At Raylu, I’ve always felt that calling what we do “deal sourcing” massively undersells it.

Recently, I finally put the right name to it: Deal Engineering.

It captures what we’re really building: we’re not just finding companies faster - we’re designing, building, and optimizing entire deal flows end-to-end, so investors can go from idea to signed deal with a level of precision and leverage that simply didn’t exist before.

From Deal Sourcing to Deal Engineering

Traditional “deal sourcing” tools do one thing: they give you a list.
You still have to:

• Manually clean and filter targets
  
  

• Google every company to understand what they actually do
  
  

• Hunt for the right email
  
  

• Write outreach from scratch
  
  

• Update your CRM by hand
  
  

• Rebuild the same analysis for every IC process
  
  

We started Raylu because that workflow no longer made sense to us.

For us, Deal Engineering means that every step - from thesis, to market map, to outreach, to CRM, to IC materials - should be:

• Systematic (repeatable, not heroics)
  
  

• AI-native (agents doing the lifting, not analysts doing data entry)
  
  

• Firm-specific (encoding your judgment, not generic filters)

We’re not another sourcing widget bolted onto a stack. We’re building the AI platform for private-market investors that turns a team’s instincts into a durable, compounding system.

So What Is Deal Engineering?

Here’s how I define it:

Deal Engineering is the discipline of using AI agents, proprietary signals, and firm-specific models to design and operate the entire lifecycle of a deal - from first thesis to investment committee and beyond.

On Raylu, that shows up in four core motions:

1. Thesis → Market Map in <30 Minutes
   
   

2. 360° Target Intelligence on Every Company
   
   

3. Automated Direct-to-CEO Engagement
   
   

4. Pipeline, CRM, and IC Intelligence in One Loop

Each motion is powered by AI agents that don’t just fetch data - they continuously refine how each firm finds and evaluates opportunities.

1. Engineering the Front End: Thesis to Market Map

In a Deal Engineering world, you don’t start with a database search.
You start with a sentence:

“Find agentic SOC automation tools selling into mid-market enterprises.”

“Map bootstrapped vertical SaaS in European insurance distribution.”

“Show me add-on targets for our existing portfolio in healthcare IT.”

We built Raylu’s agents to turn prompts like that into a thesis-driven market map in under 30 minutes, scanning tens of thousands of sources (including long-tail, bootstrapped, and emerging companies traditional tools miss) and returning hundreds of relevant targets, not a sparse list of 30.

This phase is where Deal Engineering begins: you design the universe of opportunity with intention, instead of accepting whatever a database happens to surface.

2. Engineering Understanding: 360° Target Intelligence

Once the market is defined, Deal Engineering is about depth, not just breadth.

On Raylu, we auto-build 360° profiles on every target so teams don’t have to jump between 10 tabs to answer basic questions. That includes:

• Business teardown: products, pricing model, GTM motion, buyer personas, hiring velocity
  
  

• Market context: growth projections, regulatory landscape, customer sentiment
  
  

• Competitive position: head-to-head comparisons across features, traction, and financial strength

What used to take hours of scattered research can be scanned in minutes - and standardized across the whole team.

The effect I see with customers is simple: more qualified pipeline, not just more names.

3. Engineering Engagement: Direct-to-CEO at Scale

Deal Engineering doesn’t stop at “we like this company.” It has to build the bridge to a real conversation.

That’s why we built Raylu’s agents to:

• Find verified decision-maker emails (CEO, founders, key executives) with a very high hit rate
  
  

• Generate multi-touch campaigns that sound like your fund and reference real company specifics
  
  

• Optimize reply rates using real-time analytics across sequences
  
  

• Because outreach is powered by deep research, firms see significantly higher reply rates than with generic outbound.

This is what I mean by engineered dealflow: the right companies, with the right message, at the right time - without a team rewriting the same email 100 times.

4. Engineering the System: CRM, Pipeline, and IC

At most firms, data lives everywhere: CRM, email, shared drives, data rooms, analyst notes.

Deal Engineering treats all of that as a single, living system. With Raylu, we:

• Sync bi-directionally with DealCloud, Affinity, Salesforce, so market maps, companies, and activities flow into existing CRMs
  
  

• Enrich years of unstructured notes, emails, decks, and attachments to surface “hidden gold”
  
  

• Run win/loss and intelligent scoring based on what a firm has actually closed or passed on
  
  

• Help teams go from data room → IC memo with AI-driven synthesis of CIMs, models, QofE, and call notes into decision-ready materials in their own formats
  
  

Instead of every deal being a one-off project, we help firms operate a repeatable Deal Engineering engine where:

• Time from thesis → first meetings shrinks from weeks to hours
  
  

• Market-map turnaround time drops by over 90%
  
  

• Analyst time is reallocated from manual research to judgment, debate, and relationship-building
  
  

Encoding a Firm’s Edge: AI That Learns You

The best funds don’t win because they have more spreadsheets. They win because they see patterns others don’t.

Deal Engineering, the way we think about it at Raylu, is how you encode that edge into AI systems:

• Custom scoring models based on actual wins, passes, and portfolio outcomes
  
  

• Firm-specific signals - like “sells to PE-backed customers” or “usage-based pricing” - built into search and screenings
  
  

• Self-optimizing search, where every interaction helps agents sharpen what “good” looks like for that particular strategy

For me, this is bigger than automation. It’s about turning “gut feel + 10 open tabs” into a compounding, institutional capability that survives team changes, strategy shifts, and cycles.

Built for Every Investor, Not Just One Style

One reason “Deal Engineering” clicked so strongly for me is that it cuts across silos:

• Early-stage VC using Raylu to discover emerging categories and founders before they hit anyone’s CRM
  
  

• Growth equity scanning thousands of bootstrapped or lightly capitalized category leaders globally
  
  

• Private equity running add-on target searches, checking PE-backed vendor concentration, and preparing IC materials
  
  

• Corporate development and strategic investors mapping adjacencies, competitive moves, and partnership targets

Different mandates, same core motion: design, operate, and improve the deal machine, instead of just pushing it harder.

Secure, Compliant Deal Engineering

Re-architecting how a firm sources and evaluates deals only works if it’s done safely.

That’s why we built Raylu with:

• Zero AI data retention with our model providers
  
  

• SOC 2–grade infrastructure and controls
  
  

• SSO, MFA, and end-to-end encryption
  
  

• Fully cited, source-backed outputs so teams can trust and verify critical analysis

Deal Engineering isn’t meant to be a black box. It’s meant to be a transparent, auditable system that fits within the governance standards top funds require.

Where We Go From Here

“Deal Engineering” started as an internal phrase our Head of Growth & Strategy used to describe what customers were actually doing with Raylu.

It stuck because it’s accurate:

• We’re not just giving investors more data - we’re re-architecting how deals are found, qualified, and won.
  
  

• We’re not just speeding up tasks - we’re scaling judgment across an entire platform.
  
  

• We’re not just a sourcing tool - we’re building the Deal Engineering layer for private markets.
  
  

If you want to see what Deal Engineering looks like inside your workflows, I’m always happy to walk through it live. In a short pilot, we can stand up a zero-risk environment and let your team experience what it feels like when thesis, research, outreach, CRM, and IC all live inside one engineered system. Book a demo to learn more.

This is what we’re building at Raylu - and Deal Engineering is the best name I’ve seen for it.