just their latest interaction.
Deal flow with source attribution
When a deal closes, you should be able to trace it back to who made the introduction. This is not just for thank-you notes. Understanding which relationships generate quality deal flow shapes how you allocate time.
Portfolio companies as living records
After you invest, the relationship changes. You need to track board seats, follow-on decisions, key metrics, and team changes. This is fundamentally different from tracking a closed deal.
The co-investor network
Track who you have syndicated with, who brings you into deals, and who you would want to partner with again. This network is an asset that should be visible in your CRM.
Investment Committee history
Document what was discussed, what concerns were raised, and what conditions were set. When you revisit a company for follow-on, this context matters.
How we build Attio for VC firms
Our implementation typically takes 2-3 weeks and follows a consistent structure. We start by mapping your fund actual workflow - not what you think it should be, but what your team actually does day to day. Then we build a data model that supports that workflow.
The core insight is that a VC firm is not running one pipeline; it is managing multiple interconnected processes. Deal sourcing has its own rhythm. LP relationships operate on a different timescale. Portfolio support is ongoing. Each of these needs its own views and automation, but they all connect through the underlying relationship data.
We set up email sync from day one so that relationship history starts building automatically. We configure notifications so that partners know when portfolio companies hit milestones or when LP commitments come due. And we build reports that actually answer the questions your team asks - not generic dashboards, but specific views like deals sourced by partner this quarter or LPs up for re-commitment in the next fund.
Custom objects we typically create
Funds
Each fund as a separate entity with its own tracking
- •Fund name and vintage
- •Target size and amount raised
- •Investment period status
- •Management fee structure
- •Linked LPs with commitment amounts
Limited Partners
LP relationships across your fund family
- •Commitment by fund
- •Capital called to date
- •Distribution history
- •Communication preferences
- •Re-up likelihood for next fund
Portfolio Companies
Post-investment tracking that evolves with the company
- •Investment amount and ownership
- •Board seat holder
- •Key metrics dashboard
- •Follow-on investment history
- •Exit status and returns
Co-Investors
Your syndicate network
- •Deals done together
- •Typical check size
- •Sector focus
- •Quality of deal flow shared
- •Relationship owner
Integrations that matter
Is Attio right for your fund?
We are an Attio partner, so you should factor that into what we say. But we also turn away funds when Attio is not the right fit. Here is the honest assessment:
Attio works best for funds that want customization without the Salesforce complexity tax. If your team is technical enough to appreciate a modern interface and you want to build exactly what you need rather than adapt to someone else is workflow, Attio is compelling.
Affinity, the incumbent in this space, has better relationship intelligence out of the box. Their algorithms for tracking relationship strength and finding intro paths are genuinely good. If that is your priority and budget is not a constraint, Affinity is worth considering. But Attio costs about a third of the price for comparable seat counts, and the customization flexibility is significantly better.
Attio is a good fit if...
- ✓You want to model your actual fund structure, not adapt to a template
- ✓Your team values modern, fast software
- ✓You are building institutional processes as you scale
- ✓Budget matters and you do not want to pay for features you will not use
- ✓You have some technical comfort with customization
Attio might not be right if...
- —Relationship intelligence is your primary requirement
- —You need enterprise compliance features today
- —Your team resists learning new tools
- —You want something that works out of the box with zero setup
Frequently asked questions
For most funds, 2-3 weeks from kickoff to team adoption. The first week is discovery and data model design. The second week is building and data migration. The third week is team training and workflow refinement.
Yes. We have migrated funds from both. The process involves exporting your existing data, mapping it to the new Attio structure, and running validation checks before going live. We typically do this over a weekend to minimize disruption.
Attio builds relationship history through email sync and meeting tracking. It does not have Affinity algorithmic relationship scoring, but you can build custom fields to track relationship strength manually or through automation rules.
Attio supports role-based permissions, so you can restrict LP financial data to relevant team members. We typically set up separate views for investment team vs. ops vs. partners with different access levels.
Evaluating alternatives?
Read our Attio vs Affinity comparison →