Sourcegraph (Amp/Cody AI platform)
Business Profile
Core Value Proposition
Sourcegraph provides an AI-powered software development platform that industrializes software development with AI agents (Amp) to automate code search, analysis, and editing across large codebases.
Target Customer
Engineering teams, software developers, CTOs/VPs of engineering, and IT/DevOps leaders in enterprises
Key Differentiator
Integrated AI agents (Amp/Cody) with deep codebase context, enterprise-grade security (data isolation, zero retention, no model training on customer data), and seamless integration with all code hosts and major editors, plus automated batch changes and code insights in a single UI
Implementation Timeline
Immediate to days depending on use case; some examples show results within minutes (e.g., rapid identification of issues) and fixes within days (Nutanix case). Enterprise deployments suggest value across ongoing development workflows.
Pain Points
- 1Finding and understanding code across large, multi-repo codebases
- 2Automating repetitive code changes at scale while maintaining quality
- 3Gaining actionable insights about code health, migrations, and vulnerabilities
Key Features
- 1Code Search with Deep Search and agentic search
- 2Batch Changes for large-scale automated code edits
- 3Code Insights for visualizing codebase metrics
- 4AI coding assistant capabilities (Cody/Amp) with enterprise-ready security
- 5Seamless integrations with VS Code, Cursor, Windsurf, JetBrains, and CLI; supports all major editors and code hosts
Target Customer Industries
Decision Makers
- 1Principal Engineer
- 2Software Engineer
- 3Staff Developer
- 4Application & Services Section Leader
Client Results
- 1Engineers saving roughly 5-6 hours per week using AI code assistant tools like Cody and writing code 2x faster
- 2Nutanix identified Log4j instances in minutes and implemented a fix within 2 days
- 3Workiva reports Batch Changes saves time, reduces errors, and increases confidence in deployment plans
- 4CERN users can quickly locate code snippets and relevant repositories, enabling self-service code discovery
Competitive Advantages
- 1AI agents tightly integrated with code search and code intelligence
- 2Enterprise-grade security (full data isolation, zero retention, no model training on customer data, detailed audit logs)
- 3Broad editor/IDE and code-host compatibility (VS Code, JetBrains, etc.)
- 4Ability to automate large-scale changes (Batch Changes) and derive insights (Code Insights) in a single platform
Key Benefits
Case Studies & Success Stories
Nutanix case study
Nutanix used Sourcegraph to identify Log4j instances in minutes and implemented a fix within 2 days.
CERN code search efficiency
CERN staff highlighted rapid access to code snippets and repository lists via Code Search, enabling self-served answers and faster problem isolation.
Workiva Batch Changes efficiency
Workiva noted that updating repositories with Batch Changes saves time, reduces errors, and improves confidence in deployment plans.
1Password code discovery automation
James Griffin Allwood, Staff Developer at 1Password, emphasized faster location of code across repos and improved search discovery in practice.
Additional Product Information
Product Description
Sourcegraph is an AI-powered software development platform offering Code Search, Batch Changes, and Code Insights, with AI agents (Cody/Amp) to accelerate coding across large codebases and enterprises.
Target Market
Large and mid-sized software engineering teams, IT organizations, and enterprise development groups seeking scalable AI-assisted development and code intelligence.
Unique Value Proposition
Enterprise-grade, AI-powered code intelligence with secure, scalable automation across multi-repo environments, deep codebase context, and seamless integration with all major editors/code hosts, enabling faster delivery and higher quality code.
Technical Requirements
Supported environments include VS Code, Cursor, Windsurf, and a CLI; integrates with GitHub, GitLab, and Bitbucket; supports major editors; can access latest LLMs; emphasizes data isolation and no model training on customer data.
Pricing Model
Plans include Code Search and Batch Changes; Enterprise Starter plan for teams up to 50 developers with access to powerful code search, AI chat, and multi-repo context; pricing includes Deep Search with a monthly quota (3 free Deep Searches per user per month) starting Oct 15, 2025; ongoing usage-based pricing for additional features
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