#governance #knowledge-flow #capability-audit #per-project pricing #anthropic-native

the team layer for ai-native engineering.

claudex turns each developer's claude code memory, hooks, mcp servers, and skills into a governed, shared organizational asset — so productivity compounds at the team level, not the seat.

start free see how it works local-first · no memory leaves your laptop without consent
70% of pro devs use ai tools daily stack overflow dev survey 2024
41% of dev time lost to context-rebuilding atlassian dev experience 2024
30pp team-level productivity leakage without shared knowledge mckinsey state of ai 2024
$22B ai-augmented engineering tooling tam (2028) gartner / idc 2025
78% of cios cite ai governance as top concern gartner cio agenda 2025
#01 the problem

individual productivity is up.
team productivity is leaking.

claude code, cursor and copilot deliver 25–55% individual task speed-ups. but at the team level, gains decay to 15–25% without shared knowledge processes.

the leakage lives in private ~/.claude directories — memory, hooks, mcp servers, agent capabilities, hard-won skills — none of it visible to teammates, none of it governed, none of it durable across attrition.

individual lift
55%
team-level lift (today)
22%
leakage
−33pp

mckinsey state of ai 2024 · github research (peng et al.) · atlassian state of dev experience 2024

#02 the product

six surfaces.
one governed control plane.

claudex is a local-first rust cli + a multi-tenant control plane. every feature ships behind the same trust boundary: memory contents never leave a developer's laptop until they explicitly run claudex propose.

#propose-pr

memory becomes a draft pr.

useful local entries are converted into a codeowners-routed draft pr against your repo's .claude/ tree — with a capability diff in the body. nothing auto-merges. nothing auto-writes.

  • github app · gitlab next
  • codeowners-aware
#capability-audit

see every hook, mcp, and agent.

inventory the executable surface across the org — hooks in .claude/settings.json, mcp servers in .mcp.json, agents in .claude/agents/. drift detection. one-click revoke.

  • policy-aware diff
  • incident response
#skills-sync

one skill format, two surfaces.

.claude/skills/ is the source of truth for both claude code (developer) and the agent sdk (server). edit once. both surfaces see it.

  • dual-surface symlink
  • versioned · diff-able
#multi-tenant

schema is the security boundary.

four postgres schemas — core, tenant, audit, analytics. rls everywhere. pgcrypto + supabase vault for at-rest encryption. enterprise-ready by construction, not by patch.

  • row-level isolation
  • append-only audit
#cloud-classification

local-first. cloud when you ask.

rust heuristics handle ~80% of entries with no network call. the remaining 20% can route to a haiku-class agent — opt-in via --cloud. personal entries never reach the cloud, by design.

  • haiku 4.5 default
  • prompt-cached
#managed-mcp

governed knowledge, in claude code.

a read-only managed mcp server distributes governed org knowledge back into every developer's claude code session — never writes locally, never leaks across tenants.

  • read-only by design
  • tenant-scoped
#03 the methodology

capture. classify.
govern. propagate.

a four-step loop. it runs continuously on the developer's laptop, opportunistically in the cloud, and durably across the org.

  1. 01

    capture

    a local rust daemon watches ~/.claude/projects/<dir>/memory/ and picks up new entries the moment they're written. zero config. zero network. opt-out per project.

    rust 1.75+ · directories crate · single static binary
  2. 02

    classify

    heuristics first — four classes (personal, team, project, reference). entries flagged personal never propose, never leave the laptop, never reach the cloud. anything ambiguous can be routed to a haiku-class cloud agent on explicit opt-in.

    ~80% local accuracy · <$0.005/entry cloud cost
  3. 03

    govern

    the control plane builds a live capability inventory across the org — every hook, mcp server, and agent capability is visible, diff-able, and revocable. drift against policy is surfaced before it lands in production.

    rls-isolated · append-only audit · soc 2 type ii (in progress)
  4. 04

    propagate

    approved entries flow back into the team via three surfaces: (a) propose-prs into the repo's .claude/ tree, (b) skills sync visible to claude code & the agent sdk, (c) the read-only managed mcp server. the loop closes.

    zero auto-write · always reviewed · always revocable
#04 use cases

three buyers. three outcomes.

s1

ai-native scale-up

25–250 engineers · 3–10 active repos · series b–d

"our memory is fragmented. each engineer's claude knows a different version of how we ship."

