The average VC fund uses 8–12 software tools to run its operations. Most funds spend $60,000–120,000 per year on their tech stack — and the ROI difference between a well-configured stack and a cobbled-together one shows up directly in deal quality and LP relationships.
I've been on both sides of this: as a founder getting invested in, and as an investor building out my own stack. The category leaders have consolidated significantly since 2022. Here's what the modern VC tech stack actually looks like — by category, by fund size, and with real pricing.
The VC Tech Stack by Category
Every fund needs coverage across five functional areas. The tools that win in each category are different depending on fund size, strategy, and check size.
Auto-captures every email, meeting, and LinkedIn touch. Surface relationship scores for warm intros.
AI-powered signal detection across 100M+ companies. Pre-announcement deal discovery at seed and Series A.
Centralized KPI dashboards from portfolio companies. LP reporting and investor update aggregation.
Cap table, SPV management, LP capital calls, K-1 generation. The back-office foundation.
Deal memos, IC meeting notes, portfolio wiki. Most funds run a hybrid Notion + Google Docs setup.
The VC CRM: Where Most Funds Get It Wrong
The CRM is the most important tool in the VC stack — and the one most funds configure poorly. The mistake most emerging managers make: treating it like a Salesforce-style sales pipeline instead of a relationship intelligence system.
Affinity won the VC CRM market by auto-logging every interaction across Gmail, calendar, and LinkedIn without any manual data entry. The relationship strength scoring is the actual moat — it surfaces who your GP has a warm path to a founder through, saving the 20-minute "who do we know at X?" meeting.
4Degrees is the closest competitor and often preferred by smaller funds ($20–50M) for its cleaner UI and lower cost. It does most of what Affinity does but with less enterprise overhead.
Neither tool works without discipline on tagging. The funds that extract the most value tag every contact by sector, stage, geography, and relationship type from day one. Retrofitting tags after 3 years of unstructured data is one of the most painful fund ops projects I've seen.
Deal Sourcing: The Data Layer Driving Alpha
PitchBook and Crunchbase remain staples for market research and comp analysis. But for finding deals before they're shopped, the category has shifted to signal-based discovery platforms.
Harmonic has become the go-to for emerging managers. It tracks 100M+ companies using signals like hiring patterns, LinkedIn headcount growth, and web traffic to surface companies that are scaling before they raise. A fund using Harmonic properly can identify a Series A-stage company 3–6 months before it starts its formal process.
Larger funds supplement with proprietary tools. Sequoia has built internal ML models that score companies by velocity metrics. a16z runs automated research pipelines using Claude and GPT-4o to synthesize market maps. Most funds below $200M don't have the engineering capacity to build these — which is why Harmonic and similar tools are so valuable.
What top funds are using for sourcing in 2026
Portfolio Monitoring: The Unglamorous Category That Separates Good GPs
Most funds underinvest here. They collect investor updates via email, paste them into a spreadsheet, and call it portfolio monitoring. The funds that compound LP trust — and get re-ups — build systematic monitoring from Fund I.
Visible.vc is the category leader for sub-$200M funds. It sends automated data request emails to portfolio companies, aggregates the responses into dashboards, and generates LP reports with your fund branding. The LP portal alone justifies the cost — LPs can see their portfolio exposure and DPI without emailing the GP.
Juniper Square is the institutional-grade platform used by larger funds managing $500M+ in AUM. It handles LP capital call notices, K-1 distribution, fund accounting integration, and secondary transfers. The overhead is higher but the audit trail is worth it at scale.
Many emerging managers supplement monitoring with a custom Notion wiki — one page per portfolio company, updated quarterly. It's low-tech but highly effective for funds with 15–25 companies in a portfolio. Track it on the VC Performance dashboard to see how your metrics compare to industry benchmarks.
AI Is Now a Layer on Top of Everything
The most significant shift in the VC tech stack since 2023 isn't a new category — it's AI being layered over every existing tool. Every category leader is building AI features. Every fund is experimenting with AI-assisted research.
The funds using AI most effectively aren't replacing analysts — they're giving each analyst 3x the research throughput. A solo GP with the right AI stack can run deal sourcing and portfolio monitoring that would have required 2–3 analysts five years ago.
What the Full Stack Costs by Fund Size
| Fund Size | Annual Stack Cost | Key Tools |
|---|---|---|
| Solo GP / $5–15M fund | $15,000–35,000 | 4Degrees, Crunchbase, Visible, AngelList admin, Notion |
| Emerging manager / $25–75M fund | $50,000–90,000 | Affinity, Harmonic, Visible, Carta, Notion |
| Established fund / $100–250M | $90,000–150,000 | Affinity, PitchBook + Harmonic, Visible or JQ, Carta, Zoom, Slack |
| Large fund / $500M+ | $150,000–300,000+ | Affinity, PitchBook enterprise, Juniper Square, Bloomberg, custom AI tools |
Where Most Emerging Managers Get the VC Tech Stack Wrong
After advising 20+ emerging managers on their ops setup, the same mistakes come up repeatedly:
✕ Starting with spreadsheets
Migrating deal data to a real CRM after 2+ years is expensive and painful. Set up Affinity or 4Degrees before your first deal closes.
✕ Buying PitchBook first
PitchBook is great for research but overkill for sourcing at sub-$50M. Start with Harmonic + Crunchbase Pro and upgrade when the fund warrants it.
✕ No portfolio monitoring system
Collecting investor updates by email means you're always 90 days behind. Even a free Visible plan forces structure into the process from day one.
✕ Skipping the tagging system
An untagged CRM is just a contact list. Define your taxonomy for sector, stage, relationship type, and lead source before importing anyone.
The VC tech stack isn't overhead — it's deal infrastructure.
The fund with the best CRM configuration, the cleanest data, and the most disciplined tagging will see more deals, win more competitive processes, and return more capital. Software is now a competitive advantage in venture.
Track VC fund performance and benchmarks on the VC Performance dashboard. See how funds compare on DPI, TVPI, and IRR at Value Add VC. Originally published in the Trace Cohen newsletter.