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Documentation Index

Fetch the complete documentation index at: https://docs.meetdoris.com/llms.txt

Use this file to discover all available pages before exploring further.

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Getting Started

After connecting the sandbox to your AI tool — Claude, ChatGPT, Cursor, Copilot, or any MCP-compatible agent — start a new conversation and try any prompt below. Your AI will automatically call the right ontology tools. You don’t need to know the API.
The sandbox contains a realistic B2B pipeline for Meridian Technologies — 99 accounts, 244 deals, and 10,000+ connected entities. Everything you see is what Doris builds from your real CRM data, meetings, and conversations.

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Quick Start Prompts

Try these first to see what the ontology can do: 
What deals are at risk and why?

Give me a pipeline summary — how many deals at each stage, total value, and what's changed recently?

Which commitments are overdue right now?

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Workflow 1: Deal Review

Walk through a deal the way a sales manager would before a forecast call. Step 1 — Find the deal: 
Show me the Ironforge Core Migration deal with all available context
Step 2 — Understand the stakeholders: 
Who are the key stakeholders on this deal? What are their roles and decision power?
Step 3 — Check commitments: 
What commitments are outstanding on this deal? Are any overdue?
Step 4 — Review the strategy: 
What's our strategy for winning this deal? What are the main risks?
Step 5 — Look at recent meetings: 
What happened in the most recent meeting on the Ironforge deal?
What you’ll see: A complete deal picture — stakeholders with roles (champion, blocker, economic buyer), overdue commitments creating risk signals, competitive positioning against Gong and Clari, and meeting summaries with specific action items.

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Workflow 2: Meeting Prep

Prepare for an upcoming customer meeting in 60 seconds. 
I have a meeting with Cobalt Security tomorrow. Prep me — what do I need to know?
Your AI will pull together:
  • Active deals and their stages
  • Key stakeholders and their concerns
  • Recent meeting history and what was discussed
  • Open commitments (especially overdue ones you need to address)
  • Competitive landscape (CrowdStrike is in the mix)
  • Deal strategy with specific risks and next steps
Follow up with: 
What objections should I expect from Michael Dunn?

What commitments did we make in the last meeting that we haven't delivered on?

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Workflow 3: Pipeline Analysis

Analyze pipeline health across the entire org. Overall health: 
How many deals are in each pipeline stage? What's the total pipeline value?
Stuck deals: 
Which deals have been in the same stage for more than 30 days?
At-risk deals: 
Find deals that have overdue commitments — those are at risk of stalling
Closed-lost analysis: 
Show me the deals we lost. What were the reasons? Do you see any patterns?
Win analysis: 
What do our closed-won deals have in common? What accounts and industries did we win in?

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Workflow 4: Competitive Intelligence

Understand your competitive landscape. 
Which competitors are we seeing most often? What's our win rate against each?

How do we position against Gong? What are their strengths and weaknesses relative to us?

Which deals currently have a competitor in the evaluation? What's our strategy for each?

Are there any patterns in why we lose deals to competitors?

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Workflow 5: Stakeholder Mapping

Map the buying committee across an account. 
Show me all contacts at Apex Industries — who are the decision makers, champions, and blockers?

Which stakeholders across the pipeline have the title VP or above?

Find accounts where we haven't identified an economic buyer yet

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Workflow 6: Commitment Tracking

Track follow-ups across the entire pipeline. 
What commitments are overdue right now? Group them by deal.

Which rep has the most overdue commitments?

Show me all buyer commitments that are pending — these are things the customer promised us

What commitments did we complete this month?

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Workflow 7: Cross-Entity Exploration

The real power of the ontology — connecting entities across types. 
Start with the Velocity Dev Tools Suite deal. Show me the stakeholders, then show me what meetings 
each stakeholder attended, and what commitments came out of those meetings.

Find all objections that appeared in deals we eventually won. What tactics did we use to overcome them?

Which accounts have multiple active deals? Are there cross-sell opportunities?

Show me the relationship between meetings, commitments, and deal stage progression. 
Do deals with more frequent meetings close faster?

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Tips for Better Results

Instead of “show me deals,” try “show me Enterprise deals in Negotiation stage with amount over $200K.” The ontology supports filtering by any field.
The best insights come from drilling down. Start broad (“which deals are at risk?”), then go deep (“what specifically is blocking the Ironforge deal?”). Your AI maintains context across the conversation.
When you ask about a deal, your AI can expand related data: stakeholders, commitments, objections, competitors, meetings, strategy, and more. Ask for “full context” to get everything.
“Compare our closed-won deals to our closed-lost deals” or “How does the Apex deal compare to the Cobalt deal in terms of stakeholder coverage?” Comparative analysis reveals patterns.
“What objections keep appearing?” or “Which tactics are most effective?” The knowledge graph tracks patterns across all deals and meetings.

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Entity Types You Can Query

TypeWhat it containsExample query
dealPipeline opportunities with stage, amount, owner”List deals over $300K in Proposal stage”
accountBuyer companies with industry, size, location”Show me all healthcare accounts”
personContacts with title, role, decision power”Who are the C-level contacts across all accounts?“
meetingMeeting records with summaries and attendees”What meetings happened this week?“
commitmentFollow-up actions with status and due dates”Show overdue commitments”
objectionRecurring objection patterns across deals”What are the most common objections?“
competitorCompetitive intelligence and win rates”How do we compare to Gong?“
tacticSales tactics with effectiveness data”Which tactics work best in Negotiation?“
strategyPer-deal strategy with risks and actions”What’s the strategy for the Apex deal?“
pipelinePipeline stages with probabilities”Show me pipeline stages and win probabilities”

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Ready for Your Own Data?

The sandbox shows what Doris does with synthetic data. Imagine this running on your real CRM, your actual meetings, and your team’s commitments.

Book a Demo

See it live on your pipeline — 30 minutes, no prep needed.