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PYRAMYD

The Data Foundation

The evidence behind what you build, how you position it, and how you win.

The software market, already mapped and connected to your own product, customers, and deals, so the question that used to take an analyst a week takes your team a minute, and every answer arrives with the source attached.

250K+ Products2,546 Categories2.4M+ Reviews99 Node Types10 Field Groups463 Industries249 Countries4,349 Roles

Production slice · extracted 12 Aug 2026

18,586 nodes and 22,903 edges of the real graph — vendors, products, reviews, categories, and the links between them.

~7 MB · click any node, then show 1, 2, or 3 hops — loads on demand so this page stays fast

The enrichment pipeline

Every node, 10 field groups, one canonical shape.

Each taxonomy node is enriched through the same 10 field groups in canonical tab order. Watch a single category fill in — every cell carries its model, its sources, and a quality score.

Product CategorySalesforce Sales Cloud · 88

Enrichment progress

100%

Filling Pulse …

  • 01Overview
  • 02Demand
  • 03Market
  • 04Landscape
  • 05Trends
  • 06Operations
  • 07Compliance
  • 08Economics
  • 09Capabilities
  • 10Pulse

Every taxonomy node (category, industry, country, role, product) carries the same 10 field groups in this canonical order. Same shape across taxonomies = one mental model for analysts, one API for connectors, and the sources kept with each AI-written value.

Enrichment on demand

Enrich any taxonomy, row, column, group, or cell.

The same runner powers every scope. You pick what to refresh, and every enrichment compounds back into the shared graph.

Taxonomy

1 of 5

Every row in the table, every enrichable field. Held under an advisory lock, so only one bulk run is in flight at a time.

One at a time

Row

2 of 5

One node (e.g. one category, one country) refreshed across every enrichable field group.

Runs in parallel

Column

3 of 5

One field on one node. Fields like founding year or a stock ticker resolve from a free public API instead of a model.

Runs in parallel

Group

4 of 5

One of the 10 field groups (e.g. demand, landscape, compliance) refreshed on one node.

Runs in parallel

Cell

5 of 5

One value inside a field on one node — the smallest unit, for fixing a single bad value.

Runs in parallel

Why it compounds

Every enrichment you run
makes the graph richer for everyone.

When a taxonomy row is enriched, the result lives in the shared product graph, so the next team that opens that category, country, or role finds it already filled in. You pay only for the scope you run.

  • · A cell or column run calls the model for one value, not for the whole row or table.
  • · Every value is citable — the model, the source URLs, and when they were retrieved.
  • · Every enriched row is checked by a rule-based auditor; only rows that pass are embedded.

What you pay

Pay for the scope you run.

Cell · 1 field, 1 row

One model call, or a free public-API lookup

Smallest

Row · 1 node, 10 groups

Every enrichable field, then the verification gate

One node

Taxonomy · every row

Advisory-locked: one bulk run at a time

Whole table

Runs are paid with the AI tokens on your plan (see Pricing) · the same verification gate applies to every scope.

Value-level provenance, in the app

Click any field. See where it came from.

A capture from the live app: the provenance popover shows how fresh the record is against its target, its quality, confidence, and coverage, the sources behind it, and its history.

The provenance popover open on the CRM Software category in the PYRAMYD app: freshness within its target; quality 70, with five pipeline warnings; confidence very high, 90%; coverage 100%, 11 of 11 sections; and the eight pipeline data sources behind it, among them G2, Capterra, BuiltWith, Crunchbase, Product Hunt, and GitHub.

Captured from the live app on 23 October 2026 · Markets › Categories, the CRM Software category, with its provenance popover open on the Sources tab.

Freshness

How recently the record was verified against its source, measured against a target. In this example the record is within its target.

Quality & Confidence

Quality is the underlying signal strength (70 here, with the five pipeline warnings behind it listed). Confidence is how sure the model is the extraction is correct (90% here). Both are shown as scores, not stars.

