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Vision

Cernio is an AI-powered B2B buyer discovery and intelligence platform designed to help companies systematically find the right buyers, identify decision makers, and manage sales opportunities across global markets. The system aims to eliminate the fragmented workflows B2B sales teams currently use:
  • Google search
  • trade directories
  • LinkedIn browsing
  • trade fair notes
  • spreadsheets
  • CRM tools not designed for buyer discovery
Instead of using many disconnected tools, sales teams should be able to answer two fundamental questions inside a single system: Where should I sell this product? Who should I sell it to? The primary audience is exporters and international sales teams — companies selling products across borders. However, the platform is designed to serve any B2B company that needs to find buyers in new markets, whether international or domestic. The long-term ambition of Cernio is therefore not simply to be a lead generation tool, but to evolve into a:

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B2B Buyer Intelligence Platform

A system that helps companies with:
  • buyer discovery (find companies that need your product)
  • contact intelligence (find the right person to talk to)
  • lead workflow (track and manage opportunities)
  • trade fair capture (digitize business card workflows)
  • market intelligence (where should you expand?)
  • competitive landscape (who else is selling there?)

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Why This Product Exists Now

Several structural changes make this product possible today.

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1. Public business data is widely available

Information about companies exists across:
  • company websites
  • trade directories (Kompass, Europages, ThomasNet)
  • LinkedIn and professional networks
  • industry portals and association lists
  • government import/export databases
  • B2B marketplaces (Alibaba, Amazon Business)
However, this data is fragmented, unstructured, and spread across dozens of sources.

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2. AI can structure messy web data

Modern LLM systems can:
  • interpret company descriptions in any language
  • classify industries and business roles
  • infer company type (distributor, reseller, end-user, manufacturer)
  • extract decision maker names and contact details
  • rank relevance and buyer fit
This allows the creation of structured buyer hypotheses from unstructured web data — something impossible just 2 years ago.

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3. B2B sales teams still operate with fragmented workflows

Most B2B companies — especially SMEs — still rely on:
  • Excel spreadsheets
  • Google searches
  • email outreach
  • trade fair networking
Enterprise tools like Salesforce, HubSpot, and ZoomInfo exist but are:
  • too expensive for SMEs ($14,995+/year for ZoomInfo)
  • designed for SaaS/tech sales, not industrial B2B
  • poor at covering international markets and industrial sectors
  • not built for buyer discovery (they assume leads already exist)
There is therefore a gap: AI-native buyer discovery tools for B2B companies selling across markets.

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4. Global trade is massive and growing

  • Global merchandise trade: $34.65 trillion (2025, WTO)
  • B2B e-commerce: $36 trillion (2026, Mordor Intelligence)
  • Cross-border B2B growing at 13.8% CAGR
  • US alone has 270,001 exporting companies (2024, Census Bureau)
  • EU has 750,000+ companies exporting outside the EU
  • Turkey has 180,396 registered exporters
Yet there is no AI-native platform helping these millions of companies find the right buyers.

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Target Market

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Primary Segment: Exporters and International Sales Teams

The primary audience is companies that sell products across borders — exporters, international sales teams, and trade-focused businesses. Typical characteristics:
attributevalue
company size5-200 employees
business modelB2B (selling to other businesses)
sales modeloutbound (actively seeking buyers)
internal research capacitylow to medium
current toolsExcel, Google, email, trade fairs
These companies typically do not have:
  • dedicated research or RevOps teams
  • enterprise sales intelligence tools
  • automated lead discovery workflows
Yet they constantly need to find new buyers in new markets.

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Expansion Segments (Future)

The platform’s capabilities are not limited to exporters. Future segments include:
segmentuse case
Domestic B2B sales teamsFinding buyers within their own country
Procurement teamsFinding suppliers and partners
Trade agenciesMatchmaking between exporters and importers
Industry associationsMember services — buyer discovery as a benefit
The underlying engine — “product + market → ranked companies + decision makers” — is universal for any B2B discovery need.

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Ideal Customer Profile (ICP)

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Primary ICP: Export-Focused Roles

Typical users of the platform include:

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Founder / Owner

Responsibilities:
  • strategic market expansion
  • trade fair participation
  • key account relationships
Pain points:
  • limited time for research
  • fragmented information sources

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Export / International Sales Manager

Responsibilities:
  • finding potential buyers in target markets
  • sending catalogs and proposals
  • managing follow-ups across time zones
Pain points:
  • repetitive manual research (3-4 hours per market)
  • scattered data across tools and spreadsheets

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Business Development Manager

Responsibilities:
  • lead qualification and pipeline management
  • partner and distributor relationships
  • market entry strategy
Pain points:
  • poor lead memory across markets
  • unclear prioritization (which companies to approach first?)

