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 has outrun code review. Connectory gives every pull request organizational judgment: what the system is supposed to do, what can go wrong, who owns the risk, and whether this change moves the software closer to its purpose.
Not another AI reviewer. The control plane for AI-assisted engineering.
42%
of committed code is already AI-assisted
84%
of developers use or plan to use AI coding tools
97%
of adoption happens before company-wide governance
45%
of AI-generated code contains security vulnerabilities
The gap
A developer sees the diff. No one sees the organization.
The same code can be harmless in a student project and dangerous in an automotive control system, payment workflow, healthcare product, or defense environment. The code may be syntactically perfect. The failure is contextual: it no longer serves what the system and organization are trying to accomplish.
Generic review tools
Review the current diff for syntax, common security issues, style, and localized code quality. Useful, but bounded by what changed in front of them.
Connectory
Reviews the change against system intent, repository purpose, architecture, ownership, conventions, risk classification, dependencies, and enterprise controls.
What Connectory is
The governance intelligence layer for AI-generated code.
Connectory is not a linter, scanner, or model wrapper. It is a system of record for engineering intent. The CTO, architect, or platform team defines what each system exists to do. Connectory cascades that intent down to every repository and every PR.
Intent-aware governance
Review every change against what the system exists to do, what it cannot afford to break, and who owns the consequence.
Cortex organizational memory
Build a living model of repositories, contributors, conventions, dependencies, ownership, and architectural intent.
Fog of War checks
Reveal only the checks that matter for the repo, file path, risk tier, and system classification being changed.
Regulated deployment
Deploy inside AWS, Azure, GCP, VPC, on-prem, or air-gapped environments so source code never leaves the firewall.
Why now
The governance gap did not exist two years ago. AI code generation created it.
AI code has crossed the tipping point
Copilot, Cursor, Claude Code, Codex, and Devin are expanding output faster than human review capacity can scale.
Regulation is moving from theory to enforcement
EU AI Act obligations, state AI laws, cyber insurance requirements, and audit expectations are turning AI governance into infrastructure.
API-wrapper review tools cannot serve regulated teams
Financial services, healthcare, defense, and critical infrastructure teams cannot send source code and organizational context to generic third-party AI reviewers.
How it works
Turn organizational intent into an always-on governance system.
Every review becomes training data. Every correction sharpens the model. After months of use, the system knows your architecture, standards, and risk tolerance better than any generic reviewer starting from scratch.
01
Define system intent
Architects and engineering leaders encode the mission, risk profile, failure boundaries, and standards for each system.
02
Connect every repository
Connectory maps repos, contributors, dependencies, conventions, and cross-system relationships across the organization.
03
Govern every pull request
Sentinel runs parallel security, convention, and architectural-fit review pipelines on every pull request.
04
Learn from corrections
Every accepted suggestion, false positive, and developer correction compounds into customer-specific governance intelligence.
Defensibility
The more you use Connectory, the harder it is to replace.
Each customer instance accumulates institutional knowledge: accepted suggestions, rejected findings, architectural decisions, team conventions, risk boundaries, and contributor patterns. That learning stays with the customer, especially in private and air-gapped deployments.
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.
Why we can win
Built for the buyers ordinary AI review tools cannot serve.
Built by operators who have deployed AI for AWS public sector, Microsoft Healthcare AI, JPMorgan regulatory ML, and regulated enterprise buyers.
Live product reviewing real pull requests across design partners, with weekly feedback loops shaping the product.
Private-cloud and air-gapped architecture designed for customers who cannot use ordinary SaaS code-review tools.
The shift
The boundary between human-written and AI-generated code is disappearing.
The question will not be who wrote the code. It will be whether the code serves the organization. Connectory is building the enterprise standard for answering that question before ungoverned AI code reaches production.