Sourcegraph is the code understanding layer for enterprises. It gives developers and AI agents instant context and control across every repo, branch, and language-succeeding where other tools break under scale and complexity.
Enterprise codebases are massive, fragmented, and hard to navigate. Developers waste time chasing context instead of building, while AI tools fail on real-world code and internal DIY systems crumble under scale and compliance. The result is slower shipping and stalled AI adoption.
Accelerate developer and agent flow.
Give developers and agents instant access to the right code and context so work happens faster and friction-free.
Ship with confidence.
Ensure every human and AI-driven change is accurate, compliant, and consistent across the org.
Built for the largest, most complex codebases.
Account for every code host, language, monolith, service, and framework: keep performance at enterprise scale.
Access real-time vendor security and compliance information through their Trust Center powered by Drata or Vanta. Review certifications and security standards before purchase.
AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.
Pricing is based on the duration and terms of your contract with the vendor. This entitles you to a specified quantity of use for the contract duration. If you choose not to renew or replace your contract before it ends, access to these entitlements will expire.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
This contract-based listing has two pricing dimensions. You pay per Sourcegraph User, so cost scales with the number of people using the platform. Each user includes credits for AI features, which pool across your organization. The Deep Search Credits dimension is a usage add-on. You buy these credits when your AI Deep Search needs exceed the amount included with your users. Together, the two dimensions let you size the base user count and adjust AI usage capacity independently.
Top-of-mind questions for buyers
What counts as one Sourcegraph User for billing purposes?
A Sourcegraph User is one person with access to the platform. You pay for each user you provision. Every user includes a set of credits for AI features, and those credits pool across your whole organization rather than staying locked to one person.
What happens if my AI Deep Search usage exceeds the credits included with my users?
Each user comes with credits that pool org-wide. When your team uses more than the pooled amount, you buy Deep Search Credits as an add-on. These credits do not expire monthly and roll over on renewal, so unused capacity carries forward.
Which dimension drives most of my cost — users or Deep Search Credits?
The Sourcegraph Users dimension usually drives the base cost, since it scales with team size and includes bundled AI credits. Deep Search Credits add cost only when AI usage exceeds pooled credits. Both bill independently and appear on the same invoice.
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Supports analysis and navigation across multiple programming languages within enterprise codebases.
Multi-Repository Management
Handles code understanding and indexing across multiple repositories, code hosts, and branching structures simultaneously.
Enterprise-Scale Performance
Maintains performance and functionality across large, complex, fragmented codebases including monoliths, microservices, and various frameworks.
Code Context and Search
Provides instant access to code context, dependencies, and search capabilities across the entire codebase for developers and AI agents.
Compliance and Change Validation
Ensures accuracy, compliance, and consistency of code changes across the organization for both human and AI-driven modifications.
Multi-Agent Code Review Automation
Specialized agents run across pull requests to write descriptions, flag issues with remediations, and enforce governance and security standards across GitHub, GitLab, Bitbucket, and Azure DevOps.
Cross-Repository Codebase Context
Code review analysis leverages full cross-repository codebase context to identify breaking changes, dependency conflicts, architecture-level issues, and hidden risks.
Centralized Rules Engine
Centralized system to define and enforce organizational standards including security policies, coding standards, architectural conventions, and compliance requirements consistently across all pull requests.
IDE and Git Integration
Agents operate across integrated development environments and Git platforms with shared cross-repository context to deliver precise code reviews.
Configurable Review Agents
Specialized review agents can be configured with shared context to enforce code quality rules and execute specific review tasks using integrated tools.
Source Code Management
Powerful branching tools and code management capabilities for creating and managing code repositories
CI/CD Pipeline
Advanced continuous integration and continuous deployment with automatic testing, reporting, and release controls
Enterprise Agile Planning
Project planning tools with analytics and insights into team productivity for multi-team usage and scaling organizations
Package Management
Built-in universal package management for creating software supply chains with strict quality standards
AI-Powered Development Assistance
GitLab Duo integration providing code completion, code generation, code explanation, and developer experience enhancements throughout the software development lifecycle
Using an AI assistant has streamlined code discovery and has accelerated my development work
Reviewed on Nov 06, 2026
Review from a verified AWS customer
What is our primary use case?
I worked with Sourcegraph only through the AI code assistant AMP, and I haven't used other products from Sourcegraph.
I did use Cody as well, in addition to AMP.
I used Cody integrated in IntelliJ IDEA, so I was using it as a chat, typing in a chat box. With AMP, it was more terminal-based, as far as I remember, but I wasn't using a specific code search feature.
What is most valuable?
Overall, Sourcegraph did save me time in my development process due to its capabilities in streamlined code discovery. It helped with discovering what's already in the codebase, accelerating development, reviewing afterwards, and producing results. I found I gained more value from both products as I got more experience with prompting.
The integration with Sourcegraph did help my development workflow. I had a fun experience developing with both AMP and Cody during last year in my previous job. I should mention that I hadn't used assistants before that, probably only GitHub Copilot in December 2024. Roughly, I've been consistently using an assistant only since last year. I started with Cody for roughly half a year, then switched to AMP in the middle of summer, so I basically transitioned from no assistant to using an assistant via these two products last year.
What needs improvement?
I did face some issues with Sourcegraph, such as making a lot of patches and upgrades very quickly. I was surprised in summer when they deprecated Cody, prompting me to switch to AMP, but I adapted. I think a few months later, they informed me I should update because they had a nice UI on the latest version of AMP. I was a little behind with updating it, so I had to ask them for instructions at some point, but I would say that is rather minor compared to the experience of using the assistant, especially considering I was using no assistant in 2024.
The interface of Sourcegraph was a bit unusual as it was more terminal-based, especially for AMP. Although it didn't stop me from working, I did find that sometimes the terminal-based UI would post sayings from people who used AI, and they were sometimes truncated, which made it difficult to read the full sentences. This is more of a nitpick, as in the grand scheme of things, my overall experience with it was positive.
For how long have I used the solution?
I am currently working with Sourcegraph, as I installed AMP, an agentic assistant, last year for a few months. I used AMP, which is from Sourcegraph.
I used Sourcegraph's AMP in 2025 and stopped using it in the spring of this year because I changed jobs and have different requirements. We use different assistants in the new job.
How are customer service and support?
I did contact Sourcegraph's technical support, and I remember interacting with one of the support members who gave me instructions on what to do. I don't remember all the details, but at that point, I managed to move past the issue. I didn't have a specific problem with it, but I needed to figure out a few steps to properly update it, which is why I reached out in the first place.
What's my experience with pricing, setup cost, and licensing?
Cody came via a plugin in IntelliJ, and AMP was also in IntelliJ but more terminal-based. I recall running out of credits and purchasing $20 worth of more credits. The other options were a bit more restrictive, while Sourcegraph's approach was flexible, allowing me to pay as I needed more.
What other advice do I have?
My recommendation to others reading reviews on PeerSpot is to note that switching from no assistant to having one was a big change for me. It wasn't straightforward, as I had to learn proper workflows for code review, but the switch to AMP was beneficial.
I would rate my experience with Sourcegraph around an 8 or 9 out of 10 overall. It was pretty good for that year. I'm using Copilot now, but it's a different year, and models have evolved, making it hard to compare.
For that year, I would give Sourcegraph a nine. I'd take one point off because I felt it was about communication; they were releasing many things, and I felt outdated quickly.