Transform any company website into AI-powered GTM intelligence, messaging, and outreach assets through a fully automated no-code workflow.
LaunchPilot AI is an AI-powered GTM Operations Copilot that transforms a company's website into actionable go-to-market intelligence.
The project uses Clay AI to enrich company information, generate GTM strategies, create executive summaries, and automatically publish the results into Google Sheets. A transformation layer cleans and structures the AI output before serving it to an interactive Retool dashboard.
The objective was to demonstrate a modern GTM Engineering workflow using primarily no-code tools while maintaining a clean, scalable data architecture.
| Resource | Link |
|---|---|
| 🚀 Retool Dashboard | https://gemmmohil.retool.com/embedded/public/e3f5f67a-b7c5-4884-bac2-17ee3640352a/page1 |
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🤖 Built an AI-powered GTM Operations Copilot using Clay, Google Sheets, and Retool
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🔗 Automated the workflow from company website → AI insights → dashboard
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🧹 Designed a three-layer data architecture (Raw → Transformation → Dashboard)
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📊 Created an interactive internal GTM dashboard with dynamic company selection
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🧠 Generated AI-powered GTM strategies, messaging, outreach assets, and executive summaries
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🚫 Built without a custom backend using primarily no-code tools
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⚡ Reduced GTM research from ~45 minutes to under 2 minutes
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🤖 Automated company intelligence generation
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🎯 Generated a complete GTM strategy from a single website
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📊 Built an interactive GTM Operations dashboard
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🔄 Created a maintainable multi-layer data architecture
| Layer | Technology |
|---|---|
| AI Workflow | Clay |
| Data Storage | Google Sheets |
| Data Transformation | Google Sheets Formulas |
| Dashboard | Retool |
| Documentation | GitHub |
LaunchPilot AI follows a layered architecture that separates AI enrichment, data transformation, and presentation. This ensures that raw AI outputs remain untouched while the dashboard always consumes clean, presentation-ready data.
The project automates the complete GTM research workflow from a single company website.
The user provides only the company website. Example:
https://clay.com
Clay analyzes the website and generates:
- Company Overview
- Industry
- Target Customers
- Products & Services
- Value Proposition
- Competitors
- GTM Motion
- Website Summary
Using the company intelligence, Clay generates:
- Ideal Customer Profile (ICP)
- Buyer Persona
- Pain Points
- Positioning
- Messaging Framework
- Sales Channels
- GTM Tech Stack
- GTM Score
- Current Stage
- Primary KPI
- 30-Day Action Plan
- GTM Risks
- Cold Email
- LinkedIn Outreach
Clay combines all generated insights into a concise executive summary.
Instead of consuming raw AI output directly, the project introduces a transformation layer that:
- Cleans formatting
- Standardizes bullet lists
- Creates helper fields
- Separates raw and presentation-ready data
- Preserves the original AI output
The dashboard allows users to:
- Select a company
- Review GTM health
- Explore AI-generated strategy
- Access messaging assets
- Export insights for execution
| Company Intelligence | GTM Strategy |
|---|---|
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| Executive Summary | Final Clay Output |
|---|---|
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Generate comprehensive company insights from a single website URL, including:
- Company Overview
- Industry Classification
- Target Customers
- Products & Services
- Value Proposition
- Competitor Identification
- GTM Motion Analysis
Automatically create a complete go-to-market strategy:
- Ideal Customer Profile (ICP)
- Buyer Persona
- Pain Points
- Positioning Strategy
- Messaging Framework
- Recommended Sales Channels
- Recommended GTM Tech Stack
- GTM Maturity Score
- Current GTM Stage
- Primary KPI
- GTM Risk Assessment
Generate ready-to-use outreach content:
- Personalized Cold Email
- LinkedIn Outreach Message
- Discovery Questions
- Objection Handling
- 30-Day GTM Action Plan
Explore every company through a dynamic Retool dashboard featuring:
- Company Selector
- GTM Health Overview
- Executive Summary
- Strategy Breakdown
- Messaging Assets
- Action Plan
- Outreach Content
Instead of consuming AI output directly, LaunchPilot AI introduces a dedicated transformation layer that:
- Preserves raw AI output
- Cleans formatting
- Standardizes generated content
- Creates helper fields
- Produces dashboard-ready data
Several architectural decisions were made to improve maintainability, scalability, and data integrity.
Rather than splitting workflows across multiple Clay tables, the project uses a single master table to simplify orchestration and reduce maintenance.
Raw AI output is never edited directly. Instead, Google Sheets acts as a lightweight transformation layer that:
- Cleans generated content
- Standardizes formatting
- Creates helper columns
- Separates source data from presentation data
The dashboard was initially evaluated in Looker Studio.
While suitable for analytical dashboards, the project primarily displays AI-generated strategic text and outreach assets rather than charts and metrics.
Retool was selected because it provides a significantly better experience for building interactive internal GTM applications with rich text, dynamic filters, and reusable UI components.
The project intentionally avoids custom backend services to demonstrate that sophisticated GTM workflows can be built rapidly using modern no-code tooling.
Building LaunchPilot AI involved solving several practical GTM engineering challenges while keeping the solution entirely no-code.
Large Language Models generate rich text that isn't always presentation-ready.
A dedicated Google Sheets transformation layer was introduced to:
- Standardize formatting
- Clean bullet points
- Create helper columns
- Preserve the original AI output
Directly editing AI output would make the workflow difficult to maintain.
The project follows a three-layer spreadsheet architecture:
Raw_AI_Output
│
▼
Transformation
│
▼
Dashboard_Data
This separation keeps the data pipeline maintainable and allows presentation logic to evolve independently.
Multiple dashboard solutions were evaluated during development.
| Platform | Outcome |
|---|---|
| Looker Studio | Good for analytical dashboards but limited for rich AI-generated text and interactive GTM workflows. |
| Retool | Selected due to better support for dynamic UI components, rich text rendering, filters, and internal tool development. |
This evaluation reinforced an important engineering principle:
Choose the tool that best fits the problem rather than forcing the problem to fit the tool.
The initial public deployment exposed authentication constraints with the Google Sheets OAuth resource.
The Retool resource configuration was updated to allow the published dashboard to access the data correctly while preserving the automated Google Sheets workflow.
Throughout this project I strengthened practical skills in:
- GTM Engineering workflows
- Clay AI automation
- Prompt engineering
- Data transformation
- Dashboard design
- No-code system architecture
- Internal tool development
- AI workflow orchestration
Mohil Wankar Aspiring GTM Engineer | Data Analyst | AI Builder
- GitHub: https://github.com/Mohil-Wankar
- LinkedIn: https://linkedin.com/in/mohil-wankar/
If you found this project interesting, feel free to connect or reach out.