PYRAMYD vs Hebbia
Hebbia answers from documents. PYRAMYD answers from the graph.
Both ship agentic AI grounded in source material. The difference is whether the source is a document corpus you upload or a pre-populated typed graph of the enterprise software market.
Side-by-side
What each platform is built for.
Both are agentic AI surfaces over a structured substrate. The difference is what's in the substrate, who curates it, and what question shapes it was built for.
| Dimension | Hebbia | PYRAMYD |
|---|---|---|
| Core substrate | Long-context document corpus + Matrix interface for question→answer-grid workflows. | Typed product graph · 90 node types, 2.4M+ reviews-as-edges. |
| Primary vertical | Financial services (~30% of asset managers · per Hebbia 2025 reporting). Heavy in research, due diligence, legal. | Enterprise software intelligence · CI, RFX, sales enablement, product ops teams. |
| Best for question | 'Extract every revenue mention from these 200 earnings transcripts' · spreadsheet-shaped document Q&A. | 'How is our competitive set evolving in CRM?' · graph-traversal questions over a typed substrate. |
| Data source | Customer uploads · documents, PDFs, transcripts. Customers bring the corpus. | PYRAMYD pre-populates · 249K+ products, 2,539 categories, 1,000+ live signal sources refreshed daily. |
| Citation model | Cell-level citation to source document + page. | Per-claim chain · source URL, retrieval timestamp, model + prompt hash, quality + confidence scores, audit log ID. Article 50 ready. |
| Agentic architecture | Matrix-style agentic workflows · iterate over a corpus with parallel column processors. | Supervisor + 20 specialist worker agents · 156 graph-grounded tools, MCP-native delivery. |
| Per-seat list price (2026) | Custom enterprise · estimated $20K-$80K+/seat/yr based on customer reports (~$1,700-$6,700/seat/mo). | Free Foundation, then five hubs from $150/seat/mo, à la carte or bundled into three plans. |
| Partnerships | FactSet, Microsoft Azure AI Foundry, Third Bridge, FlashDocs (acquired Jun 2025). | MCP-native into Claude / ChatGPT / Cursor / Windsurf / VS Code · 197 connector logos sourced from product-graph registry. |
When to pick each
Two answers, two markets.
Pick Hebbia when
- Your workflow is 'extract data from a large document corpus we upload' (M&A diligence, legal review, equity research).
- Spreadsheet-shaped document Q&A is the dominant UX pattern.
- Financial services or legal vertical with heavy regulatory document workflows.
- Long-context language model behavior is the primary value driver.
Pick PYRAMYD when
- Your team asks competitive, category, or product-market questions about the SaaS landscape.
- You need a pre-populated substrate · not a corpus you have to upload.
- Battlecards, RFP responses, win/loss, and product-market-fit are core workflows.
- Per-seat economics matter · the bundle replaces 5 separate platform subscriptions.
Bottom line
Hebbia is the financial-services answer engine. PYRAMYD is the enterprise-software answer engine.
Hebbia's 30% asset-manager penetration tells you who they built for. PYRAMYD's 249K-product graph + five hubs on a free Foundation tells you who we built for. Different verticals, similar architectural commitments (agentic, cited, auditable).
See PYRAMYD answer a SaaS market question.
30 minutes. Bring a real competitive or category question. We'll show the multi-hop traversal, the citation chain, and the per-seat economics vs. your current stack.