Coordination is the
revenue killer nobody tracks.
OpenPing removes overhead so delivery teams handle more projects with less pressure, close decisions faster, and grow business without adding operations headcount.
We lived the problem.
Now we're building the models to fix it.
Rafal Wyderka
CEO / Product
Product leader obsessed with removing coordination overhead from expert work.
- -Lived the problem: coordination collapsed across 5 time zones at Remitly
- -Shipped AI-first products from zero (ppmlx, tview.work)
- -10+ years leading product & delivery at KPMG, MARS, Remitly
Konrad Alfaro
CTO / Engineering
Infrastructure engineer who builds systems that scale to millions of users.
- -Scaled infra at Printify (millions of merchants)
- -Founded 8lines: AI-driven agency shipping real systems
- -Deep expertise in distributed systems, real-time data, and ML pipelines
Serial entrepreneurs. Both from Lodz, Poland. We don't just use AI tools - we build entire products with AI as a co-creator. OpenPing is built the way software will be built: small team, AI-native from day one, shipping 10x faster than legacy approaches.
Coordination is a tax on growth.
Knowledge workers spend more time moving information than executing decisions. Every tool adds a channel. Every channel adds overhead. The bottleneck is always a person.
The real cost isn't ops headcount.
It's the revenue that can't be reached.
The Individual — Lost Upside
Reported ROI on AI tools at org level
Revenue lost to missing delivery capacity
Last time had capacity for new initiatives:
The Organization — Growing Cost
Coordination-to-maker ratio at scale
Increased rotation from coordination burnout
Where team capacity goes:
From noise to decisions and results.
Fully automated.
Listens
Connects to all communication - in real-time.
Understands
Classifies signals with actor and confidence.
Routes
No thread pollution, no group pings.
Surfaces
Escalates only what needs human judgment.
Acts
Acts autonomously.
Every decision makes the system
harder to replace.
Open-source interface gets adoption. Proprietary intelligence layers get built with every customer's data. The moat compounds — it can't be forked.
Proprietary Decision Graph
- •Every decision, commitment, and outcome mapped in a temporal graph unique to each org
- •More data = better predictions. Competitors start from zero
Proactive Signal Layer
- •Captures intent, blockers, and commitments before they're formally stated
- •Per-org classifiers fine-tune continuously. This data doesn't exist anywhere else
Closed-Loop Learning
RESEARCH- •Every human decision feeds training data
- •System improves with usage
- •Outcomes validate predictions automatically
Real-Time Context Engine
BUILT- •All inputs embedded under 80ms
- •Hybrid retrieval, per-org namespace
- •Streaming incremental - no batch reprocessing
Open Data Model
BUILT- •Open schema, full export, no lock-in
- •Customers own data - trust drives adoption
- •Air-gapped deployments supported
Offline-First Mobile
BUILDING- •Native app with on-device inference via ppmlx
- •Personal temporal context graphs
- •CRDT sync for intermittent connectivity
Slack is a copilot.
OpenPing is the autopilot.
Copilots help individuals go faster. Autopilots close decisions, route context, and follow through without human overhead. No product owns the coordination control plane. That's the gap.
Copilot
Slack + AI
Autopilot
OpenPing
Three revenue engines.
Open core. Success-based. Proprietary data.
We don't sell seats. We capture value at every layer - from free adoption to outcomes customers pay to keep.
Adoption engine
- +Open-source workspace interface
- +Community-driven adoption, zero CAC
- +Users own their data
Conversion trigger: teams hit coordination limits
Revenue engine
- +Priced on outcomes
- +Decisions tracked to resolution
- +Pay because it works, not because of a lock-in
- +Compared against headcount, not software
Moat engine
- +Every conversation builds the org context graph
- +Classifiers improve with usage
- +Data compounds into an unforkable moat
- +Differential Privacy deep model training
Services are the new software
AI lets us deliver outcomes directly — not tools for professionals to use. OpenPing replaces coordination labor, not just coordination software.
Path to software margins
Start with high-touch onboarding (services revenue). As the model learns each org, automation increases and margins converge to 70%+ at scale.
Not a SaaS seat. A coordination FTE — or lost revenue.
SaaS seat
$12/mo
Coordination FTE or lost revenue
$180k+/yr
United States
~50k agencies, SW houses, consultancies
Expanding to all professional services
Full coordination headcount budget
ARR at 1% beachhead
ARR at 5% penetration
European Union
~35k agencies across DE, NL, Nordics, UK, PL
Professional services, compliance-driven orgs
EU coordination + data sovereignty premium
Self-hosted open-source model removes data sovereignty objections. GDPR-first architecture is a competitive advantage vs US-only vendors.
Founder / COO / Head of Delivery
50-300 people
~85k agencies globally
US + EU combined
$24k - $150k
vs headcount, not SaaS
Agencies · SW houses
Consultancies · Managed svc
Earn trust with 5 teams.
Then let results compound.
Design Partners (now)
Deploying hands-on with 3-5 agencies. Sitting alongside delivery leads, iterating weekly. Proving coordination saves senior time measurably.
Open-source + community (Q3 2026)
Open-source workspace drives developer adoption. Self-hosted free tier creates awareness. Teams hit the coordination ceiling and convert to paid.
Founder-led sales (Q4 2026)
Design partner results become case studies. Direct outreach to Heads of Delivery and COOs at 50-300 person agencies. Founders close every deal.
Channel partnerships (2027)
Consultancy networks and implementation partners become distribution. Every deployment generates referral signal from adjacent firms.
A new decision layer is forming.
OpenPing is the foundation.
The product that controls context and coordination data for professional services will be infrastructure for how expert work gets delivered at scale.