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Secondary ICP: B2B Sales Teams (Future)

roleuse case
Sales Manager (domestic B2B)Finding new accounts in local market
Procurement ManagerSourcing suppliers for specific products
Market ResearcherMapping competitive landscape in a sector

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B2B Sales Workflow Today (Current State)

The typical workflow for a B2B company looking for new buyers:
  1. Google search for potential companies in a target market
  2. Browse trade directories (Kompass, Europages, Alibaba)
  3. Check company websites for relevance
  4. Look up people on LinkedIn
  5. Save prospects in Excel or CRM
  6. Send cold emails or LinkedIn messages
  7. Visit trade fairs and collect business cards
  8. Follow up manually (often forgotten)
Problems:
  • Research takes 3-4 hours per market-product combination
  • Results are inconsistent and incomplete
  • No ranking or scoring — all leads look equal
  • Follow-ups are often forgotten after trade fairs
  • Information is scattered across 5+ tools

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Core Product Promise

The platform should deliver one clear value moment: These are the 5 companies most likely to buy your product. This moment must occur within the first session — ideally within 30 seconds of entering a search. Everything else in the product builds on this initial value. The promise is universal: whether you’re a Turkish chemical exporter looking for distributors in Germany, or a US machinery manufacturer looking for resellers in India — the same engine delivers the same value.

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Product Wedge Strategy

The product should not launch as a full B2B intelligence platform. Instead, it should begin with a narrow but powerful wedge.

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Wedge Product

AI Buyer Discovery Enter your product + target market → get AI-ranked companies with confidence scores. This solves the biggest immediate problem: Finding relevant buyers without hours of manual research.

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Retention Layer

After discovery, the platform adds features that keep users coming back:
  • saved leads with status tracking
  • decision maker discovery (headhunt)
  • notes and follow-up reminders
  • interaction history

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Intelligence Layer

As usage grows, the platform adds market-level intelligence:
  • market selection recommendations
  • competitive landscape analysis
  • industry trend insights

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B2B Buyer Intelligence Platform

Finally the platform becomes a system of record for B2B buyer relationships and market decisions. 
Wedge:          Product + Market → Ranked Buyers (30 seconds)
Retention:      Save → Track → Follow-up → Close
Intelligence:   Which markets? Which segments? What's changing?
Platform:       System of record for all buyer relationships

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Core Product Modules

The first version of the platform includes four main modules.

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1. AI Buyer Discovery

This is the core acquisition feature. Input:
  • Product or service description
  • Target country or region
Examples:
  • “textile stain remover spray” + “Germany”
  • “CNC milling machines” + “United States”
  • “organic food ingredients” + “Japan”
The system returns: Top 25 companies — ranked by AI-calculated FitScore And highlights: Top 5 most likely buyers — with confidence indicators Company types found: distributors, resellers, end-users, manufacturers — all scored and classified.

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2. Decision Maker Finder

Once a company is discovered, the system identifies relevant contacts. Target roles include:
  • purchasing manager / procurement director
  • import manager / sourcing manager
  • owner / CEO / founder
  • business development / sales director
Output example:
nametitleemaillinkedin
Anna MüllerPurchasing Manageranna@company.delinkedin.com/in/anna
Thomas WeberCEOthomas@company.delinkedin.com/in/thomas

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3. Lead Workspace (Light CRM)

Users can store discovered companies as leads and manage the sales pipeline. Fields:
  • company
  • contact(s)
  • notes
  • follow_up_date
  • status
  • priority
Lead statuses:
  • Saved
  • Contacted
  • Waiting Reply
  • Negotiation
  • Customer
  • Lost

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4. Trade Show Lead Manager

Trade fairs remain a major channel for B2B companies, especially exporters. The mobile companion (future) enables: 
Scan business card
       ↓
AI extract data
       ↓
  Create lead
       ↓
Link to company
Extracted fields:
  • name, company, email, phone, website
Users can add meeting notes such as:
  • “met at Chemspec Europe booth 412”
  • “interested in exclusive distribution for Benelux”
  • “price sensitive, prefers EUR terms”

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Product Workflow

The typical user flow: 
      Signup (free)
          ↓
  Enter product + target market
          ↓
     AI discovery
          ↓
  Review ranked companies
          ↓
  Find decision makers
          ↓
      Save as lead
          ↓
      Add notes
          ↓
  Set follow-up reminder
          ↓
  Track → Close → Repeat
This simple workflow forms the core of the platform. It works for any product, any market, any industry.

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The “WOW Moment”

The product’s defining moment should be: These 5 companies are most likely to buy your product. This is achieved through:
  • AI-powered web research and company analysis
  • FitScore ranking algorithm
  • Company type classification (distributor, reseller, end-user, manufacturer)
  • Confidence scoring
The WOW moment works because:
  1. It’s specific — real company names, not generic advice
  2. It’s fast — results in under 30 seconds
  3. It’s relevant — AI understands the product-market fit
  4. It’s actionable — users can immediately find contacts and reach out