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Von is built for
Enablement

What can Von do for Enablement?

Call scoring

Score the last 20 sales calls against our MEDDPICC framework. Which reps are hitting each element and who's missing discovery?

Onboarding content

Build me a 30/60/90 day onboarding plan for new AEs — include key milestones, training modules, and ramp benchmarks.

Playbook from top performers

Analyze calls and deals of our top 3 reps by win rate. What are they doing differently? Build me a playbook document.

Ramp report

Build me a ramp report for every rep who joined in the last 6 months. Compare them against top performers at the same stage.

Talk track creation

Based on our most successful discovery calls, create a talk track for how to position [product] against [competitor].

Content effectiveness

Which sales collateral and battle cards are being referenced in deals we win vs. lose? What content is actually working?

Scheduled coaching briefs

Create a scheduled command that sends me a coaching brief for each of my reps before their 1:1 every week.

“What Von really gave us back was time. Time we used to spend sifting through Salesforce for nuggets of insight. Now those insights come to us.”
Lindsay Dembinski
Senior Manager, Sales Enablement
Why not just use Claude or ChatGPT?

Von is built specifically for the needs of revenue teams

You already pay for general-purpose AI tools, so you could probably build this yourself. But those tools weren’t built for the specific needs of revenue teams.

Explore Build vs. Buy
Claude / ChatGPT
Von logo lockup
System connections
Each user sets up their own connections. Centralized access requires engineering to build and maintain an MCP server.
Admin connects once. Native, one-click integrations available to the entire org immediately.
Business context
Doesn’t know your fields, fiscal year, or churn definition. You write and maintain skill files for every use case.
Von builds a context graph in days. No skill files. Corrections from any user apply to everyone via org-wide memory.
Context limits
Even with a million-token window, 50 deals and hundreds of calls bury the middle. The model samples and gives you plausible guesses, not the full picture.
Pre-processes all unstructured data. Analyzes 10,000+ calls in a single query. Real answers, not sampled guesses.
Search quality
Limited to keyword search. Questions like “Why are we losing to competitor X?” return shallow answers.
True semantic search across all data. Deep answers on competitive losses, rep performance, and discovery patterns.
Enablement
Making it work for each persona is entirely on RevOps to figure out and maintain.
Von knows what works for every persona across 50+ companies. No training required from your side.
Timeline
3-6 months of engineering. You eventually assign 2-3 engineers full-time. Results uncertain.
Ready for the entire GTM team from day one. Productivity boost within two weeks.

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