Personalized, tax-aware portfolios across thousands of accounts — deterministic, auditable, and fast at fleet scale. Every account is its own problem; the promise is to re-solve all of them, correctly and on time, as a fleet. PRISM runs the batch and reports exactly how long it took, per percentile.
At fleet scale, "it works" isn't enough — you need to know the p50, p95, and p99 of the run, because the tail is what blows the window. PRISM treats it as a production engine: batches of 100, 1,000, and 10,000 accounts, each with tax-lot handling and a full audit trail.
A personalized, tax-aware account is a genuinely better product and a genuinely harder thing to run, because each account is its own optimization problem — its own lots, restrictions, and tax situation — that has to be re-solved as the world changes. Sell it to thousands of clients and you've signed up to run thousands of those problems, correctly, on a schedule.
That makes it a fleet problem, not a single-portfolio one. The work grows with the number of accounts, not the dollars, and the thing that breaks the window isn't the average account — it's the tail. Which is why the run has to be measured the way production systems are: by percentile.
Each is manageable alone. Together — every account correct, the whole fleet on time, the tail bounded — is where most stacks hit a wall.
Every account is a distinct problem and the count grows faster than assets — the work scales with the number of problems, not the dollars.
An average latency hides the accounts that blow the window. You need p50, p95, and p99 to trust the batch will finish on time.
Lot-level holding periods and wash-sale windows mean the right trade depends on each account's history, not just today's prices.
You bring the book; PRISM returns per-account trades, tax-lot handling, an audit trail, and the latency report for the batch. The methods are proprietary; the interface is simple.
One engine, fleet scale, deterministic.
Demonstrated results on the batches described — not a guarantee. Comparators are referred to generically as conventional / standard solvers.
Account batches of 100, 1,000, and 10,000 — the fleet sizes a real direct-indexing book runs.
Full latency reporting on every batch — the tail percentiles, not just an average that hides them.
Lot-level tax handling per account, with a content-hashed audit trail for the whole fleet run.
A matched-workload pilot on your accounts, lots, and constraints — batched to your scale, with full latency reporting and every losing case shown.
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