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Solution
Forge and Forecast Your Decision
- Calculating Causal Outcomes
Abel.AI models the world as a causal graph —
a decision-grade causal representation extending decades of
causal inference research, and implemented as a scalable AI system operating on real-world signals, per individual instance.
Inside the System
Decision-Grade
Individual Computation
World Model
Simulation
Decision
Computable representation of the world
Propagation of change through the world
Reliability of outcomes
in the real world
10M+
Executable
Causal Nodes
Entities, variables, and constraints structured as an executable causal graph, built from high-frequency, continuous real-world signals.
→ Explore → Explore
5M+
Real-world events
Simulated
Events are injected, propagated, and
resolved through causal inference and
do-calculus
→ Explore → Explore
+110%
Decision
outcome lift
Measured where causal structure, rules,
and consequences matter,
not just fluent answers
→ Explore → Explore
Product
Right Before Your Decision
Abel.AI surfaces the variables others miss —
limits capping outcomes, value already shifting, momentum turning crowded,
windows quietly closing.
See the game clearly — before the move commits.
Buy 4090
Utilities / Power
NVDA Shock
VRT (cooling)
Causal chain: NVDA → Cooling (VRT) → Power
Measured lag: ~14d to cooling, ~30d to power
Result: ~30% of GPU premium is driven by cooling & energy constraints
State: the system is already operating near capacity
Why
|
Buy 4090
Utilities / Power
NVDA Shock
VRT (cooling)
Causal chain: NVDA → Cooling (VRT) → Power
Measured lag: ~14d to cooling, ~30d to power
Result: ~30% of GPU premium is driven by cooling & energy constraints
State: the system is already operating near capacity
Why
|
Buy 4090
Utilities / Power
NVDA Shock
VRT (cooling)
Causal chain: NVDA → Cooling (VRT) → Power
Measured lag: ~14d to cooling, ~30d to power
Result: ~30% of GPU premium is driven by cooling & energy constraints
State: the system is already operating near capacity
Why
|
Buy 4090
Utilities / Power
NVDA Shock
VRT (cooling)
Causal chain: NVDA → Cooling (VRT) → Power
Measured lag: ~14d to cooling, ~30d to power
Result: ~30% of GPU premium is driven by cooling & energy constraints
State: the system is already operating near capacity
Why
|
Buy 4090
Utilities / Power
NVDA Shock
VRT (cooling)
Causal chain: NVDA → Cooling (VRT) → Power
Measured lag: ~14d to cooling, ~30d to power
Result: ~30% of GPU premium is driven by cooling & energy constraints
State: the system is already operating near capacity
Why
|
Buy 4090
Utilities / Power
NVDA Shock
VRT (cooling)
Causal chain: NVDA → Cooling (VRT) → Power
Measured lag: ~14d to cooling, ~30d to power
Result: ~30% of GPU premium is driven by cooling & energy constraints
State: the system is already operating near capacity
Why
|
01 - Test Limits
02 - Check Value
03 - Avoid Crowding
04 - Watch Windows
05 - Avoid Undo
06 - Play Long Game
Shows how close this decision is to hitting hidden limits — before extra effort stops paying off.
Blog
The World, Computed
View more
January 2026 Domains
→ Read more
Start Simulating with Causal AI
Interested in shaping the future of
causal intelligence? We're hiring.
Open Roles
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