AI-assisted CRM intelligence
Extracts senders and recipients, identifies founders and checks whether contacts already exist.
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Case study · Venture Capital / Investment & Advisory
Turning deal-flow chaos into governed intelligence.
AI-assisted CRM intelligence and n8n workflows that process inbound founder and deal flow without duplicates, loops or uncontrolled AI actions.
- Client
- DQ Ventures
- Industry
- Venture Capital / Investment & Advisory
- Delivery
- AI-powered workflow and CRM automation
- Capability
- AI Agents & Automation
The challenge
What DQ Ventures was up against.
Data flowed in from email, CRM, founder outreach and deal pipelines, but the workflows were manual, spread across tools and hard to govern.
- Large volumes of inbound email and contacts
- Manual checks for existing CRM records
- Inconsistent enrichment
- Duplicate records and re-processing
The solution
What we built.
Skugal designed deterministic automation for critical logic and used AI only where interpretation was needed, with strict separation between decisions and execution.
De-duplication & processing control
State flags skip handled contacts and emails and prevent loops, so automation is idempotent.
Tool-based execution
AI suggests; approved tools act. No AI has uncontrolled access to business systems.
Timezone-aware scheduling
Predictable once-a-day processing windows across regions.
How it works
From input to outcome.
- Emails & CRM events
- Extraction & validation
- AI classification & enrichment
- Governed tool execution
- CRM update & state control
Business impact
What changed.
DQ Ventures runs a governance-first automation system that scales with deal flow without sacrificing control.
Technology
- n8n (self-hosted)
- LLM classification & enrichment
- Folk CRM
- MCP-style governance
- Timezone-aware scheduling
- Faster processing of inbound deal flow
- Less manual CRM work for investment teams
- No duplicate records
- Cleaner, enriched CRM data
- Secure, auditable AI usage
Automation works best when intelligence and control evolve together.
Next step
Have a similar challenge?
Tell us about the workflow or product. We’ll come back with an architecture, a delivery plan and where AI agents fit.