2. Managers, and HR of
tech and design companies
with innovative teams.
IDEAL CLIENT PROFILE (B2B)
3. • Unresolved spats with know-
it-all teammates or managers.
• Feeling aggrieved by unfair
and rude idea-challenges.
“That s#*t will never work!!”
• You wonder, “why bother
speaking up?”
• Sick of the loudest voice
always winning.
THE PROBLEM – UNFAIR PLAY
4. THE SOLUTION – REFEREE
Employ an AI referee toolkit to help determine unfair
behavior & efficiently resolve team spats, disputes, & conflicts.
Team Buy-in
to the Standard
Team Charter
3-Step
Procedure
App
Spatz AI Data
Analysis of
Team Dynamics
Team
Assisted
Review
Platform
5. How the Spatz Referee
Toolkit Works
Acknowledge
Acceptable Apology
Simple Apology
Minor SPATS…
…DISPUTES…
…CONFLICTS
6. #4(Network) VOTE
#3(Network) STOP
#2(App) OBJECTION
#1(App) CAUTION
#0(Verbal) CAUTION 3012 SPATZ
COMPARITIVE DATA EXAMPLE OF PILOT:
*Illustrative/speculative data for a healthy team of 100 members in 1 week
1 NETWORK 1 Resolved
5 CONFLICTS 4 Resolved
43 DISPUTES 38 Resolved
353 SPATS 310 Resolved
2659 Resolved
SPATZ AI LLM DATA
7. MARKET SIZE (TAM)
• 500,000 tech companies in the USA alone.
• 5 million tech employees.
• TAM at $2 per team member, per month.
• $120 million per year.
8. WHY I AM BACKABLE
• 20 years of research, to be commercial by mid 2024.
• Self-published book in 2012, 760 blog posts, 50 journals.
Rethink Perfect - The upside of uncertainty & the art of moderating our own disputes
• Product designer – industrial designer.
• Tech experience – co-founder of two a successful startups:
• Tripcover.me Insurance AU & NZ, $1M previously in annual sales - 12 years
• Co-founder of Bonzah.com Insurance USA with $1M annual sales - 7 years
9. TRACTION & RESULTS
• MVP consisting of a 3-page messaging webpages.
• The SpatzAI Peer Review Network, website and brand.
• The SpatzAI charter agreement, LLM algorithm.
• Five guiding principles (see Unique Team Psychology).
• The SpatzAI manual and anecdotal testing and feedback.
10. HOW MUCH MONEY
• $50K to $100K
WHAT WE WILL DO WITH IT
• Complete MVP,
• Run a pilot of some 100 participants.
With 50 Spatz AI users and 50 control group.
• Contracting AI data specialist and psych researcher.
• More fully develop the App and network plugin.
11. Contact: Desmond Sherlock
Website: Spatz.ai
Email: des@spatz.ai
Blog: Object123.com
Linkedin: linkedin.com/in/tripcover
Disclaimer: The information contained in this pitch
is speculative and needs to be tested and should only
be used in agreement with all team members.
Thanks for watching
our presentation.
Powering bold idea-sharing
in teams, spat by spat.
Editor's Notes
Welcome
Welcome to SpatzAI
We see our mission to protect team members sharing conflicting views
And are developing a toolkit to self-manage our team spats, disputes, and founder conflict
Welcome
Welcome to SpatzAI
We see our mission to protect team members sharing conflicting views
And are developing a toolkit to self-manage our team spats, disputes, and founder conflict
GUIDANCE
With 9 out of ten startups failing it is pretty obvious that these teams have poor decision-making skills.When founders disagree, we can get defensive, and misconduct will occur on occasion. With little or no recourse to manage our spats, disputes and founder conflict, poor decision-making is inevitable we feel. which causes most startups to fail.
OUR VISION
To increase startup team cohesion and interaction (psychological safety) by creating a toolkit to self-manage and monitor our spats, disputes and founder conflict.
Did you know that some 65% of startup teams fail due to founder conflict
According to Harvard Professor Noam Wasserman, author of: THE FOUNDER’S DILEMMAS
GUIDANCE
With 9 out of ten startups failing it is pretty obvious that these teams have poor decision-making skills.When founders disagree, we can get defensive, and misconduct will occur on occasion. With little or no recourse to manage our spats, disputes and founder conflict, poor decision-making is inevitable we feel. which causes most startups to fail.
Our toolkit consists of: - The Spatz Intervention Agreement- The Spatz 3-step App- The Spatz Peer Review Network and- The SpatzAI Data collection for Machine Learning
How the Spatz App and intervention worksthe team simply agrees to use a 3-step Objection intervention for any minor infractions that makes usfeel uncomfortable, offended or threatened.
And using the corresponding 3-levels of accountability; acknowledge, apologize, or an acceptable apology to resolve our, spats, disputes or conflicts.
The Spatz A.I & Machine Learning Data
The data from Pablo and Lucia’s Spat, Dispute and Conflict has been automatically collated and parsed, along with millions of others, so that the Spatz A. I. can continue machine learning from the data.
By comparing a team's performance, with their Spats data, allows investors and organizations to more accurately predict a team’s future success.
Our toolkit consists of: - The Spatz Intervention Agreement- The Spatz 3-step App- The Spatz Peer Review Network and- The SpatzAI Data collection for Machine Learning
Our toolkit consists of: - The Spatz Intervention Agreement- The Spatz 3-step App- The Spatz Peer Review Network and- The SpatzAI Data collection for Machine Learning
Our toolkit consists of: - The Spatz Intervention Agreement- The Spatz 3-step App- The Spatz Peer Review Network and- The SpatzAI Data collection for Machine Learning
Our toolkit consists of: - The Spatz Intervention Agreement- The Spatz 3-step App- The Spatz Peer Review Network and- The SpatzAI Data collection for Machine Learning
Our toolkit consists of: - The Spatz Intervention Agreement- The Spatz 3-step App- The Spatz Peer Review Network and- The SpatzAI Data collection for Machine Learning
Our toolkit consists of: - The Spatz Intervention Agreement- The Spatz 3-step App- The Spatz Peer Review Network and- The SpatzAI Data collection for Machine Learning
Our toolkit consists of: - The Spatz Intervention Agreement- The Spatz 3-step App- The Spatz Peer Review Network and- The SpatzAI Data collection for Machine Learning