Sources · Quality · History · Provenance

Four tabs · Sources lists the links behind the value, Quality explains its score, History shows when it was checked, and Provenance names the model and the run that wrote it.

What's in the graph

Every vendor is a typed node with real fields.

A real record from the production graph, read on 8 October 2026: the Salesforce company node and two of its products. Scores are on the 0–100 scale.

Company node · as stored

{
  "uuid": "498ff126-ced2-416c-9422-87c8e511ae57",
  "company_name": "Salesforce",
  "slug": "salesforce",
  "year_founded": 1999,
  "headquarters": { "city": "San Francisco", "state": "CA" },
  "country": "USA",
  "website_url": "https://www.salesforce.com",
  "provenance": {
    "ein": {
      "model": "gpt-5.6-luna",
      "quality": { "pass": true, "score": 100,
        "scored_at": "2026-10-07T17:59:58Z" }
    }
  }
}

Linked to it: 101 product nodes, 23,384 review nodes and 74 categories (its products show 214,229 reviews on the review sites). Every enriched field records the model that wrote it and the quality score it passed.

Two of its 101 products

{
  "company": "Salesforce",
  "products": [
    { "product_name": "Salesforce Sales Cloud",
      "product_review_score": 88,
      "review_count": 25877,
      "category": "CRM Software" },
    { "product_name": "Salesforce Service Cloud",
      "product_review_score": 88,
      "review_count": 7997,
      "category": "Help Desk Software" }
  ],
  "top_categories_by_reviews": [
    "Work Management Software",
    "CRM Software",
    "Cloud Platform as a Service (PaaS)",
    "Marketing Automation Software"
  ]
}

In early access today: create a token under Settings › Workspace › API and Claude Desktop, Cursor, ChatGPT, or Microsoft 365 Copilot can read your battlecards, competitors, and signals. Wider graph queries are coming.

The Six Layers

Volume. Velocity. Variety. Governance. Network effects.

Each layer reinforces the others. Together they form a foundation that gets deeper with every refresh · not narrower.

01

Volume

250K+ software products mapped across 2,546 categories with 2.4M+ aggregated reviews.
02

Velocity

2,000+ signal sources in the catalog, chosen per watchlist. Refresh runs on demand, per source or per record, when you ask for it.
03

Variety

99 universal node types, 431 edge types and about 200 connectors in the catalogue. Every node typed; every edge traversable.
04

Governance

SOC 2 Type 2 · ISO 27001 / 42001 · GDPR · CCPA · EU AI Act Article 50 — all in progress. Every signal carries its source URL, and each enriched value records its source links, when they were retrieved, the model that wrote it, and a quality and confidence score.
05

Network Effects

Every customer's RFX responses, battlecards, and win/loss data stay private to their Organization. The public graph grows as we add sources, for everyone.
06

AI Specialization

Embeddings on the core tables, plus graph search that follows the links between records (Graph RAG). Built for questions about the software market, not general chat.

250K+ products and 2.4M+ reviews already in one graph.

Depth × Breadth

Not just rows. Every row, enriched across 10 dimensions.

Every taxonomy carries the same 10 field-group schema — overview, pulse, demand, market, landscape, trends, economics, operations, compliance, capabilities. Multiply row count × column width × 10 dimensions and the foundation is structured, not just big.

NodeRowsColsFields (rows × cols)Refresh
Products250,63231679.2MOn demand · per source
Reviews2,455,618118289.8MOn demand · major review platforms
Vendor features3,847,8422901115.9MOn demand · vendor changelogs
Companies1,436,837314451.2MOn demand · funding + hiring
Contacts3,383,472126426.3MOn demand · roles + moves
Categories2,546212539,752On demand · LLM-enriched
Industries46311854,634On demand · LLM-enriched
Countries24910125,149On demand · regulator-tracked
Roles4,34986374,014On demand · LLM-enriched
Total~11.4Macross 9 node types~2.4B fields (rows × columns)On demand

Enrichment coverage

99–100% of every taxonomy, fully enriched.

