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PYRAMYD

The Platform

One graph. Four layers. The PYRAMYD itself.

Our logo is our architecture. From the Data Foundation at the base, through the AI Models layer, up through Studio, to the APEX copilot at the tip.

Four Layers

The PYRAMYD is the architecture.

Click any band of the PYRAMYD to expand. Each layer is independently powerful · together they're the system that replaces four point tools with one workspace and one copilot.

Layer 04 · APEX

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

21

specialist agents · ~165 graph tools

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

Four Jobs, One Platform

One workspace for the four teams that win on intelligence.

Product Operations, Competitive Intelligence, Sales Enablement & RFX, and AI Context Management · your buyer is the same person across all four. So is the data.

PRODUCT OPSRoadmap aligned to livemarket signals.Replaces Pendo / ProductboardCOMPETITIVE INTELLIGENCEBattlecards that staycurrent automatically.Replaces Klue / CrayonAI CONTEXT MANAGEMENTGrounded answers withcited sources, no hallucinations.Replaces ad-hoc LLM wrappersSALES ENABLEMENT & RFXRFP responses drafted fromyour live capabilities.Replaces Loopio / ResponsiveProductGraphONE PLATFORM
One workspace, one copilot, one source of truth · across the four jobs your teams already do.

Stop paying four bills for one job.

The same buyer signs the contracts for CI, RFP, sales enablement, and AI grounding. Their teams need the same intelligence. PYRAMYD ships one platform, one copilot, one source of truth · backed by the only pre-populated enterprise-software knowledge base in the market.

The Architectural Advantage

Graph RAG vs vector retrieval · structurally different substrates.

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.

Accuracy range: ~20% zero-shot to ~80% fine-tuned

Graph RAG (PYRAMYD)

Typed entities + relationships. Multi-hop reasoning with citations.

Retrieval unit: Typed graph entity (Product, Vendor, Category, Persona, Country)

Benchmark Comparison

  • Aggregation queries

    Vector
    8% relevance
    Graph
    23% relevance

    Lift:

  • Cross-document reasoning

    Vector
    8% accuracy
    Graph
    33% accuracy

    Lift:

  • Avg accuracy lift

    Vector
    Graph
    Knowledge-graph grounding

    Lift: +35-54%

  • Multi-hop reasoning

    Vector
    Weak · cosine similarity on chunks
    Graph
    Native · FK traversal across entity types

    Lift:

  • Citation granularity

    Vector
    Document-level
    Graph
    Cell-level · source URL + timestamp per claim

    Lift:

PYRAMYD's stack: Mastra Graph RAG + CopilotKit UI + 88-node universal schema + 200+ connectors + 1,000+ live signal sources.
Sources · Gartner 2026 Hype Cycle for Agentic AI · Fluree · Neo4j · Atlan · AIMultiple · Microsoft Research GraphRAG (arXiv:2404.16130)

Multi-hop reasoning

Every hop is typed. Every claim is cite-able.

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 entities.

  • Category
  • Product · Vendor
  • Review aggregates
  • Live signals (funding, talent, releases)

Hop 0 / 5

CategoryCRMSalesforceHubSpotPipedriveG2 reviewsTrustRadiusFundingsignalTalentsignalCitedbattle card

Gartner's 2026 Hype Cycle for Agentic AI shows 3-4× accuracy lift on multi-hop queries when retrieval is graph-typed instead of vector-only. 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.

