Generic AI reviewers don't know what your repo is. SlopBuster does, and it changes everything about what a good review looks like.
AI is writing your code. Connectory governs what ships.
Code generation is increasing output faster than traditional review can absorb. Connectory helps your team decide whether each pull request is safe, aligned with your architecture, consistent with your standards, and ready to ship.
AI code review that understands your systems, not just the diff.
42%
of committed code is already AI-assisted
84%
of developers use or plan to use AI coding tools
97%
of adoption can happen before governance catches up
45%
of AI-generated code can introduce security vulnerabilities
The gap
Your reviewers need more than the diff.
The same code can be harmless in one repository and risky in a payment workflow, healthcare product, public-sector system, or customer-facing automation path. Your team needs reviews that understand where the code runs, what it touches, and what failure would mean for the business.
Generic review tools
Catch syntax, common security issues, style problems, and localized code quality concerns. Useful, but often missing the customer, system, and risk context around the change.
Connectory
Reviews each change against your system intent, repository purpose, architecture, ownership, conventions, risk classification, dependencies, and enterprise controls.
What Connectory is
A governance layer your developers can actually use.
Connectory is not another linter, scanner, or generic model wrapper. It gives your team a practical way to turn engineering intent into pull request guidance: what each system exists to do, which risks matter, and which standards must be enforced before code ships.
Intent-aware governance
Help reviewers understand whether a change fits the product, the architecture, and the failure modes your team cares about.
Cortex organizational memory
Give every pull request the context senior engineers carry in their heads: ownership, conventions, dependencies, and architectural intent.
Fog of War checks
Reduce review noise by surfacing the checks that matter for the repo, file path, risk tier, and system being changed.
Regulated deployment
Use AI code governance in private-cloud, VPC, on-prem, or air-gapped environments where source code cannot leave your control.
Why now
AI changed the review problem your team has to solve.
AI code is already in the delivery path
Copilot, Cursor, Claude Code, Codex, and Devin help teams ship faster, but they also expand the amount of code reviewers must trust.
Audit expectations are rising
Security, compliance, cyber insurance, and procurement teams increasingly need evidence that AI-assisted changes were reviewed and controlled.
Regulated teams need deployment control
Financial services, healthcare, defense, and critical infrastructure teams often cannot send source code or organizational context to generic SaaS reviewers.
How it works
Turn your engineering standards into always-on PR guidance.
Connectory gives developers feedback at the moment they need it, while giving leaders, architects, and security teams a consistent way to enforce standards across repositories without slowing every review down.
01
Define system intent
Capture what each system is supposed to do, what it must not break, and which standards apply before code reaches production.
02
Connect every repository
Connectory maps repositories, contributors, dependencies, conventions, and cross-system relationships so reviews have real context.
03
Govern every pull request
Every pull request is checked for security, convention drift, architectural fit, and risk before it becomes production debt.
04
Improve from your feedback
Accepted suggestions, false positives, and reviewer corrections teach Connectory how your team wants software reviewed.
What improves over time
Connectory becomes more valuable as it learns how your engineering organization builds.
Every pull request adds context: repository purpose, architectural patterns, ownership boundaries, risk expectations, and the standards your team wants enforced. Over time, reviews become less generic and more aligned with how your organization actually engineers software.
Accuracy compounds
Developer corrections reduce false positives and teach Connectory how the team actually wants software reviewed.
Coverage compounds
More repositories create a richer graph of dependencies, ownership, architectural boundaries, and cross-system risk.
Built for regulated teams
Get AI code review that fits the way your organization has to operate.
Your engineering, security, and compliance teams get review evidence tied to architecture, risk, and system intent instead of generic AI comments.
Your developers get fewer noisy findings and more actionable feedback because Connectory learns from real pull requests and reviewer corrections.
Your deployment team gets private-cloud and air-gapped options for environments where ordinary SaaS code-review tools are not acceptable.
The shift
The boundary between human-written and AI-generated code is disappearing.
Your team still owns what ships. Connectory helps you review AI-assisted code with the same judgment you expect from experienced engineers: system context, architectural fit, security impact, and evidence that the right controls were applied.