// Solution 05
CtxMeet

1-on-1 peering and business meeting scheduler built for how NOG events actually work. AI-powered matching, single profile across all events, table-based room assignment — no more Excel files flying around the day before.

Free for all NOG operators.  Always.
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ctxmeet — bash — 80×24
ctx@prod:~$ ctxmeet schedule --event=mynog-2027

■ Meeting Scheduler — MyNOG 2027
Participants: 142 registered
Meetings: 86 confirmed
Tables: A1–A12 assigned
AI matches: 34 AI-suggested matches
Slot Length: 20 min each

ctx@prod:~$ ctxmeet export --format=ical
✓ 142 calendar files generated
✓ PeeringDB: 89 networks matched
✓ LLM: 34 additional matches suggested

ctx@prod:~$ █
// Features

Meeting scheduling that
actually works

🤝
Self-Service Meeting Requests
Participants browse the attendee list and send meeting requests directly. Accept, decline, or propose an alternative slot. No intermediary, no email chains, no organiser bottleneck.
🏷️
Automatic Table Assignment
CtxMeet assigns meeting tables automatically based on confirmed meetings and available slots. Room layout is configurable. Live meeting status board visible to all participants and staff.
📊
PeeringDB Integration
Network profiles pulled directly from PeeringDB. Peering eligibility, IX memberships, and policy information shown on participant profiles. Makes meeting requests more informed and targeted.
📅
iCal + CSV Export
Every participant gets a personalised iCal file with their confirmed meeting schedule. CSV export for event organisers. Meeting room assignments included. Import directly into your calendar.
🔗
CtxRego Integration
When combined with CtxRego, the full participant profile — including network information, infrastructure details, and preferences — flows automatically into CtxMeet. No duplicate data entry.
🌍
API-Integrable
CtxMeet exposes a full REST API. NOGs with their own websites or apps can integrate the meeting scheduler directly, displaying schedules and managing requests through their own interfaces.
// AI Matching Engine

Smart matching trained on
data since 2008

CtxMeet's matching engine is trained on IT-specific event data, NOG community patterns, and commercial conference data going back to 2008. It understands the peering and routing world — not just generic business matching.

Infrastructure Analysis Matching
ASN and prefix count matching
Shared IX membership detection
Peering policy compatibility analysis
Transit provider overlap identification
Geographic routing path analysis
Profile Preference Matching
Matching preferences set in your profile
Industry segment targeting
Meeting type preference (peering, BD, technical)
Previous event interaction history
Community role and expertise matching

// Trained on NOG events data since 2008 · IT-specific, not generic business matching · All inference runs locally

// Single Profile

One profile,
every event

Your CtxMeet profile follows you across all events on the platform. Your ASN data, PeeringDB link, bio, meeting preferences, and interaction history carry over automatically. Set it once, use it everywhere.

Profile Fields
Full NameCarried across all events
ASNAuto-linked to PeeringDB
OrganisationSyncs from CtxRego if connected
IX MembershipsPulled from PeeringDB
Meeting TypePeering / BD / Technical / Any
PreferencesWho you want to meet, what topics
Cross-Event History
Past meetingsHistory preserved across events
Match qualityImproves with each event
Interaction dataUsed to refine AI recommendations
NOG eventsDKNOG, DENOG, NANOG, RIPE, and more
PrivacyYou control what's visible to others
// Infrastruktur · Network Intelligence

Matching based on real BGP topology

CtxMeet's matching engine isn't fed survey data — it's fed actual routing topology. Live BGP data, PeeringDB policies, RIPE Atlas latency measurements, and AS relationship graphs. When CtxMeet suggests a meeting, it's because the network data says there's a real conversation to have.

📡
Live BGP Topology via RIPEstat
Every participant's ASN is mapped against live BGP data from RIPEstat. Prefix counts, AS path length, transit relationships, and announcing regions — all factored into matching relevance scores automatically.
// RIPEstat BGP · Updated daily
🔗
PeeringDB Live Policy Matching
Shared IXP memberships and peering policy compatibility pulled live from PeeringDB. Open peering policy? CtxMeet flags it. Same IX but no existing session? High-priority match suggestion with full policy context shown.
Shared IXPs · Policy type · Contact details
🌍
RIPE Atlas RTT Matrix
Round-trip times between participant networks measured via RIPE Atlas anchors. Two networks with high latency between regions despite shared IXP membership? CtxMeet surfaces this as a priority peering conversation.
// Atlas anchors · RTT heatmap per event
🔀
AS Relationship Analysis
Provider/customer/peer relationships inferred from BGP data. CtxMeet knows if two participants are already in a transit relationship — and can filter out or specifically surface those meetings depending on event type.
Provider–customer · Sibling ASNs · IX peers
// The moat

Generic meeting schedulers like Brella or Grip use questionnaire-based matching. CtxMeet uses actual network topology. The only way to replicate this is to build deep integrations with PeeringDB, RIPEstat, and RIPE Atlas — and understand what the data means in a peering context. That's the moat.

// Competitive Positioning

Why NOG operators choose CtxMeet over generic schedulers

Feature CtxMeet Brella / Grip Manual (Excel)
BGP / PeeringDB topology matching ✓ Questionnaire only —
RIPE Atlas latency-based prioritisation ✓ — —
Free for all NOG operators Always free $3,000–$15,000/event Free
Single persistent profile across NOG events ✓ Per-event only —
Self-hosted · You own all data ✓ SaaS only Local
// Join Waitlist

Better meetings
at every NOG

CtxMeet is in development. Join the waitlist to get early access for your event — and tell us which NOG you run so we can prioritise the right integrations.

Join Waitlist ↗ CtxRego Integration →

// Free for all NOG operators · API-integrable · Couples with CtxRego