13 OF 1,000+ LIVE SOURCESG2REVIEWSTrustRadiusREVIEWSGetAppREVIEWSCapterraREVIEWSProduct HuntDISCOVERYVendor sitesVENDORTech docsVENDORChangelogsVENDORPress releasesVENDORSEC EDGARREGULATORYCrunchbaseFINANCIALUSPTO PatentsIPLinkedIn jobsTALENTINGESTIONdedup · normalize · hash1,240 signals · last 60s1,000+ source feeds
G2TrustRadiusGetAppCapterraSoftware AdviceProduct HuntGartner Peer InsightsIT Central StationFeaturedCustomersCrowdReviewsVendor websitesTechnical documentationChangelogsAPI docsStatus pagesPress releasesBlog feedsInvestor relations pagesTechCrunchThe InformationArs TechnicaVentureBeatProtocolStratecheryAxios ProBusinessWirePRNewswireGlobeNewswireReutersBloombergSEC EDGAREU Commission filingsUSPTO PatentsWIPO IP databaseCrunchbasePitchBook public dataCB InsightsFedRAMP marketplaceFINRA filingsLinkedIn jobsGreenhouse boardsLever boardsWorkable boardsIndeedAngelList TalentBuilt InGlassdoorSalesforce AppExchangeHubSpot EcosystemSlack App DirectoryAtlassian MarketplaceShopify App StoreAWS MarketplaceAzure MarketplaceGoogle Cloud MarketplaceKlue feedsCrayon feedsKompyte intelligenceOwler signalsOwletterZoomInfo data6sense signalsBombora intentReddit (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 HuntGartner Peer InsightsIT Central StationFeaturedCustomersCrowdReviewsVendor websitesTechnical documentationChangelogsAPI docsStatus pagesPress releasesBlog feedsInvestor relations pagesTechCrunchThe InformationArs TechnicaVentureBeatProtocolStratecheryAxios ProBusinessWirePRNewswireGlobeNewswireReutersBloombergSEC EDGAREU Commission filingsUSPTO PatentsWIPO IP databaseCrunchbasePitchBook public dataCB InsightsFedRAMP marketplaceFINRA filingsLinkedIn jobsGreenhouse boardsLever boardsWorkable boardsIndeedAngelList TalentBuilt InGlassdoorSalesforce AppExchangeHubSpot EcosystemSlack App DirectoryAtlassian MarketplaceShopify App StoreAWS MarketplaceAzure MarketplaceGoogle Cloud MarketplaceKlue feedsCrayon feedsKompyte intelligenceOwler signalsOwletterZoomInfo data6sense signalsBombora intentReddit (r/SaaS, r/devops, r/cscareers)Hacker NewsTwitter / XLinkedIn PulseIndustry RSS aggregatorVertical newslettersSubstack techSOC 2 attestationsISO 27001 registerHIPAA disclosuresEU AI Act Article 50 disclosures

The workspace

What your teams see, every day.

Persona-tuned modules sharing one graph. Two of the most-used surfaces below; the AI Context module + Product Ops dashboards live behind the demo.

Competitive Intelligence · Battle Card

PYRAMYD battlecard comparing Pyramid Analytics vs Klue, captured live from app.pyramyd.ai
Live from app.pyramyd.ai · /battlecardsGenerated · cited · refreshable

Auto-generated against your category. Refreshed weekly from the graph. Every claim cites its source.

Sales Enablement · RFP Drafter

PYRAMYD RFX Manager showing inbound RFPs and graph-grounded drafting workflow — captured live from app.pyramyd.ai
Live from app.pyramyd.ai · /rfx-managerDrafted · cited · graph-grounded

Paste an RFP, get cited responses pulled from your library and the live graph. Sub-5-hour proposals.

Built Enterprise-Grade from Day One

Four product layers, audit-ready by design.

Data Foundation, AI Models, Studio, and APEX · all running on AWS-native infrastructure with row-level security, tenant-isolated graph slices, inline vector embeddings, and a continuously refreshed signal pipeline.

Architecture

CONNECTOR LAYER200+ pre-builtG2 · TrustRadius · GetAppSEC · Crunchbase · LinkedInSIGNAL SOURCES1,000+ live feedsReleases · Pricing · HiringPress · Funding · ReviewsCUSTOMER DATAYour own systemsSalesforce · HubSpotSlack · Jira · PendoENRICHMENT ETLMulti-tier refreshEmbed · Verify · ScoreProvenance + audit logTHE PRODUCT GRAPH88 node types252K+ products2,606 categories2.4M+ reviewsInline embeddings · Multi-hopTenant-isolated · AWS-nativeAPI / AUTH3-tier authRLS · Tenant slicesSSO · SAML 2.0APEX COPILOTGraph RAG copilotCited multi-hop answersLLM-agnostic · Bring your ownWORKSPACE MODULESCI · ProdOps · RFX · ContextPersona-tuned workspacesOne source of truthMCP SERVERAny agent, your graphClaude · ChatGPT · CopilotYour internal LLMINGESTIONENRICHGRAPHSURFACES

Compliance

  • SOC 2 Type 2In progress
  • ISO 27001In progress
  • ISO 42001In progress
  • GDPRIn progress
  • CCPAIn progress
  • AWS Well-ArchitectedIn progress
  • EU AI Act Article 50Aug 2026 ready

EU AI Act Article 50

Transparency mandate effective August 2026. Non-compliance penalties reach 7% of global annual revenue. PYRAMYD's citation hierarchy and audit trails are built to satisfy the requirement.

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

See APEX answer your hardest competitive question.

Book a 30-minute demo. We'll run a multi-hop question against your category and show every citation.