Probe gives agencies the leverage to deliver like an internal team — with the flexibility clients hired you for.
Free and open source. Business and Enterprise plans available.
Your engineers get answers about architecture, patterns, and ownership in seconds, not days. No waiting on Slack responses.
Every engineer works against the same quality bar. AI-powered code review enforces the client's actual standards.
Know the dependencies, the patterns, and the gotchas before you touch a line. Fewer bugs. Faster reviews.
New team members get the same depth of understanding as your veterans, from day one. Say yes to expansion.
And trust erodes every time your team needs to ask "where is this implemented?" or "why was this built this way?"
New client signs. Engineers clone repos and hit walls. Architecture isn't documented. Questions pile up in Slack. Days pass billing hours, not shipping code. The client starts wondering if they made the right choice.
Your senior engineer who "gets" the codebase goes on vacation. The replacement follows different patterns. Small inconsistencies compound. Six months later, the client blames "agency code quality."
Client wants to double the team. Your current engineers are the only ones who understand the system. Onboarding new people means pulling productive engineers into endless knowledge transfer. You grow headcount but not output.
Real prompts from delivery teams. Questions, investigations, and automations — across client codebases.
Ask any question about any codebase and get accurate, contextual answers in seconds.
The system reads code semantically — understanding functions, classes, dependencies, and call graphs — not just doing text search. It pulls context from linked Jira tickets, Confluence docs, and historical PRs to give you the full picture.
Every PR reviewed against the client's actual standards — automatically, consistently, thoroughly.
Generic AI code review tools don't know your client's conventions. They don't understand that this client cares deeply about error handling patterns, or that the team prefers composition over inheritance, or that touching the billing service requires extra scrutiny.
Probe learns each client's standards and applies them to every PR. It checks for security issues, performance problems, architectural violations, and cross-service dependencies. It explains why something is flagged, not just that it is.
Work across an entire system of services, not just isolated repositories.
Real enterprise systems aren't single repos. They're dozens of services with complex dependencies, shared libraries, and cross-cutting concerns. A change in one service can break three others. Traditional tools can't see this.
Probe maps the entire system. It understands which services depend on what, how data flows between them, and what happens when you change something. When a client asks you to modify an API, you'll know every consumer that needs to be updated.
Pre-built automation workflows you can deploy immediately. Customize per client. Version like code. Improve over time.
Connect to client repos and automatically generate system architecture documentation, ownership maps, and local development guides. Your engineers understand the system before writing a line of code.
Automated code review against client-specific standards. Catches security issues, architectural violations, and cross-service breaking changes before human review. Reduces review cycles from days to hours.
When engineers rotate between projects or new team members join, automatically generate personalized onboarding based on what they need to know. No more pulling senior engineers into endless briefings.
When clients want to grow the engagement, spin up new capacity without proportionally increasing chaos. New engineers get the same depth of understanding as your veterans, from day one.
Runs entirely inside client infrastructure. Code never leaves their environment. Full data sovereignty and compliance compatibility.
Use the client's preferred model — Claude, GPT, open-source, or self-hosted. No vendor lock-in. Switch providers without changing workflows.
OpenTelemetry instrumentation captures every query, every workflow run, every decision. Complete traceability for compliance and debugging.
The core engine is open source and auditable. Clients can inspect exactly how their code is being processed. No black boxes.
Start with the open-source core to evaluate the technology, then scale to enterprise when you need multi-project capabilities.
Free forever
The core code intelligence engine. Perfect for evaluating the technology on a single project or for individual engineers exploring a codebase.
Contact for pricing
Everything in Open Source, plus multi-project architecture support, workflow automation, and integrations with your existing tools.
We recommend a two-phase approach: first, validate the core technology with open source on a single project, then pilot the enterprise features on a real client engagement.
Pick any of these and have something running before your next meeting. No account required.
Get enterprise-grade code understanding in Claude Code, Cursor, or any MCP-compatible tool. Auto-detects auth, works with any LLM API. One command to install.
Add a GitHub Action for automated code review. Every PR gets a first-pass review for security, performance, and quality with inline comments. Fully customizable per client.
Create a Slack bot that answers questions about your codebase. Your team can ask questions in Slack and get intelligent answers grounded in actual code — no context switching.
Once you've validated the core technology, run a pilot on a real client engagement to test the full enterprise workflow: multi-repo understanding, automated code reviews, and integrations.
Choose an engagement where you have multiple repositories, existing Jira/ticket systems, and ideally where onboarding or quality has been challenging.
We'll work with your team to map the system architecture, configure cross-repo dependencies, and set up integrations with Jira/Zendesk.
Define client-specific quality standards, security requirements, and patterns. These rules live with the project and evolve over time.
Track time-to-first-PR for new team members, questions asked to client team, and PR review cycles. Compare to previous engagements.
Want to discuss how a pilot would work for your team?
Schedule a Technical DiscussionCopilot and ChatGPT work with whatever code is in front of them. They don't understand your client's architecture, conventions, or the relationships between services. They can't tell you that changing this function will break three other services, or that this pattern violates the team's coding standards.
Probe understands the entire system — across all repositories, integrated with Jira and Confluence, aware of historical decisions. It's the difference between asking someone who just read the file versus someone who built the system.
Yes, and this is where it shines. Legacy systems are exactly where context is hardest to get — documentation is outdated, original authors are gone, patterns are inconsistent. Probe builds understanding from the code itself, not from documentation that may or may not exist.
Each client gets their own configuration. Code review rules, quality standards, workflow automations — all customized per client and versioned like code. When a client's preferences change, you update the config and the entire system adapts.
Basic setup takes hours, not weeks. Connect your repos, configure initial rules, start using it. The system learns and improves over time, but you get value immediately. Most agencies start with one client engagement as a pilot, then roll out across their portfolio.
Let's talk about how Probe can transform your client engagements. We'll show you how it works on a real codebase — yours or one of your clients' — and discuss how to structure a pilot.