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:
In plain English. Every application below is the same underlying problem: choose the best option from an enormous number of possibilities, obey every rule, and finish before a deadline. Only the subject matter changes — investment accounts, batteries on a power grid, a bank's capital. Unfamiliar words? See the glossary.
The deepest evidence is in finance — direct indexing and real-time portfolio decisioning. The same core extends to any high-stakes decision that must be re-solved correctly, on time, the instant the world moves.
Personalized, tax-aware portfolios across thousands of accounts — deterministic, auditable, and fast at fleet scale. PRISM's deepest evidence base.
Each client owns real shares in their own account, so each one needs its own buy/sell list every night — tailored to their tax position. This is doing that for tens of thousands of accounts before the market opens.
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.
Optimal rebalancing plus full risk attribution inside a hard latency budget — at universe sizes where standard optimizers stall.
A big portfolio drifts out of shape as prices move. This works out what to buy and sell to bring it back in line, fast enough to still act on, and shows exactly where its risk is coming from.
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.
Re-optimize battery & distributed-energy dispatch the instant prices or forecasts move — within the grid control-tick.
Thousands of batteries spread across an electricity grid each need a fresh instruction every few seconds as power prices move — and each instruction has to be something the equipment can physically do.
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.
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.
Try the interactive models: tax-loss harvesting · rebalance latency · FRTB capital · energy dispatch.
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.
8-week paid pilot on your data — you get a benchmark report on your real problem and reference pricing for production. Your data, your constraints, your deadline; every losing case shown.
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