Commission-Based Sales for Proprietary Technology. Deal Target USD 500K. 30% Sales commission
Budget: $30 – $250 USD
I’m reaching out to explore a potential commission-based sales or licensing partnership for a proprietary technology I’ve developed in the area of extreme-event discovery within high-dimensional combinatorial systems.
What I’ve built (context)
I have created a constrained-search discovery engine that compresses massive combinatorial spaces to surface rare, high-impact outcomes that are effectively unreachable through brute-force enumeration.
While lottery data was used as a verifiable benchmark domain, the system itself is not a prediction model and does not rely on randomness or guarantees. Instead, it identifies structural manifolds formed by historical co-occurrence, spacing, and density constraints, enabling efficient discovery of extreme outcomes.
Validation & proof (key credibility)
The engine has been rigorously validated with full reproducibility and bias-corrected scaling:
Progressive scaling: 15k → 30k → 100k → 200k candidates
Early-stop bias identified and eliminated (superset-safe sampling)
Monotonic performance verified
At the 200k scale (full-year backtest):
215 verified 4-match-plus-bonus outcomes
3 verified five-match (5W) outcomes
1 verified five-match + bonus (jackpot-level) outcome
The jackpot-level outcome was surfaced without brute force, without relaxing constraints, and without any look-ahead, indicating genuine structural signal inside the learned search manifold.
What I am offering (commercial options)
I am open to three commercialization paths, depending on buyer profile and deal structure:
1️⃣ One-time lump-sum sale (outright acquisition)
Full transfer of the technology (terms negotiable)
Suitable for firms seeking exclusive ownership
Clean exit model
2️⃣ B2B licensing (non-exclusive or limited exclusive)
Annual or multi-year licenses
Private analytics use, research, or syndicate deployment
No source code disclosure required
3️⃣ Black-box SaaS access
Controlled API or dashboard access
Output-limited, parameter-restricted
Designed for scalability and legal safety
No algorithm exposure
I am not offering open-source access or public prediction claims.
What I’m looking for
I am seeking experienced, commission-based partners who can:
Introduce qualified B2B buyers
Structure licensing or acquisition deals
Sell high-ticket analytics or IP-driven technology
Operate under NDA with disciplined positioning
Ideal backgrounds include IP brokerage, enterprise software sales, analytics licensing, or technology commercialization.
Commercial structure (flexible)
I am open to standard industry models, including:
20–30% commission on closed deals
Tiered commission for repeat sales
Optional regional or vertical exclusivity
All terms would be documented under NDA and a simple commission agreement.
Proof & next steps
I have a concise proof pack (10–12 slides) documenting:
The problem and market gap
Why brute-force approaches fail
The constrained-search architecture
Scaling curves and bias correction
Reproducibility
Verified jackpot-level discovery
Legal and commercial positioning
If this opportunity aligns with your experience, I’d be glad to:
Share the proof pack
Walk through the results
Discuss whether a partnership makes sense
What I’ve built (context)
I have created a constrained-search discovery engine that compresses massive combinatorial spaces to surface rare, high-impact outcomes that are effectively unreachable through brute-force enumeration.
While lottery data was used as a verifiable benchmark domain, the system itself is not a prediction model and does not rely on randomness or guarantees. Instead, it identifies structural manifolds formed by historical co-occurrence, spacing, and density constraints, enabling efficient discovery of extreme outcomes.
Validation & proof (key credibility)
The engine has been rigorously validated with full reproducibility and bias-corrected scaling:
Progressive scaling: 15k → 30k → 100k → 200k candidates
Early-stop bias identified and eliminated (superset-safe sampling)
Monotonic performance verified
At the 200k scale (full-year backtest):
215 verified 4-match-plus-bonus outcomes
3 verified five-match (5W) outcomes
1 verified five-match + bonus (jackpot-level) outcome
The jackpot-level outcome was surfaced without brute force, without relaxing constraints, and without any look-ahead, indicating genuine structural signal inside the learned search manifold.
What I am offering (commercial options)
I am open to three commercialization paths, depending on buyer profile and deal structure:
1️⃣ One-time lump-sum sale (outright acquisition)
Full transfer of the technology (terms negotiable)
Suitable for firms seeking exclusive ownership
Clean exit model
2️⃣ B2B licensing (non-exclusive or limited exclusive)
Annual or multi-year licenses
Private analytics use, research, or syndicate deployment
No source code disclosure required
3️⃣ Black-box SaaS access
Controlled API or dashboard access
Output-limited, parameter-restricted
Designed for scalability and legal safety
No algorithm exposure
I am not offering open-source access or public prediction claims.
What I’m looking for
I am seeking experienced, commission-based partners who can:
Introduce qualified B2B buyers
Structure licensing or acquisition deals
Sell high-ticket analytics or IP-driven technology
Operate under NDA with disciplined positioning
Ideal backgrounds include IP brokerage, enterprise software sales, analytics licensing, or technology commercialization.
Commercial structure (flexible)
I am open to standard industry models, including:
20–30% commission on closed deals
Tiered commission for repeat sales
Optional regional or vertical exclusivity
All terms would be documented under NDA and a simple commission agreement.
Proof & next steps
I have a concise proof pack (10–12 slides) documenting:
The problem and market gap
Why brute-force approaches fail
The constrained-search architecture
Scaling curves and bias correction
Reproducibility
Verified jackpot-level discovery
Legal and commercial positioning
If this opportunity aligns with your experience, I’d be glad to:
Share the proof pack
Walk through the results
Discuss whether a partnership makes sense