Connectory: organizational memory for your whole company, plus PR reviews that use it. Free to start.
Catch risky AI-generated code before it merges. Make sure every change fits how your company actually works.
Every other AI memory lives in the agent. Ours lives in the organization.
Connectory helps your company remember policies, decisions, and ownership across every repository, then checks every pull request against that context. A non-technical leader can read and steer it from a dashboard, with no terminal and no Claude install.
Genie is your company's living policies and decisions (read and steer from a dashboard, no terminal). SlopBuster is the GitHub reviewer that applies them on every pull request. One platform: Connectory.
Your policies and decisions stay with you when you change AI tools or models.
$1.3T
U.S. knowledge-worker turnover cost per year
70-80%
of enterprise knowledge is tacit, never written down
46%
of AI-code failures default to CTO or VP Eng
12%
of enterprises have dedicated AI governance
81%
report rising production failures from AI-generated code
Sources: Deloitte Global Human Capital Trends (2024); Gartner (2024); CloudBees State of Code Abundance (May 2026), survey of 200+ enterprise technology leaders.
The accountability gap
Leadership is accountable. Leadership has no instrument.
We are not selling to the competent coder who already drives Claude across cloned repos. We are selling to the person held accountable for what that coder ships: the CTO, the CEO, the CISO. They do not have time to sit in a terminal and interrogate an agent.
The real question is not "how many PRs merged?" It is: Is this organization still building the right things, the right way, and can I prove it?
46%
of AI-code failures default to CTO or VP Eng
12%
of enterprises have dedicated AI governance
81%
report rising production failures from AI-generated code
DORA dashboards measure delivery health, not comprehension health. Velocity goes up while the team quietly loses the ability to explain its own system. Connectory captures intent as typed beacons and decisions, not only code patterns.
Sources: Deloitte Global Human Capital Trends (2024); Gartner (2024); CloudBees State of Code Abundance (May 2026), survey of 200+ enterprise technology leaders.
What the Genie does for the person in charge
One authority across the entire organization. Not a better autocomplete. The org's brain that also governs the code.
Guide everyone
Hold policies, decisions, objectives, constraints, and regulations in one typed place. Apply them automatically to every change in every repo. Update a policy once; the next review everywhere obeys it.
Hold everyone accountable
Judge each change for appropriateness against those policies. Track per-person and per-AI-agent quality, trajectory, and bus-factor risk across all repos.
Be the thing you talk to
Leaders ask questions in plain language and get answers grounded in the company's real state. No IDE, no terminal, no Claude install required.
Ask the right people
When only a human can close a gap, raise a typed question routed to the person who should answer. Slack delivery integrates with your existing workflows.
Work for compliance
A read-and-steer dashboard plus a continuous, queryable audit trail of decisions and changes for people who will never open a code editor.
Yes, Claude + skills is powerful. We are not asking you to give that up.
Claude Code, Cursor, Codex, and AGENTS.md are the right layer for writing code faster on repos you have open. Connectory sits above it: keep Claude, add the org brain. When you swap models or IDEs next year, the company's memory stays in one server-side graph.
| Layer | Who it serves | What it does |
|---|---|---|
| Coding agents + AGENTS.md / skills | The developer at the desk | Draft, refactor, and explore on repos you have open locally |
| Connectory Genie + SlopBuster | Leaders and everyone accountable for what ships | Remember intent, people, and policies across all repos; govern every PR; dashboard and audit without an IDE |
What local AGENTS.md actually is (and why leadership must see through it)
- Stateless: close the tab, the session forgets
- Per-machine and private: collaborators do not get your memory
- One repo at a time: cross-repo work needs hand-written CONTEXT files
- Goes stale: the file says JWT, the team moved to OAuth months ago
- Files fight: global vs project CLAUDE.md bleed into each other
Three tiers of AI memory. Same ceiling.
We are precise and honest: Augment, MemNexus, and similar graph tools are real competition. They still reconstruct memory from code and sessions, live inside developer tools, and cannot be read or steered by a non-technical human.
| Tier | Examples | What it is | The wall |
|---|---|---|---|
| 1. Static files | AGENTS.md, CLAUDE.md, Cursor rules | Markdown the agent reads at session start | Drifts, per-repo, hand-maintained, confidently wrong when stale |
| 2. Per-account memory | Claude / ChatGPT memory, Cursor memories | Auto-notes the agent writes for itself | Per-machine, per-account, not shared, siloed |
| 3. Knowledge-graph memory | Augment Code, Greptile, MemNexus, Context Cloud | Real graphs, cross-session, MCP-served, some team tiers | Still code/session-derived, IDE-bound, developer-only |
| Connectory Genie | Server-side org ingest, typed intent + people + questions, leader dashboard, PR enforcement | Built for the organization, not the session | |
What Claude remembers vs. what your company remembers
Desk tools help one developer. Connectory is built for the whole organization at pull request time.
| Topic | What desk tools remember (Claude, AGENTS.md, etc.) | What Connectory remembers for your company |
|---|---|---|
| Where the knowledge comes from | What an agent saved, or an index of local code | Server-side ingest of org git, PR, and contributor activity, plus human prose |
| What is stored | Facts, code patterns, conventions (the what) | People, teams, ownership, intent (policies, decisions), and open questions (the why) |
| Who can read and steer it | Developers via IDE, CLI, or MCP client | Any human via dashboard and plain language; machines via PR bot and MCP. Nothing installed to read or steer |
| How up to date it stays | Manual updates or re-index; staleness is the admitted failure mode | Evolves from live activity and curation; a policy change now governs the next review everywhere |
| How much of the org it sees | Per-machine, per-account, per-repo; sees only what is checked out | One server-side graph per org; sees everything; single source of truth |
| What it is for | Make the individual coder faster | Govern the organization: appropriateness, ownership, decisions, onboarding, risk |
One typed graph. Three readers.
