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Doris builds a knowledge graph for your organization that grows smarter with every meeting. Instead of treating each deal in isolation, Doris connects the dots across your entire pipeline — tracking stakeholders across deals, learning which objections come up most, and spotting patterns in how your prospects buy.

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How it works

Every time a meeting is recorded, Doris extracts intelligence and adds it to your organization’s knowledge graph. Over time, this builds a compounding picture of:
  • Stakeholders — Who’s involved, their roles, influence, and how they’ve behaved across multiple deals
  • Objection patterns — Which objections come up most often, how they correlate with deal outcomes, and what approaches work
  • Competitor insights — Which competitors appear in your deals, how often, and in what context
  • Buying patterns — How your prospects typically buy: common stage durations, where deals stall, and what accelerates them
  • Organization patterns — Company-level intelligence like procurement cycles, decision-making structures, and budget timing
This intelligence feeds into your deal briefs, agent conversations, and the cards Doris renders in chat — so every interaction gets smarter as your team has more conversations.

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Knowledge Graph Explorer

The Explorer gives you a visual, interactive view of everything Doris has learned about your accounts and deals. Access it from the Context page.
An interactive node-and-edge visualization of your knowledge graph. Entities appear as color-coded nodes, and relationships between them appear as connecting edges. Click any node to see its full detail. Drag to rearrange, scroll to zoom, and use the toolbar to filter by entity type or confidence level.
Click any node to open a detail panel showing everything Doris knows about that entity — properties, evidence count, confidence score, source meetings, and related entities. You can adjust confidence manually or dismiss entities that aren’t relevant.
Toggle visibility of each entity type from the toolbar: stakeholders, organization patterns, objection patterns, competitor insights, buying patterns, and topic preferences. Focus on what matters for your current analysis.
Filter the graph by confidence level. High-confidence entities have been seen across multiple meetings. Lower-confidence entities may have appeared only once — useful for discovery, but filter them out when you want a clean picture.
Doris identifies potential duplicate entities (e.g., “Sarah Smith” and “S. Smith”) and surfaces them for manual review. Merge duplicates with one click to keep your knowledge graph clean.

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Cross-Deal Intelligence Cards

Doris surfaces knowledge graph insights directly in chat through interactive cards:

Organization Intelligence

Company-level patterns learned from all deals with that organization — procurement cycles, decision-making structures, and stakeholder networks.

Cross-Deal Patterns

Patterns that emerge across your pipeline: common objections by stage, competitor frequency, and buying behaviors that repeat across deals.

Objection Playbook

Your most common objections ranked by frequency and win rate, with context on what approaches have worked in past deals.

Stakeholder Map

A 2x2 influence-vs-disposition grid enriched with cross-deal history — see how stakeholders have behaved in previous deals, not just the current one.

Pain Point Categories

Cross-deal pain point patterns with win rates and overcome rates. See which pain points correlate with closed-won deals and which rebuttals work best.
These cards appear automatically in chat and deal outbox conversations when relevant context exists in the knowledge graph.

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Deal Briefs powered by KG

When the knowledge graph has sufficient data, Deal Briefs pull from cross-deal intelligence instead of just the current deal’s conversations. This means:
  • Stakeholder sections include history from other deals where the same people appeared
  • Risk assessments reference patterns from similar deals that stalled or were lost
  • Competitor context draws on what Doris has learned across your entire pipeline, not just one deal
  • Recommended next steps factor in buying patterns observed across comparable deals
The knowledge graph grows more valuable over time. After a few weeks of meetings, you’ll notice deal briefs and agent responses becoming noticeably richer with cross-deal context.

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Company Sentiment

Company pages now show sentiment trends powered by the knowledge graph. Instead of a single score, you see themes extracted across all deals and meetings with that organization — what’s going well, what concerns have surfaced, and how sentiment has shifted over time.

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Knowledge Base Integration

Doris can also pull from your uploaded knowledge base documents when answering questions in chat. Product features, pricing details, case studies, objection rebuttals, and competitor positioning extracted from your documents are available on demand — just ask. When the agent retrieves knowledge base entities, it attaches the source documents as clickable cards in the conversation so you can open the original file directly.
Upload product sheets, competitor analyses, pricing guides, and case studies to your knowledge base. Doris extracts structured entities from these documents and makes them available to the agent across all deal conversations.

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How intelligence accumulates

Doris builds knowledge through four layers:
  1. Meeting extraction — After each call, Doris extracts objections, competitors, topics, and other signals directly from the conversation
  2. Deal agent analysis — The deal agent identifies stakeholders, assigns MEDDPIC roles, and assesses influence and sentiment
  3. Cross-deal aggregation — Entities are normalized across meetings and deals, building a unified picture per stakeholder, competitor, or objection
  4. Pattern derivation — Buying patterns and organization-level insights are derived from deal stage progressions, cycle times, and stall points across your pipeline
Each layer feeds the next, and confidence scores increase as more evidence accumulates. Entities that haven’t been seen recently decay gradually, keeping your knowledge graph focused on what’s current and relevant.