Map markets, score targets, and leverage your entire deal history.
QX runs origination and research, consistently across every company and every document, with citations behind every answer. All directly from Slack or Teams, so that investors can focus on decisions.
5.0 on G2
Enhance your deal pipeline with AI teammates
Turn broker reports into ranked deal digests
A broker report lands in your inbox. QX pulls out the companies, researches each one, scores it against your thesis and sends the team only the names worth their time.
New broker report arrives
Outlook mail trigger
Extract companies from report
AI data extractor
Enrich and score candidates
QX company data + score
Send ranked deal digest
Delivered by email
Map a market in minutes
Type in what you're looking for or import data from your tools. QX populates a Grid enriched with headcount, funding, product focus and any other features you choose, with sources in every cell.
Run prospects through the same diligence questions and criteria
Give it the competitors and the questions you always ask. It answers each one for every company, with the source in the cell, so you compare like with like.
A sourced brief on any company, on request
Name the company. QX reads the web, filings, news and your own deal notes, then lands the brief in your inbox before the intro call, every claim linked.
Helix Bio · sourced brief ahead of Thursday's intro
to Dana
Helix Bio builds genomics data infrastructure in Cambridge. Here's what matters before Thursday's intro.
They're at $8.4m ARR with 62 staff, and closed a Series A in October 2024.
A new CFO started in January, hired from Recursion. Worth asking why.
Read the customer list carefully: two of the three named customers are still pilots.
I've attached the brief, with a source behind every line. We looked at them in 2023 and passed on price; that note is on page 4.
Query the data room with citations
Point QX at the data room and your past diligence. Ask the buyer's question list in plain English and every answer points back to the page it came from.
✅ 37 of 41 questions answered from the data room, each with its source page. Three are worth a closer look.
Revenue is concentrated: the top three customers are 41% of revenue (accounts, page 12).
Churn over the last twelve months is 6.2% by logo, 3.1% net (KPI pack, page 4).
The legal folder holds one unresolved claim.
⚠️ Four questions have no supporting document. They're flagged for the deal team rather than answered.
falcon-diligence-answers.xlsx
Question, answer and source page for all 41 rows
Tracked targets, watched while you work the fund
The long-list from last cycle doesn't go stale. On a schedule you set, QX re-checks every tracked company for leadership changes, funding, filings and news, and emails you only the ones that moved.
Tracked targets · 3 changes this week
to Tom
Three of the 84 tracked companies moved this week.
📢 Arden Systems raised a Series B, their first round since you passed in 2024.
👔 Fenwick Data's founder moved to chairman; a hired CEO starts in March.
📈 Marlow Group filed annual accounts: revenue up 23% on last year.
QX learns your investment preferences, then runs across your pipeline.
The same criteria on every target, the same checklist on every data room, and a source behind every claim.
Connect apps
Search 1,000+ apps- Connected
Outlook
deals@ inbox
- Connected
SharePoint
Project Falcon data room
- Connected
Salesforce
Fund IV pipeline
- Connected
Excel
Screening models
ConnectPitchBook
- Connected
Google Drive
Research library
1Connect your sources
Pick sources for your internal knowledge, email, CRM, and data providers — including Outlook, Gmail, Drive, SharePoint, Salesforce, and many more.
- Dana09:18Look at our past IMs to build a detailed rubric for scoring new companies. Make sure to include: $5–30m revenue, >20% growth, founder-owned, UK or DACH, B2B software. When we score new leads we should give clear rationale.DQXAgent09:18
✅ Criteria saved to memory. Here is how I'll judge every target.
Every target gets a score out of 10 with a one-line reason, I flag edge cases for a human look, and every cell shows its sources.
Want me to prepare a document outlining the full rubric for you to review?
SourcesSharePoint, Google Drive2Write your criteria once
Revenue scale, growth, margin, market structure, mandate fit. The way you would brief a new analyst. It remembers that for every new target.
- Dana09:31Can you score all companies attending the biotech conference next week. Also check our CRM and past IMs to see who we've spoken to before and who we already have data on.DQXAgent09:31
I've scored 10/412 companies and saved them to a Grid so that you can first review the results.
Three scored 8 or above, led by Helix Bio with 9/10. I've relied on web search, PitchBook, our internal data and CRM.
Say the word and I'll run scoring on the rest.
GRIDbiocon-2026-attendees
Score, rationale and sources for the first 10 rows
SourcesPitchBook, DealCloud, SharePoint
3Check the sources, then scale
Run ten rows, open the sources, tighten the criteria if needed, then run the market. Every cell points back to where it came from.
Your deal stack
Inbox, CRM, data providers and internal knowledge. QX reads and works inside the tools you already use.
QX operates inside your existing stack. No new tools to learn, no lengthy onboarding. Run it from Slack, Teams, WhatsApp or email.
QX takes out hours of crunching and admin every week so that you can build conviction.
Days of collection become an afternoon of review, screened consistently and cited to the page.
Associates with spreadsheets spend days of copy-paste building a market map, and each analyst screens slightly differently.
Every company researched the same way, every target scored on the same criteria, with the reasoning in the cell.
ChatGPT helps with a one-off summary, but can't see the data room, the pipeline or your past deals.
Answers come from your own documents with citations to the page: your IC notes, not a generic model.
Data providers alone give you excellent data, while the screening, thesis fit and first draft still happen by hand.
QX starts from the provider's pull, runs the screening and writes the rationale on top.
Point tools per task split sourcing, diligence and monitoring three ways, and context doesn't travel between them.
Sourcing, screening and the data room run on the same connections and the same knowledge.
Building it in-house costs months of engineering, then maintenance, for something that changes with every thesis.
The deal team configures it in plain English, changes it in minutes, and every run stays traceable.
Built for investment teams
Confidentiality first, a citation on every claim, and an audit trail on every run.
- We never train on your deal data
- QX does not train models on your data. Encryption in transit and at rest, role-based access by fund or deal, audit logs, and an isolated tenant on Enterprise.
- Cited, or flagged as missing
- Vault answers point to the document and page. When nothing supports an answer, it says so rather than filling the gap.
- Consistent by construction
- The same criteria run on every row and the same checklist on every data room, so screens and diligence are comparable across the portfolio.
- Any model, your keys
- OpenAI, Anthropic or Google per task, including your own API keys, so model choice follows your compliance posture rather than ours.
Questions investment teams ask before using QX
Screen your next market today.
Free to start. See your deal pipeline grow within days.