  • compound the 55% individual lift across the team
  • onboard new hires in days, not weeks
  • retain context when senior engineers leave
recommended: pro
s2

regulated mid-market

250–2,000 engineers · fintech · health · gov-tech

"the eu ai act + soc 2 require capability inventory for every ai tool we let touch the codebase."

  • org-wide hook / mcp / agent inventory
  • audit log export, sso/scim, rbac
  • on-prem path · custom dpa · fedramp roadmap
recommended: enterprise
s3

platform engineering

2,000+ engineers · mature idp · multi-team

"we standardize 40 teams. ai tooling is the only surface we haven't put under the platform."

  • backstage plugin · public api
  • multi-tenant org tree
  • policy-as-code for ai capabilities
recommended: enterprise
#05 pricing

per-project pricing.
not per-seat.

we charge for the surface we govern — your repos — not for the people typing. a 50-engineer team buys 3 projects ($99/mo), not 50 seats. inspired by supabase, vercel, render.

hobby

individuals · oss · evaluators

$0 free forever
  • 1 project · ≤5 contributors
  • 100 cloud classifications/mo
  • unlimited local heuristic classification
  • single-repo propose-pr
  • community support
install the cli

team

mid-market eng orgs

$499 / org / month
  • 10 projects included · $40/proj add'l
  • ≤100 contributors per project
  • 10,000 cloud classifications/mo
  • capability audit + drift detection
  • rbac · sso (google / github)
  • priority support <8h
contact sales

enterprise

regulated · platform-eng

from $24k / year
  • unlimited projects · pooled compute
  • multi-tenant org tree · sso/saml + scim
  • audit log export · soc 2 type ii report
  • on-prem helm · custom dpa
  • backstage plugin · public api
  • named csm · 99.9% sla · fedramp path
talk to sales
annual commit: 17% off (two months free) startup program: 50% off pro for 12mo (yc / techstars / a16z) oss program: pro free for repos with ≥5k ★
#06 faq

questions, answered.

why per-project, not per-seat?

per-seat ai tools (copilot, cursor) read as "monitor my developers" to procurement and to the developers themselves. claudex meters on the surface we govern — repos, not heads. a 50-engineer team buys 3 projects ($99/mo), not 50 seats. it lands faster and feels less surveillance-y. fair-use contributor caps prevent monorepo gaming.

does any of my memory ever leave my laptop?

not without an explicit claudex propose or --cloud flag. the rust cli handles ~80% of classification locally. anything labeled personal never proposes and never reaches the cloud — even via override. this is enforced in the schema, not just policy.

which ai tools do you support today?

claude code is first-class; cursor and github copilot enterprise are in compatibility preview. mcp servers and the claude agent sdk are governed natively. multi-vendor capability ingestion for cursor + copilot is on the 2027 roadmap.

can i self-host?

yes — on the enterprise tier. a kubernetes helm chart ships the control plane, postgres, and the managed mcp server in your own cloud. air-gapped license available for fintech, health, and gov-tech. fedramp moderate path is on the q1 2027 roadmap.

how does the propose-pr flow work, exactly?

when you run claudex propose, the cli (1) re-classifies any new entries, (2) drops anything personal, (3) opens a draft pr against your repo's .claude/ tree via the github app, (4) routes it via codeowners, (5) writes a capability diff into the pr body so reviewers see exactly what hooks / mcp servers / agent capabilities are being added or changed. nothing auto-merges.

what about soc 2 / eu ai act / iso 27001?

soc 2 type ii is in progress (target q4 2026). the platform was designed against common criteria 2.0's ai-assisted-access controls from day one. eu ai act article 9 (high-risk) and article 50 (transparency) reporting is built into the audit-log export. iso 27001 is on the 2027 roadmap. enterprise customers receive the soc 2 report under nda.

how is this different from sourcegraph cody / glean / stack overflow for teams?

cody is search-first; glean searches existing docs; so4t is a wiki. none of them are ai-tool-aware — they don't know what a hook, mcp server, skill, or agent capability is. claudex sits in the gap: an ai-tool-native, provider-agnostic governance plane that creates governed knowledge from the artifacts your team is already producing inside claude code.

i'm sold. how do i start?

install the cli with brew install claudex, run claudex init in any repo, and you're in the hobby tier — free forever. for teams: sign up at the start-free link below; you'll be on pro within five minutes, no credit card for the first 30 days.

ready to make your team's ai memory compound?

five minutes to install. zero credit card to start. zero memory leaves your laptop until you say so.

$ brew install claudex && claudex init