Each enriched row records the model and the time of its run; category rows also keep the web citations that were found. Counts come from the production database.

Categories

100%

2,539 of 2,546 rows enriched

1 model

last enriched: 2026-06-19

Industries

100%

463 of 463 rows enriched

1 model

last enriched: 2026-08-13

Countries

100%

249 of 249 rows enriched

2 models

last enriched: 2026-08-14

Roles

100%

4,329 of 4,349 rows enriched

5 models

last enriched: 2026-06-18

Refresh on demand

Refresh any node when you need it.

Categories, industries, countries, roles, products, and reviews can each be re-enriched from the workspace when you need them; token consumption applies.

On demand

User-triggered · any node

Need fresher data right now? Hit refresh on any node from the workspace to queue a fresh enrichment run. Token consumption applies per re-enriched row, billed against your workspace budget.

Signals

Every refresh brings them in

Review feeds, competitor website diffs, funding announcements, hiring signals, and press wires come in each time their sources are refreshed, then show in Competitor 360 and the signal feed. (Alert delivery is paused for now.)

Why this matters

Every node carries a verified-at timestamp. When a review changes, a category shifts, or a competitor ships a price change, anyone on the team can rebuild the battlecard or refresh the rows that matter most, with provenance kept on every cited claim.

Live Today

What's in the graph today.

These aren't roadmap numbers. Every figure here is queryable on the platform today.

01

250K+

Software products tracked across 2,546 categories

02

2.4M+

Aggregated software reviews from the major review platforms

03

2000+

Signal sources in the catalog, selectable per watchlist

04

99

Universal node types across the entire graph schema

05

431

Edge types, each one checked by the database

06

3.08×

Live query speedup vs. baseline (2,519ms → 818ms)

99 Universal Node Types

Every node in the software market, typed and connected.

The graph schema is the foundation. Ten categories span people, nodes, products, revenue, finance, operations, comms, content, data, and systems — and every edge between them is a query the graph can answer.

8types

People

Contacts · roles · positions · interviews

8types

Companies

Companies · teams · workspaces · segments · locations · countries · industries

6types

Products

Products · categories · features · releases · reviews

12types

Revenue

Deals · evaluations · orders · pipelines · subscriptions · contracts · campaigns · cadences · battlecards · assessments

7types

Finance

Transactions · postings · ledgers · periods · budgets · forecasts · filings

12types

Operations

Ideas · requirements · issues · projects · roadmaps · cycles · objectives · capabilities · processes

4types

Comms

Communications · chats · channels · events

12types

Content

Documents · discussions · articles · snippets · sheets · slides · notebooks · canvases · forms · files · folders · transcripts

14types

Data

Datasets · catalogs · connectors · transformations · prompts · agents · runs · models · experiments · metrics · signals · dashboards

16types

Systems

Repositories · branches · commits · credentials · settings · activities · devices · alerts · applications · policies · services

Every Signal Cited

Provenance is not optional.

Enriched records carry source, time, model, and confidence where they were produced by a run.

Source URL

Every signal links back to the real source — a press release, a review, a vendor changelog, a regulatory filing.

Retrieval Timestamp

When the signal was captured. When it was last re-verified. When the source itself was updated.

Model + Version

Which model wrote the enrichment, the run it came from, and a confidence score per field.

Verification Status

Every enriched row is scored by a rule-based audit before it is used.

When a customer asks "where did this come from?" they have a defensible, regulator-ready answer.

See the graph in your category.

In 30 minutes we'll refresh the data for your top 5 competitors on the call, walk the graph, and show APEX answer a multi-hop question with every citation traceable to source.

250K+ products are not the moat. The links between them are — edges are what let the engine predict, not just retrieve.

Where do you want to take this?