PRISM's optimization core returns a feasible, near-optimal, fully auditable answer inside a hard real-time deadline — at a scale and speed where conventional solvers can't respond in time. The same engine powers new domains:
Three application areas we've validated — each a high-stakes decision that has to be re-solved correctly, on time, the instant the world moves.
Re-optimize battery & distributed-energy dispatch the instant prices or forecasts move — within the grid control-tick.
Demonstrated on real California ISO grid data: a feasible, audited dispatch plan delivered within deadlines from 500 ms down to ~5 ms, changing only the few intervals worth changing.
Optimal rebalancing plus full risk attribution inside a hard latency budget — at universe sizes where standard optimizers stall.
Demonstrated on a real 75,000-asset dataset: an optimal rebalance, a factor/specific risk breakdown, and an audit trail returned in well under a second — across tens of thousands of holdings.
Personalized, tax-aware portfolios across thousands of accounts — deterministic, auditable, and fast at fleet scale.
Production-grade fleet engine: 100 / 1,000 / 10,000-account batches with full latency reporting (p50/p95/p99), tax-lot handling, and a full audit trail.
Demonstrated results on the datasets described — not guarantees. Comparators are labeled generically as conventional / standard solvers. Schematic elements in the panels above are marked illustrative.
Inputs in; a feasible, near-optimal, fully auditable answer out — inside your deadline. The methods are proprietary; the interface is the same across every domain above.
One engine, a hard deadline, deterministic.
The answer arrives inside the deadline that matters — a grid control-tick, a latency budget, an overnight window — not whenever the solver happens to finish.
Every decision traces to your inputs and constraints, with a content-hashed, reproducible record — the same audit trail across energy, finance, and wealth.
See the demonstrated results, or run the same core on your own workload — your data, your constraints, your deadline, every losing case shown.
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