Claw Empire installs a private AI assistant for venture capital on customer-controlled infrastructure. It cuts deal flow noise with thesis-aware screening, drafts diligence summaries that know what you have backed before, and protects sensitive data with approval gates and NDA-compliant workflows that never train public models.
The useful install is narrow, explicit, and tied to work you already repeat. Claw Empire maps the lane, connects approved systems, and keeps sensitive actions gated.
I am on a hamster wheel that can only spin faster and faster and never stops, as one VC put it on r/venturecapital. Investing in new companies has lost its luster because the volume of inbound pitches is overwhelming and there is no time to think.
Pasting a deck into ChatGPT and asking if it is a good investment is a Magic 8-Ball with a subscription fee. AI does not know your thesis, does not know what you have backed before, and does not know what patterns you have seen work.
An AI tool needs everything: inbox, CRM, portfolio data, LP data. So there is a sensitive data breach issue. NDAs get violated the moment a deck or data room hits a consumer-grade AI tool with no governance.
Less than 14% of active VC firms globally have integrated AI tools beyond basic CRM enrichment. The funds that move first will compound their advantage through the next cycle while the rest catch up.
A private assistant should produce a reviewable queue, not mystery automation. Every output should make approval faster and safer.
The assistant screens inbound against your specific thesis, portfolio history, and pattern recognition, not generic ChatGPT logic. Deals that fit your thesis surface to the top and the rest get structured triage instead of a glance.
The assistant drafts diligence summaries that reference what you have backed before, what patterns worked, and where this deal fits or breaks your thesis. Every claim traces to a source in the deck, data room, or public filing.
The assistant runs on customer-controlled infrastructure. Decks, data rooms, LP data, and portfolio information never leave your environment and never train public models. Every action is logged and approval-gated.
This is the level of specificity we want before a workflow touches production tools.
WORKFLOW: venture_capital_deal_flow_and_diligence
TRIGGER: new inbound deck OR sourcing cycle OR IC prep request
READ: inbound decks, CRM context, portfolio data, LP reports, market signals
DO:
1. screen inbound against firm thesis, portfolio history, and pattern fit
2. draft diligence summary with references to prior investments and thesis
3. prepare IC memo section with source citations from deck and data room
4. flag NDA-sensitive items and data breach risks for partner review
APPROVAL GATES:
- never send outreach or founder-facing messages without partner approval
- never update pipeline or CRM records without approval
- never share diligence or portfolio data externally without review
STOP CONDITIONS:
- legal terms, NDA violation risk, valuation dispute, unclear owner
RECEIPT:
- write source evidence, proposed action, partner reviewer, unresolved questionsThe point is not to remove judgment. It is to reserve judgment for the decisions that matter.
The assistant drafts outreach and follow-ups but waits for partner approval before anything reaches a founder.
Deal stage, owner, and task updates are proposed with evidence before a human approves writes.
Decks, data rooms, and portfolio information route to partner review by default and never leave your infrastructure without approval.
The exact implementation depends on tool access and data quality. The operating model stays simple: map, install, dry run, hand off.
Define firm thesis, deal sources, screening rules, IC cadence, and stop conditions.
Connect approved CRM, inbound decks, portfolio data, and LP context to the private assistant on your infrastructure.
Review proposed deal screens and diligence summaries until the workflow matches your investment motion.
Receive the operating runbook, approval receipts, and expansion notes for the next deal cycle.
Plain answers for the trust, security, and implementation questions buyers ask before connecting AI to real workflows.
A Claw Empire venture capital AI assistant is a private workflow on customer-controlled infrastructure that screens deal flow against your thesis, drafts diligence summaries that know your portfolio, and protects sensitive data with approval gates and NDA-compliant workflows.
Generic AI does not know your thesis, does not know what you have backed before, and does not know what patterns you have seen work. The assistant screens against your specific portfolio history and thesis, and every output traces to a source in the deck or data room.
The assistant runs on customer-controlled infrastructure. Decks, data rooms, LP data, and portfolio information never leave your environment and never train public models. Every action is logged and approval-gated, so NDAs are not violated by consumer-grade AI tools.
The assistant works inside your existing CRM (Affinity, Attio), meeting tools (Granola), and data sources (PitchBook, Harmonic, Standard Metrics). It is not another login; it reads from where your data already lives and writes back only on approval.
Pricing is scoped on a discovery call because deal volume, thesis complexity, CRM systems, and data sources vary. The public page does not publish a flat price because installs differ by fund size and workflow depth.
Send the workflow you want off your desk. We will confirm the tools, approval gates, stop conditions, and safest week-one install path.