How we discover and score organizations at scale
In Part 1 we walk through our current agentic research system: from discovery of organizations and products to LLM-as-judge scoring, URL validation, and asset enrichment. We share the pipeline, the agents, and where tokens go.
At Moncho we use multiple AI agents to discover, validate, and enrich market data. This post describes the workflow we run today, the one that powers organization discovery, scoring, and logo enrichment, and how it fits into the bigger picture of product and pricing discovery.
The high-level flow
Before we populate any data, we first define sectors, landscapes, and segments based on global market maps, value chains, and well-established segments and needs. This is often done manually, by reviewing industry reports, analyst blogs, marquee investor memos, and similar sources, so the taxonomy is stable and aligned with how markets are structured.
Our research pipeline then follows a clear sequence:
- Discovery of organizations: Search and LLM extraction find companies by sector, segment, and location.
- Score to select the top ones: A Judge Agent scores each org on six dimensions; we keep those above a confidence threshold.
- Verify URL: The validation tool (used by the Judge) runs a HEAD request and rule-based checks (defunct, duplicate, subdomain/country-path rules).
- Fetch logos: Approved orgs get logos via the Logo Agent and Logo.dev.
- Discovery of products & pricing: For selected orgs we discover products and pricing (Pricing Agent, search tools).
- Score to select top products: The Scoring Agent scores products on multiple dimensions using sector-specific rubrics.
- Verify URL / Fetch product images: Product URLs and images are handled by the Product Image Agent and related tools.
End-to-end pipeline (organizations and products)
Below is the full flow from search query to approved organizations with logos, and then to products and product images. Judge Agent and Scoring Agent are our LLM-as-judge steps; the rest use tools and external APIs.
flowchart TB
Q([Search query]) --> D[Discovery]
D --> J[Judge and validate]
J -->|Judge and validate top orgs| L[Logo enrichment]
L --> P[Product discovery]
P --> S[Score products]
S -->|Score by sector rubrics| I[Product images]
style J fill:#dbeafe,stroke:#0ea5e9
style S fill:#dbeafe,stroke:#0ea5e9
Blue = LLM as Judge
Agents and their tools
Each agent is wired to specific tools. Judge and Scoring are the two that act as LLM judges (multi-dimensional scoring); the others orchestrate search, validation, or asset APIs.
flowchart LR
subgraph A[Agents]
TAX[Taxonomy]
D[Discovery]
V[Validation]
J[Top Orgs Judge]
L[Logo]
P[Product discovery]
S[Product Scoring]
I[Product Image]
VER[Verification]
end
subgraph T[Tools and APIs]
T0[Taxonomy and sector definitions]
T1[Search: Exa, Tavily]
T2[Validation]
T3[Logo.dev + CDN]
T4[Product discovery: Exa]
T5[Sector Specific Rubrics]
T6[Physical Goods: Exa]
T7[Digital Goods: Logo.dev]
T8[Verify website, social]
end
TAX --> T0
D --> T1
V --> T2
J --> T2
L --> T3
P --> T4
S --> T5
I --> T6
I --> T7
VER --> T8
style J fill:#dbeafe,stroke:#0ea5e9
style S fill:#dbeafe,stroke:#0ea5e9
- Taxonomy- Defines sectors, landscapes, and segments (taxonomy and sector definitions).
- Search- Exa or Tavily for web search; internal tools and agents to search the taxonomy.
- Validation- Rule-based checks (e.g. URL, defunct, duplicate).
- Top Orgs Judge- LLM scoring on six dimensions; uses the validation tool.
- Logo- Logo.dev and CDN for fetching and serving logos.
- Product Scoring- Sector-specific rubrics only.
- Product Image- Physical goods: Exa. Digital goods: Logo.dev.
- Verification- Verify website and social activity for active/inactive checks.
Verification runs outside the main discovery pipeline; URL checks in the org flow are done via the validation tool.
Other agents and tools
Additional agents support landscape structure, needs, market sizing, and service discovery. They use internal tools for landscape and segment reference, market reports and sizing, link validation, and economic research. We do not list every tool or dimension here; the pipeline above covers the core flow from taxonomy through to product images.
Where we use LLM judges
- Judge Agent: Scores discovered organizations on six dimensions, applies a weighted overall score, and uses the validation tool for URL and rule-based checks. We filter to orgs above a confidence threshold before logo enrichment.
- Scoring Agent: Scores entities (organizations or products) on multiple dimensions using sector rubrics. It uses search and LLMs to research and output scores plus short rationales. We use it to select top products (and can use it for orgs) after discovery.
Both return structured JSON so we can store scores, filter by threshold, and trace decisions.
Unit economics of the workflow
We track the end-to-end cost of generating each organization or product record in the database. From search and discovery through scoring, validation, and asset enrichment, we measure latency and token usage per run so we can keep unit economics predictable as we scale. That visibility lets us tune prompts, choose when to run parallel agents, and align cost with the value of each new data point.