We're not a black box
If we can't explain it, we don't ship it. Transparency at every step of the decision.
Decision Intelligence System · Private Markets
When the data whispers Xylence listens.
The Right capital. The Right Startup.
The Decision Intelligence System for private markets. Not a CRM, not a database, not an LLM wrapper: it embraces the tools VCs already use and replaces the logic behind their decisions — with the GP at the center.
Founders seeking capital.
Investors seeking signal.
The noise is the same problem.
What looks like noise
holds the answer.
Finding your signal
in a world of noise
01 About
The Decision Intelligence System for investors and founders.
An intelligence-first science company, wrapped in software. We don't compete with the tools VCs already use — we compete with how decisions are made. We absorb the chaos, structure it, make opportunities comparable, place every startup in context, and learn from every decision.
We don't decide for the GP
We rank, structure, explain, and score. We give humans superpowers — we don't replace their judgment.
No prediction without ground truth
Where the data is weak, we say so. We don't fix bad infrastructure: we fill in the gaps.
80,726
Startups in the intelligence graph
5,051
Enriched end to end, source by source
30+
Sources to reconstruct the truth
02 Video
Xylence in 90 seconds.
When data whispers, Xylence listens.
03 MOAT
The moat is what we've built, not the model.
What takes a well-funded team 12+ months to replicate — because they'd have to redesign the system from the data model up. Adding modules to a CRM doesn't get you here. And in LATAM, the data simply doesn't exist anywhere else: we're not building a moat against time, we're building one against access.
A temporal database
Event-driven from day one. The reconstruction of any startup at any past moment — not a snapshot of today.
A relational ecosystem
Founders, investors, markets, and events connected — a network that evolves with every ingest.
A formalized evaluation layer
The GP's judgment externalized into auditable facets. We structure how it's evaluated, not just what you see.
A consumption interface (Sound / Echo)
The surface that closes the loop between investors and founders — where intelligence is consumed and composed.
04 Pricing
Firm pricing. No surprises.
We sell access to world-class intelligence. Pick your side of the ecosystem.
Individual
$6,000/yr
Active angels · single-LP · family office principals
- 1 seat
- 25 deep dives/mo
- Full scoring
- Basic VC intelligence
Scout
$24,000/yr
Emerging managers · micro-funds <$50M AUM · solo-GPs
- 3 seats
- 50 deep dives/mo
- Basic integrations
- 36h SLA support
Core
$48,000/yr
Funds $50M–$300M AUM · our sweet spot
- 8 seats · unlimited deep dives
- 20 AI interviews/mo
- Basic Firm Memory + Trust Layer
- All integrations · CS manager
Platform
from $120,000/yr
Funds $300M–$1.5B · multi-fund · PE in venture
- 20 seats · API access
- Full Firm Memory
- Portfolio Operating Intelligence
- Advanced Trust Layer
Enterprise
from $250,000/yr
Funds >$1.5B · multi-strategy institutions · banks
- White-label · single-tenant
- SOC 2 Type II · ISO 27001
- Dedicated Outcome Engine
- Custom Models (post-Series A)
Free
$0
Top-of-funnel engine for founders
- 1 analysis/mo
- Basic scoring
- 10 comparables in your industry
- 20 VCs read-only
Pro
$49/mo
or $470/yr (−20%)
Founder actively fundraising (or in the next 6 months)
- Unlimited pitch analyses
- Multi-dimensional scoring + tone intelligence
- 3 pitch practice sessions/mo
- Personalized VC intelligence (top 50)
Elite
$149/mo
or $1,430/yr (−20%)
Serial founder · Xylence as a continuous business cockpit
- Everything in Pro + unlimited pitch practice
- Full VC intelligence (141+ funds)
- AI coaching + Echo Data Room
- Continuous platform features
Annual contracts for Sound · Echo monthly or annual (−20%). List prices; discounts only within program rules.
05 Why now
Venture is illegible. The window is open — briefly.
Every decision speaks a different language, and none of them leaves a memory behind. Information explodes; verification doesn't. Capital is moving toward AI with the same human attention as always, and most funds now run something they call data — few can say where any single number came from. In LATAM the asymmetry is sharper still: more opportunity, less data, worse infrastructure.
80,726
companies in the graph — and every fact in it names its source
30+
sources reconciled into one timeline per company
0
facts stored without provenance — the schema will not accept one
6
visibility levels keeping each fund's data its own
The tools are everywhere. The decision system underneath is missing.
06 Approach
Three pillars no one had stitched together.
A single system for understanding startups across time, judgment, and context. Legacy tools sell what happened; we sell what it means, in context and over time.
Temporal reconstruction
What did this startup look like in 2019? Not today's snapshot.
Why it's hard
Event-driven from day one — not a database of snapshots.
Formalized criteria
The GP's judgment, made explicit. Evaluation broken down into auditable facets.
Why it's hard
We model judgment — not just companies.
Relational ecosystem
Every founder, investor, market, and event — connected and evolving.
Why it's hard
Ingest, structure, and infer as a single system.
07 Product
Three modules, one engine.
Pulse · Echo · Sound on top of a single data engine, one feature store, and one explainable scoring layer — that learns from every decision, interaction, and outcome.
Onboarding
Pulse
The onboarding layer, from T₀.
- VC and founder intake
- Data from origin (T₀)
- Structured, not scraped
Echo
Founder intelligence that closes the loop.
- Benchmarks and signals
- Gaps and ecosystem position
- Data flows back, structured
Sound
The VC's cockpit.
- Ranked dealflow
- Decomposed, explainable reasoning
- Portfolio-level intelligence
08 Team
The quiet minds behind Xylence.
Led by conviction. Built by data.
Isaac Kohab
Founder & CEO
1 exit (2023) · Harvard & TED speaker · G20 (FSB) · 2× YC invitee
Marcelo Ergas
Co-Founder & Chief Business Intelligence Officer
Business intelligence & data science · +30 years in banking · ex-Banamex
Antonio Guzmán
Chief Technology Officer
Platform architecture · AI-enabled workflows · product engineering
Alejandra Maytorena
Chief Data Officer
Pattern detection, decision intelligence, and ML systems
Eduardo Guzmán
Infrastructure & Security
Full-stack & DevOps · cloud, CI/CD, high availability · ex-Kavak
Moises Cohen
Legal & Operations
Private equity, capital markets · Associate @Creel · lawyer @UP
Galia Puszkar
Revenue & Growth (CRO)
Partnerships, ecosystem expansion, and GTM · Director @EO Latam
David Cuellar
AI Engineering
Inference pipelines, frontier and local models, agent systems
Jovani Gonzalez
Platform & Security Engineering
Full-stack engineering, security, and the move to microservices
Luis Virues
Data Science & Modeling
Projections, scores, and causality analysis behind the decision factors
Melissa Ríos
Intelligence Operations
Startup discovery, validation, and data quality across the Xylence intelligence graph
12
Months building
11
People on the team
1,600+
Custom API endpoints
~20x
Velocity with AI
Be part of this quiet revolution.
We're embedding Xylence into the real processes of a select group of top-tier funds as design partners. If you run a fund, let's talk.
Request access