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Simulate Customers withNative AI Agents

Your data holds the history. Modelmouse predicts the future. We build data-based user AI personas and run simulations to help teams test churn, sentiment, and roadmap decisions automatically.

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app.modelmouse.com/dashboard/delta

Analysis

Q3 Pricing Sensitivity Analysis

Q3 Pricing Sensitivity Analysis

Human survey (n=450) vs AI simulation (n=10,000)

Window: Last 90 days
Prediction Accuracy
91.6%

Validated vs last 6 quarters

Avg. Delta
4.7 pts

Abs gap: human vs AI

Churn Risk
8.9%

Projected next 90 days

Runs This Quarter
312

Across pricing + roadmap tests

Sentiment Distribution
HumanAI
Price SensitivityDelta: +5%
Feature AdoptionDelta: -5%
Support SatisfactionDelta: +5%
New UI FeedbackDelta: +8%
Cohorts

Enterprise Managed

1,260 accounts

4.1%

Low

Growth Mid-Market

2,940 accounts

8.7%

Medium

Legacy Contracts

620 accounts

16.3%

High

Data Record

Connect Snowflake or your data warehouse and import segments, metadata, and user flows directly. Keep records fresh with live updates so your simulations reflect recent activity.

SF
User Record
ID: 0035f00000A1
api_key_***
NameAlex Rivera
IndustryFinTech
RoleCTO
Flows...

Survey Builder

Create surveys by hand or AI generate them. Gather real customer feedback, and map each answer to specific table fields for automatic persistence and later usage. Teams can reuse templates, adjust question types, and ship targeted surveys to customers with the click of a button.

Builder
Q1: Which feature is most critical?
Multi-Select
API Integration
Visual Dashboard
Exports
Q2: How likely are you to recommend us?
Syncs to object: Survey_Response__c

AI Agent Simulation

Build custom AI personas (using your existing AI subscription) from customer profile data and run simulation batches before deploying live campaigns and real features. Compare projected outcomes against human responses to find gaps early, validate assumptions, and align direction before launch.

Agent: "FinTech CTO"v3.5 • Temperature 0.7
Active
Risk Tolerance
Tech Adoption
Predicted Sentiment
"Based on my role, I prioritize API stability over new UI features."
Coming soon

Modelmouse works in any MCP-compliant AI client

Before MCP, every AI app needed its own interface. Use MCP to plug Modelmouse into your existing AI workflow through Claude Code, Cursor, or any other agentic tool.

Example workflow

  1. You ask Claude to check the 'VIP Enterprise' data segment and predict the reaction to new pricing.
  2. Claude sees the run_silicon_sampling tool exposed by Modelmouse.
  3. Claude calls the MCP server, which runs the Python workflow, builds an AI persona against your latest Salesforce data, generates a pricing survey, and runs the simulation.
  4. The server returns results, and Claude responds with your customer sentiment.

Start understanding your customers today

Modelmouse offers you the tools to unlock your user data

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