The product graph for enterprise software teams

LIVE · releaseSalesforce shipped Agentforce 3.0 — pricing diff +12%

Every competitor.Every category.Every signal.All in one live Graph!

RFPs in under 5 hoursBattle cards refreshed weeklyOne workspace, four teams

Loading 16,600-node production slice…

Pre-populated with 0K+ products across 0.0K categories, 0.0M+ reviews, and 0K+ live signal sources — so your CI teams stop rebuilding the same intelligence.

200+ pre-built connectors

Browse the full catalog

Why a graph, not a vector store

“Graph RAG outperforms vector retrieval by 3–4× on multi-hop reasoning and lifts enterprise AI accuracy by 35–54%.”

Gartner Hype Cycle for Agentic AI · 2026 (also: Fluree, Neo4j, AIMultiple benchmarks)

3–4×

multi-hop lift

35–54%

accuracy gain

99%

enterprises lose to ungrounded AI

One subscription. One graph. One copilot.

Stop renting four tools. Own the graph.

Most teams pay $640K–$1.4M/yr across four point tools that don't share a graph. PYRAMYD replaces that stack with one subscription, one source of truth, and a copilot that cites every answer.

Your current stack	Annual cost	PYRAMYD replaces with
Klue / Crayon — Competitive Intel	$50K–$100K	CI module — live categories, weekly battle cards
Loopio / Responsive — RFP / RFX	$30K–$80K	RFX module — cited proposals in under 5 hours
Productboard / Pendo — Product Ops	$60K–$200K	Product Ops module — Feature Market Fit + competitor releases
Neo4j + Data team — Build-your-own KG	$500K+ · 12–24 mo	Pre-built, MCP-ready graph — live in days, not quarters
Total	$640K–$1.4M / yr	From $50K / yr

Annual cost ranges from public ACV benchmarks and analyst commentary on each category (Klue/Crayon, Loopio, Productboard, Neo4j) · All amounts USD · Build-your-own estimate includes engineering + data acquisition over 12–24 months.

The Platform

One platform. Four layers. The PYRAMYD itself.

The PYRAMYD logo is our architecture. Click any band of the pyramid to see what powers it — from the Data Engine at the base to the APEX copilot at the tip.

Layer 04

APEX

The supervisor copilot on top of the entire stack.

APEX is the citation-grounded copilot that sits on top of the AI Models layer and reasons over the live graph. It orchestrates 21 specialist agents (Battlecards, RFX, Win/Loss, Pricing, Releases, Personas, …) through one supervisor — so users ask one question and the right specialist responds.

21 specialist agents routed by intent and skill
~165 graph-grounded tools — every tool reads from typed nodes, not raw text
MCP-native — plug APEX into Claude / ChatGPT / Cursor / any MCP client
Per-answer citation set with source URL, model, and prompt hash

specialist agents · ~165 graph tools

The Pipeline

A single packet of intelligence, flowing up the stack.

Watch a signal travel from a connector through each layer of the PYRAMYD — arriving at the user as a cited, audit-trail-backed answer in seconds.

Connector

Data

AI Models

Studio

APEX

Answer

Layer 01 · Data Engine

1,554 FK constraints · 88 node types · graph hydration

Layer 02 · AI Models

Embeddings · provider routing · token + cost audit

Layer 03 · Studio

Dashboards · Sheets · Documents · Slides · Agents

Layer 04 · APEX

Specialist agent routing · citation assembly · MCP egress

Built on Graph RAG, not Vector RAG. Built on real product data, not scraped text. Built for enterprise software teams, not generalists.

One Graph, Four Jobs

Built for the four teams that win on intelligence.

Each use case shares the same graph, the same copilot, and the same source of truth — so what one team learns, every team can act on.

Use Case 01 of 04

Competitive Intelligence

2,606 live category taxonomies, 2.4M+ aggregated reviews, 1K+ signal sources, and auto-generated battle cards your sales team actually trusts.

Read the use case

Use Case 02 of 04

Product Operations

Feature Market Fit scoring across 250K+ products, weekly competitor feature tracking, and cross-team alerts when the market moves.

Read the use case

Use Case 03 of 04

Sales Enablement & RFX

RFP intake auto-matched to the graph. APEX drafts cited responses. Sub-5-hour RFPs and a 15–30% win-rate lift from AI proposal tools.

Read the use case

Use Case 04 of 04

AI Context Management

A universal context layer with an MCP server, row-level security, and tenant isolation. The trusted layer underneath every grounded AI workflow.

Read the use case

The Data Moat

The asset that compounds weekly.

Internal estimate: replicating this would require 12–24 months and $1–3M of focused engineering and data spend. PYRAMYD's lead grows every refresh cycle.

252K

enterprise software products

Across 2,606 categories, with 2.4M+ aggregated reviews and 88 universal node types linking them.

1,000+

continuously refreshed signal sources

200+ pre-transformed connectors, 183 bi-directional flows. Multi-tiered refresh tuned to release cadence.

Graph RAG

inline embeddings · multi-hop

Vertical AI grounded in typed entities and citation hierarchy — not a horizontal copilot reading the open web.

See the data behind the graph

Built for Enterprise

Trusted by procurement. Priced for teams.

Enterprise-grade compliance from day one, with pricing built to land, expand, and compound.

Security & Trust

See how we keep your data yours.

SOC 2 Type 2 · ISO 27001 · ISO 42001 · GDPR · CCPA · AWS Well-Architected — all in progress. Row-level security, tenant-isolated graph slices, audit-ready AI answers.

EU AI Act Article 50 ready — August 2026 deadline.

Read the security posture

Pricing