👋 Hi, I’m Andre and welcome to my newsletter Data Driven VC which is all about becoming a better investor with data and AI.
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The Tools Converged. Adoption Is Still Wildly Uneven.
Majority of modern VC funds run on the same tools. The 2026 DDVC Landscape contains unique insights from 345 funds, including their most frequently used vendors, where adoption of AI is the most mature & where it’s lacking.
Sourcing, screening, and DD score 3.4 out of 5 on our AI adoption scale. Engineering and infrastructure sit close behind at 3.3. Legal and compliance sits at 1.8, the lowest score on the value chain.
Interestingly, at the largest funds, that gap gets wider. Indication that the bigger the teams, the higher the inertia to get going.
The Modern VC Tool Stack
Our Landscape report grouped the tools VCs actually use into five clusters.
Data. Harmonic, Findem, Evertrace, PitchBook, Specter, Coresignal, Crunchbase, Dealroom, CB Insights : the sourcing and intelligence layer VCs lean on to track companies and talent.
CRM, fund, and portfolio management. Vestberry, Carta, Affinity, Attio, Visible, Pipedrive, HubSpot, Salesforce, Rundit: the backbone for managing deal flow, cap tables, and LP/portfolio reporting.
Productivity. Slack, Granola, Wispr, Gamma, Notion, Airtable: how teams communicate, run meetings, and capture notes day to day.
Agents and automations. Kruncher, Claude, Cursor, ChatGPT, n8n, Langdock, Zapier, Perplexity, Gemini: the most valuable layer of the stack, where VCs are implementing AI for research and workflows.
Infrastructure. Foresight, Exa, Supabase, GitHub, Pinecone, PhantomBuster, Cloudflare, Google BigQuery, AWS: the systems powering search, data, and hosting.
Most of this list is now a commodity purchase. Any firm with a budget and the ability to cut through the noise can stand up a comparable stack in no time.
I've tracked VC tools since 2017, when the list I kept ran about 100 deep. It passed 1,000+ tools in 2025. My own working stack went the other direction.
I consolidated it from the peak of 80+ tools in 2024 down to about 30 tools in January this year, and most of them map straight onto the five clusters above: Affinity, Vestberry, and Carta for CRM; Harmonic, Dealroom, and Evertrace for data; Claude, ChatGPT and Gemini as the assistants; n8n and Zapier running the automation layer.
Full deep dive on my top 30 tools for 2026 here.
Access Versus Adoption
If everyone uses the same tools, is there still a way to generate alpha? My clear answer is yes - via actual adoption (don’t underestimate how difficult it is to change habits…), custom workflows, and most critically by fusing public data with proprietary workflow and decision data.
While we’ve covered the public vs private data part in detail in the past, the Landscape report went deep into custom workflows and AI/tool adoption. In the chart below, you can see it split by function, on a scale of 1 (=low) to 5 (=high).
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