Top 5 AI Tools I Use as a Venture Capital Investor

Why AI is becoming mandatory in VC workflows? It’s simple: there are so many incredible founders building today, and often we don’t have the capacity to meet them—or even realize they reached out. In the age of AI, manually drafting memos like we did a few years ago is no longer sustainable if we want to stay ahead of the game and focus our time on founders, not mundane research or document creation.

After testing over 40 tools, I’ve also realized that the big-name platforms—typically built for broad industry use—aren’t necessarily the best fit for investor workflows.

Venture capital is, at its core, a signal-processing business. We’re flooded with data in all formats every day—yet success still hinges on spotting patterns early, asking sharper questions, moving faster than the rest, and backing the extraordinary people who are destined to make it🤔

That’s where AI makes the leap from “nice-to-have” to “must-have.”
It doesn’t replace judgment — it frees our time so we can apply it where it matters most.

Here are five AI tools I’ve selected from the dozens I’ve tested—ones I use almost daily to screen smarter, think deeper, and operate at scale.

Kruncher — My AI Co-Pilot for Screening, Memos, Portco & LP Ops 🚀

If I had to choose just one tool from my stack —it would be  Kruncher 💪

It’s the most comprehensive, purpose-built for VC workflows and handles everything (except sourcing) from screening my inbox and reviewing pitch decks to identifying those that meet my investment criteria, breaking down each section, enriching with public data, generating deep analysis, drafting memos, managing stakeholder communication, sending automated emails and reminders, and providing signals to monitor companies. Think of it as a full-stack AI analyst for the private markets.

🔍 What I use it for:
 ➡️ Auto-screening new inbound emails in my Gmail based on my specific investment criteria so I don’t spend time on companies that are great but beyond my investment focus / Discipline and Efficiency.
 ➡️ Drafting memos from decks, notes, emails, recordings and public research / Speed and Deep Insight.
 ➡️ Managing portfolio KPIs, signaling changes (employee count, new partnerships, public announcement etc.), requesting quarterly updates.
➡️ Generating LP updates that I can review and update accordingly with some additional thoughts. 
➡️ Watchlist Automation — Kruncher tracks up to 90 company metrics, analyzing changes like pivots, CEO exits, investments, and growth signals. It monitors companies monthly or quarterly, alerting you to key events so you can spot fast-growing startups early and understand their evolution over time and finally reconnect with the companies that were put on hold to be tracked but you never remember to check up with them.
➡️ Chat-style search across all my internal docs, notes, and communications. I can ask: ‘what humanoids companies I met recently’ and I have a list of all of them at my fingertips without going through folders or even airtable database.

✅ What stands out:
 ➡️ Deep VC focus: Not generic AI — it’s trained for private market workflows
 ➡️ Actual time saved: I cut memo drafting and early triage by 70–80%
 ➡️ Secure and scalable: Built for sensitive workflows, with strong compliance
 ➡️ Signal alerts: Notifies you of activity or traction shifts across portcos

⚠️ What to know:
 ➡️ Still a young company — some integrations are being built out
 ➡️ Best suited for early-stage to growth VCs managing large volumes of data or founder touchpoints

TL;DR: Kruncher is the backbone of my workflow. It thinks like an analyst, works like a partner, and scales with me as I grow omy portfolio.

Manus — Deep Financial Analysis at Lightning Speed 📊

When I’m deep into a deal and want to understand comps or model out assumptions, Manus is absolutely outstanding. It’s an autonomous AI agent for multi-step financial research and modeling.

📈 What I use it for:
 ➡️ Finding relevant public comps across markets and metrics
 ➡️ Running EV/Revenue and multiple analyses
 ➡️ Building quick dashboards for internal reviews
 ➡️ Stress-testing assumptions with simulations and running different scenarios for revenue growth as well as exit outcomes

✅ What’s great:
 ➡️ More powerful than GPT for deep financial work and all ‘excel’ type of tasks
 ➡️ Runs multi-step instructions with very little hand-holding
 ➡️ Keeps analysis structured and repeatable

⚠️ What to watch:
 ➡️ Still in limited rollout — access is gated
 ➡️ Some tasks (e.g., messy startup data) still require human review

Manus is like having an investment banking analyst you don’t need to train.

NotebookLLM — The Document Interrogator 📂

NotebookLLM is your secret weapon for turning documents into dialogue.
Upload 100+ files — decks, emails, legal docs (yes all of them!), diligence notes — and ask nuanced questions to surface inconsistencies or generate new angles.

🧠 How I use it:
 ➡️ Prepping questions for founder calls
 ➡️ Spotting inconsistencies in financial projections or timelines
 ➡️ Summarizing dense data rooms
 ➡️ Extracting red flags from legal or technical files

✅ Strengths:
 ➡️ Handles big batches of documents without breaking
 ➡️ Great for second-order questions you wouldn’t think to ask manually

⚠️ Limitations:
 ➡️ Works best on clean, legible files (OCR needed otherwise)
 ➡️ Doesn’t replace legal or expert review, but a powerful filter
➡️ Does not process excels. Need to do screen shot and upload let’s say pdf which is no go to do for all excel tabs.

NotebookLLM gives you x-ray vision across the documents and surface conclusions, dependencies you are not able to comprehend on your own with huge volume of data and docs.

Perplexity — Real-Time Competitive Landscape Scouting 🕵️‍♀️

Before a first call — or after a funding announcement — I’ll often fire up Perplexity to get a clean picture of a startup’s competitors, adjacent players, and market trends.

🌐 My use cases:
 ➡️ Mapping out adjacent players fast
 ➡️ Understanding tailwinds or headwinds in a space
 ➡️ Grabbing a quick read on technologies

✅ What’s useful:
 ➡️ Structured search with links to verified sources
 ➡️ Faster than manual googling
 ➡️ Great for market overviews 

⚠️ What to know:
 ➡️ Quality varies on less-covered topics or private startups
 ➡️ Can hallucinate or over-simplify nuanced market segments

Perplexity is the fastest way to map the playing field — without 20 open tabs.

ChatGPT — My Creative & Strategic Partner 🧠

Still one of the most versatile tool in the stack (or it’s just my anchoring bias?!). From emails and intros to narrative crafting and investment themes, ChatGPT is like my brainstorming whiteboard — available 24/7.

✍️ What I use it for:
 ➡️ Brainstorming new investment theses
 ➡️ Testing different positioning angles
 ➡️ Summarizing interviews, notes, or founder convos

✅ Strengths:
➡️ Fast and flexible for any type of writing
➡️ Useful for simplifying ideas
➡️ Accessible and easy to prompt
➡️ Learns my style and remember preferences

⚠️ Limitations:
 ➡️ Doesn’t know your deal context (unless you integrate deeply)
 ➡️ Requires judgment — can produce overly generic results
➡️ It’s not your CRM, does not integrate with your tools, cannot support along the whole workflow but do just separate pieces of the work

ChatGPT helps me refine the why and how of every investment decision.

⸻

🧩 Final Thoughts: My AI VC Stack

These tools don’t operate in silos — they form a full-stack operating system for modern VC with Kruncher as the main one and supplemented by Manus, NotebookLLM, PErplexity, ChatGPT if needed.

Lesson learned: if we invest in AI, it’s both our obligation and our right to leverage the very innovations we’re backing. We’re meant to be—or have already become—AI-augmented investors.

I love geeking on the AI most creative use cases. Let me know if you’re using any of these — or if you’ve found something that’s leveled up your workflow. Always curious to learn how others are evolving their stack.

#VC #AItools #Dealflow #Kruncher #StartupInvesting #ProductivityStack #MemoGeneration #AIforInvestors