The Platform

How every answer stays honest.

Ask a question, get an answer you can put in front of your CEO, because every answer lists the sources it came from. Four layers make that possible: the Data Foundation holds the facts, the AI Models read them, Studio lets you build on them, and APEX answers in plain language from the graph's records and shows the sources it used.

Book a demo See the data foundation

Four Layers

The PYRAMYD is the architecture.

Click any band of the PYRAMYD to expand. Each layer works on its own; together they're one system: one workspace and one team of agents on one graph.

Layer 04

APEX

Agents on top of the entire stack.

APEX puts agents on top of the AI Models layer: they answer from the graph and show the sources they used. It routes each question through one supervisor to 20 specialist agents (Battlecards, Win/Loss, RFX requirements, reviews, market research, financials, and more), so you ask one question and the right specialist answers.

20 specialist agents routed by intent and skill
150+ tools across the specialist agents
Early version: ChatGPT, Claude Desktop, Cursor, and Zed read your battlecards, competitors, and signals with a scoped token
Every answer lists the records it used, with a link back to each original source where one exists

specialist agents · 150+ tools

Built on a typed graph, with vector search as a helper. Built on typed product records, not loose text. Built for software companies, not generalists.

One graph instead of four tools

One workspace instead of four separate tools.

Competitive intelligence, product operations, sales enablement and RFPs, and AI context are usually four products, bought separately by product, marketing, and sales teams. In PYRAMYD they run on one graph, around your product.

Your product at the center, connected to the market, competitors, customers, and deals, with agents working on that evidence for your product, marketing, and sales teams.

One source of truth for three decisions.

Product decides what to build, marketing decides how to position it, and sales decides how to win, from the same evidence about your product, its market, competitors, customers, and deals. PYRAMYD ships one platform, one team of agents, and one source of truth, on a graph of the software market that is filled before you sign in.

The Architectural Advantage

A typed graph underneath, with vector search as a helper.

Why a typed, traversable knowledge graph delivers more reliable multi-hop reasoning than disconnected document chunks.

Vector RAG

Disconnected document chunks. Brittle on multi-hop reasoning.

Retrieval unit: Text chunk, ranked by similarity

Typed graph (PYRAMYD)

Typed nodes and edges. Multi-hop reasoning with citations.

Retrieval unit: Typed graph node (Product, Vendor, Category, Role, Country)

Benchmark Comparison

Multi-hop reasoning
Vector
Weak · cosine similarity on chunks
Graph
Native · traversal across node types
Lift:
Citation granularity
Vector
Document-level
Graph
Value-level · each enriched value keeps its source links and when they were retrieved
Lift:

Multi-hop reasoning	Weak · cosine similarity on chunks	Native · traversal across node types
Citation granularity	Document-level	Value-level · each enriched value keeps its source links and when they were retrieved

PYRAMYD's stack: Mastra Graph RAG + CopilotKit UI + 99-node universal schema + about 200 catalogued connectors + 2,000+ signal sources.
Background · Microsoft Research GraphRAG (arXiv:2404.16130)

Multi-hop reasoning

Every hop is typed. Every answer lists its sources.

Watch APEX traverse the graph: from a Category, through its top Products, to their Reviews, to the underlying Signals — assembling a cited answer in 4 hops. A vector store can't do this — it retrieves similar text, not connected nodes.

Category
Product · Vendor
Review aggregates
Signals (funding, talent, releases)

Hop 0 / 5

Typed graph retrieval follows the links between records, so multi-hop questions do not depend on text similarity. Every hop here is a real FK constraint in the production graph.

How it works

Four stages. One graph.

From a vendor's release note hitting the ingestion layer to APEX citing it in a sales-rep briefing — the path through the platform, animated.

G2TrustRadiusGetAppCapterraSoftware AdviceProduct HuntPeerSpotVendor websitesTechnical documentationChangelogsAPI docsStatus pagesPress releasesBlog feedsInvestor relations pagesTechCrunchBusinessWirePRNewswireGlobeNewswireReutersBloombergSEC EDGAREU Commission filingsUSPTO PatentsWIPO IP databaseCrunchbaseCB InsightsFedRAMP marketplaceFINRA filingsLinkedIn jobsGreenhouse boardsLever boardsWorkable boardsIndeedAngelList TalentGlassdoorSalesforce AppExchangeHubSpot EcosystemSlack App DirectoryAtlassian MarketplaceShopify App StoreAWS MarketplaceAzure MarketplaceGoogle Cloud MarketplaceZoomInfo dataReddit (r/SaaS, r/devops, r/cscareers)Hacker NewsTwitter / XLinkedIn PulseIndustry RSS aggregatorVertical newslettersSubstack techSOC 2 attestationsISO 27001 registerHIPAA disclosuresEU AI Act Article 50 disclosuresG2TrustRadiusGetAppCapterraSoftware AdviceProduct HuntPeerSpotVendor websitesTechnical documentationChangelogsAPI docsStatus pagesPress releasesBlog feedsInvestor relations pagesTechCrunchBusinessWirePRNewswireGlobeNewswireReutersBloombergSEC EDGAREU Commission filingsUSPTO PatentsWIPO IP databaseCrunchbaseCB InsightsFedRAMP marketplaceFINRA filingsLinkedIn jobsGreenhouse boardsLever boardsWorkable boardsIndeedAngelList TalentGlassdoorSalesforce AppExchangeHubSpot EcosystemSlack App DirectoryAtlassian MarketplaceShopify App StoreAWS MarketplaceAzure MarketplaceGoogle Cloud MarketplaceZoomInfo dataReddit (r/SaaS, r/devops, r/cscareers)Hacker NewsTwitter / XLinkedIn PulseIndustry RSS aggregatorVertical newslettersSubstack techSOC 2 attestationsISO 27001 registerHIPAA disclosuresEU AI Act Article 50 disclosures

Built for enterprise security from day one

Four product layers, audit-ready by design.

Data Foundation, AI Models, Studio, and APEX — all running on Azure with row-level security, tenant-isolated graph slices, embeddings on the core tables, and a signal pipeline.

Architecture

Compliance

SOC 2 Type 2In progress
ISO 27001In progress
ISO 42001In progress
GDPRIn progress
CCPAIn progress
EU AI Act Article 50In progress

EU AI Act Article 50

Article 50 has applied since 2 August 2026. Breaches can be fined up to EUR 15 million or 3% of worldwide annual turnover. Generated images already carry a machine-readable AI marker; disclosure and marking for text answers are being built.

Performance is part of the foundation. 3.08× query speedup live (10-query test 2,519ms → 818ms) via pinned-transaction architecture.

See the agents work on your own product.

Book a 30-minute demo. We'll start from your product, run a question across your market, competitors, and accounts, and show every source.

Book a demo Review the security posture