The same institutional knowledge serves humans, the PR bot, and coding agents. No duplicate sources of truth.
Leaders
Dashboard in plain language
Org health, appropriateness signals, bus factor, what the company decided and why
SlopBuster (PR bot)
Every pull request
Live rendered institutional context at review time for appropriateness, not only correctness
Coding agents
Advisory MCP (check_idea, check_plan, check_code)
Org-grounded guidance before code ships; tool-agnostic, no graph mutation from advisory tools
War stories
Situations where org memory matters more than another linter pass on an isolated diff.
Cross-repo contract drift
A frontend PR depends on an API contract a backend team changed last week in a different repo. A local agent sees only the cloned frontend. The Genie holds the cross-repo relationship and flags it at review.
Stop reinventing shared libraries
Two teams independently build the same auth helper. The Genie knows your org already provides it in commons-python and the review stops the reinvention before merge.
Preserve the why behind workarounds
An infra workaround required to run on AWS gets deleted by someone who never knew why it existed. The Genie carries the why and the regression is caught.
Onboarding without six pings
A new hire, contractor, or AI agent inherits accumulated context on day one instead of reconstructing it from scattered docs and DMs.
Bus factor of one
The engineer who knows payments goes on leave. Their knowledge is already in the Genie, not only in their head and their laptop's CLAUDE.md.
Policy durability
"We standardized on Pydantic v2" or "Python 3.13 everywhere" is enforced on every future PR in every repo, not re-litigated team by team.
Metrics that lie to leadership
Adoption and lines-of-code charts look great while rework and post-merge defects rise. The Genie surfaces appropriateness and org health, not vanity throughput.
M&A and contractors
Acquired teams and external collaborators do not inherit anyone's AGENTS.md. The Genie is keyed to the org, not the laptop.
Built for the buyers who are stuck
CEO / Founder
The fear: We ship faster than ever, and I have no idea if we are building the right things or what walks out the door when someone leaves.
$1.3T/year in U.S. knowledge-worker turnover cost; 70-80% of enterprise knowledge is tacit (Deloitte, Gartner 2024).
The outcome: A living organizational brain: decisions, ownership, and goals captured as they happen and readable in plain language, no terminal required.
CTO / VP Engineering
The fear: Accountability for AI-code failures lands on me, but I cannot review thousands of agent PRs across dozens of repos myself.
46% of AI-code production failures default to the CTO or VP Eng; only 12% of orgs have dedicated AI governance (CloudBees, May 2026).
The outcome: Every PR judged for appropriateness against live org policy, per-person and per-agent quality signals, and bus-factor alerts across the fleet.
Compliance / CISO
The fear: Regulators want evidence of why AI acted, inside our perimeter. "AI wrote it" is not a defense.
EU AI Act high-risk obligations, 6-month log retention, auditors requiring trails inside your infrastructure.
The outcome: Typed, queryable record of policies, decisions, and evidence. Read and steer from a dashboard with no coding tool installed. SOC 2 Type II; no source code stored.
Objections, answered honestly
"My engineers already have this with Claude + AGENTS.md."
That is per-laptop, per-repo, stateless, and invisible to leadership. It helps the coder write the next line. It does not let you see across the org, enforce a policy everywhere, survive turnover, or produce an audit trail.
"Isn't this just another code reviewer?"
SlopBuster is the visible proof. The Genie is the memory that makes the review know what is appropriate for your org. Reviewers without it judge correctness; the Genie adds appropriateness.
"There are team-memory startups now (MemNexus, Augment)."
They are agent-side and developer-only, fed by coding sessions or code indexing. None is server-side org ingest with intent, ownership, and open questions as typed first-class data, and none is usable by a non-technical leader.
"We will just write better docs / a wiki."
Wikis are static prose that rot the day they are saved and no machine acts on them at review time. The Genie is typed, queried by bots at decision time, and continuously updated.
Built today
- Typed organizational graph: people, teams, projects, sources, beacons, questions, events, relationships
- Autonomous org ingest: contributors, quality, bus factor, human vs AI-agent separation across all repos
- PR review consumes live org context at review time (appropriateness, not only correctness)
- Advisory MCP for coding agents: check_idea, check_plan, check_code
- Read-only org MCP for the Hermes steward
- Read-and-steer dashboard for leaders and compliance
- SlackBot module (OAuth, notifier, teaching, welcome)
- SOC 2 Type II; no source code stored
On the roadmap
We mark these clearly so technical buyers know what is shipping vs planned.
- Propose-and-approve write MCP tools for high-stakes graph changes through human approval
- Fully autonomous delivery from a raised Question to Slack (routing primitive exists today)
- Explicit event-stream canonical store and richer compliance export
SlopBuster is how org memory meets every PR
The Genie is the brain. SlopBuster is the proof: every pull request is checked against live policies, decisions, and cross-repo context. Reviewers without org memory ask "is this correct?" Connectory asks "is this right for this organization?"
Keep Claude. Add the org brain.
Start free. Connect your org. Read and steer institutional memory from a dashboard. Let SlopBuster enforce it on every pull request.