Pith turns the market maps, founder updates, and sector reads you bookmark into a cited wiki you can query before any partner meeting. Built for investors who read constantly and need to remember all of it.
As a VC you read across dozens of deals, theses, and portfolio companies at once: market maps, founder updates, competitor launches, analyst notes, expert calls. Most of it evaporates — the killer data point you saw three weeks ago is now somewhere in a tab, a Slack thread, or your head. Pith makes that reading a first-class knowledge layer. You bookmark what you read, and it auto-builds a cited wiki per company, per sector, and per thesis — every claim links back to the source, so conviction is traceable rather than vibes. It auto-tags each bookmark to the right deal or portfolio company, briefs you in audio or text before a meeting, and is queryable from Claude or ChatGPT via MCP. Knowledge spaces are shared per deal and per portfolio, so the partnership builds durable, citable conviction together instead of in scattered private notes.
What changes for you
Scenario 1
Diligence prep without re-reading the internet
You take a first meeting next week with a Series A infra startup. Over the past month you bookmarked the founder's old blog posts, two competitor launches, a teardown of the category, and an expert call transcript. Pith has already auto-tagged all of it to the deal and built a cited wiki page: market size, the three real competitors, the open technical risk, who else is funding the space. You read the briefing on the way in — every claim links to where it came from, so when the founder pushes back you know exactly which source said what.
Scenario 2
A thesis that compounds instead of resetting
You've been building a thesis on European defense-tech for eight months. Every report, regulatory change, and funding round you bookmark flows into one cited thesis wiki that grows sharper over time — not a doc you rewrite from scratch each quarter. When a new deal lands in the space, your accumulated reading is already structured and sourced, so you can judge it against a living view of the market rather than starting cold.
Scenario 3
Monday partner meeting, briefed in five minutes
Before the partner meeting you ask Pith for a briefing on the two deals you're championing and any portfolio company with news this week. It pulls from the shared knowledge spaces — including reading your partners added — and gives you a tight, cited summary plus an audio version for the walk to the office. Portfolio monitoring stops being a quarterly scramble: the competitor raise or pricing change a partner bookmarked on Thursday is already in the company's wiki, with the link, when you open it Monday.
Founder's note
I'm a tech consultant, and I built Pith because I was drowning in things I'd read and half-remembered across too many clients. Investors have the same problem at ten times the scale — the conviction is buried in tabs and your memory. I wanted the reading to actually compound into something cited you can hand to a partner, not just disappear.
FAQ
Can I keep each deal and portfolio company separate?
Yes. Bookmarks are auto-tagged to the right company, sector, or thesis, and each gets its own cited wiki. You can scope a knowledge space to a single deal, a portfolio company, or a broad sector thesis, and a bookmark can live in more than one when it's relevant to several.
Can my partners and the rest of the firm share this?
Yes. Knowledge spaces are shareable across the partnership, so a deal or portfolio wiki reflects what the whole team has read, not just one person. Everyone queries the same cited source of truth, and you can keep a personal space for your own early reading before it's ready to share.
How is this different from Notion or Affinity?
Affinity is your CRM and relationship/deal-flow pipeline; Notion is a blank workspace you have to structure and fill by hand. Pith is the reading-and-conviction layer: you just bookmark, and it auto-builds the cited wiki and briefings for you. It complements a CRM rather than replacing it — Affinity tracks who you met and where the deal stands, Pith remembers what you've learned and why you believe it.
Where is our data stored, and is it used for training?
All data is stored in Frankfurt, Germany, under GDPR, and is never used to train models. For a fund handling confidential founder materials, deal data, and LP-sensitive theses, that residency and the no-training guarantee are the baseline, not a feature.
Does this work for a solo angel, or only for a full fund?
Both. A solo angel gets the cited per-deal wiki, auto-tagging, and pre-meeting briefings with no team to manage. A fund adds shared knowledge spaces across the partnership. You can start solo and add the team later without rebuilding anything — the same reading just becomes shared.
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Last reviewed: 6 June 2026