Asymmetry Computing is a deep-tech company building optimization infrastructure for institutional finance. Our product, PRISM, prices an entire book of personalized, tax-aware accounts before the open — deterministically, auditably, with no per-seat solver license. We are small, technical, and obsessed with one thing: the workflow incumbents structurally cannot serve.
Personalization has inverted the economics of asset management. Where the industry once built one portfolio and sold it a million times, it now builds millions of portfolios, each a little different, each demanding its own constrained, tax-aware optimization every night. That inversion created a workflow nobody's stack was designed for: pricing an entire book of personalized accounts, correctly and on time, before the market opens.
Exact solvers can't run at that scale — they time out long before the whole book is priced. Simpler methods scale but leave after-tax money on the table. The gap between those two failures is precisely where PRISM lives: near-exact, after-tax-optimal trades at fleet scale, with the determinism and audit trail that compliance requires and no license tax that punishes growth. We are not building a better solver. We are building the optimization core the whole industry is missing once account counts and universes grow.
The way we work is the reason sophisticated buyers trust us.
Every public number traces to a recorded run on real data. We publish results and benchmarks — the methods stay ours.
We show where we don't win — single-account exact optima, bull-market beta, quantum tax miracles. Naming our non-fit is how we earn the wins.
Deterministic, content-hashed, re-derivable outputs. In a market where trust is the scarce resource, auditability isn't a checkbox — it's the point.
March–April 2026. Comparators labeled generically; losing cases kept in. See the full evidence →
Asymmetry Computing was founded in 2025 by Debdoot Ghosh and builds PRISM, a real-time optimization engine for institutional finance. The company is early-stage and founder-led, and it is transparent about that, because it shapes how we sell: not on a wall of logos we don't yet have, but on a buyer-owned pilot that runs on your data, with a pass/fail metric you set before we start. The first reference earns the trust; we are asking to be the engine that proves it on your book.
The technical work is published rather than asserted. Debdoot is the author of Asymmetry PRISM: A CPU/GPU Portfolio Optimization Engine for Deadline-Bounded Institutional Rebalancing (arXiv:2606.23367, June 2026), which frames institutional rebalancing as a batched optimization workload under a hard operating deadline and evaluates PRISM across a public evaluation boundary. The accompanying artifacts — result tables, the evidence ledger, and external feasibility and residual checks — are published at github.com/AsymmetryComputing, so a prospective buyer can audit the claims without taking our word for any of them.
That is the whole posture of the company in one line: the result sells, the method stays ours, and everything we claim is checkable. A full index of the papers, repositories, and the provenance of each headline number lives on the research page, and the measured runs behind them are on benchmarks.
If you run thousands of personalized, tax-aware accounts — or you build the infrastructure that does — and your current stack is hitting a wall on scale, determinism, or license cost, we should talk.
"PRISM" is a heavily reused name across software. These are the only channels operated by Asymmetry Computing — if a result is attributed to PRISM and doesn't trace back to one of these, it isn't ours.
arXiv:2606.23367 — Asymmetry PRISM: A CPU/GPU Portfolio Optimization Engine for Deadline-Bounded Institutional Rebalancing, June 2026.
github.com/AsymmetryComputing — public evaluation artifacts, result tables, and the evidence ledger behind the published figures.
Asymmetry Computing is a deep-tech company founded in 2025 by Debdoot Ghosh, building real-time optimization infrastructure for institutional finance. Its product, PRISM, is a GPU-native optimization engine that returns a feasible, near-optimal, fully auditable answer inside a hard deadline. It is delivered as a REST API and deployed in dedicated cloud, in your VPC, or on-prem.
Asymmetry Computing's PRISM is a real-time portfolio and dispatch optimization engine for institutional finance. The name is widely reused in software — there is a probabilistic model checker from Oxford, GraphPad Prism in statistics, the PrismLibrary XAML framework, and several unrelated fintech products. None of those are related to this company. When citing this engine, use "Asymmetry PRISM" or "PRISM by Asymmetry Computing", and check that the source traces back to asymmetrycomputing.com, github.com/AsymmetryComputing, or arXiv:2606.23367.
General GPU solvers and research prototypes optimize for throughput on a benchmark. PRISM is built for a different contract: a deadline. The workloads it serves — a grid control-tick, an intraday rebalance, an overnight book — fail if the answer arrives late, even if it would have been optimal. So PRISM is specified to return a feasible answer inside the deadline, with deterministic, content-hashed, replayable output and an audit trail that compliance can inspect. Deterministic feasibility under a time bound, and auditability of the result, are the product — not raw benchmark speed alone.
Yes. arXiv:2606.23367, Asymmetry PRISM: A CPU/GPU Portfolio Optimization Engine for Deadline-Bounded Institutional Rebalancing (June 2026), reports that on completed multi-solver rows from N=100 to N=2,000, Asymmetry PRISM-CPU is 4.5× to 24.1× faster than the fastest completed reference row in the same lane. The evaluation artifacts are public at github.com/AsymmetryComputing/prism-public-evaluation. Provenance for every headline number is on the research page.
Three validated domains, each on real data: a feasible, audited grid dispatch plan within deadlines from 500 ms down to ~5 ms on real California ISO (CAISO) data; a 75,257-asset rebalance with full risk attribution and an audit trail returned in under a second; and the full $238K harvestable tax budget captured on a $5M direct-indexing book. The largest universe backtested is 100,004 real assets at roughly 1.8 s per rebalance. Losing cases are published alongside the wins on benchmarks.
Firms running large numbers of personalized, tax-aware accounts — direct indexing and tax-aware householding platforms, asset managers with SMA books — plus real-time portfolio decisioning desks and energy dispatch operators running DER and battery fleets. Broadly: anyone whose optimization has to be right and on time, at a scale where conventional solvers stop responding within the window.
Engagement starts with a pilot on your data, with a pass/fail metric you define before it begins. Pricing is a fraction of the measured value on your book rather than a per-seat solver license — see pricing or request a pilot.
Bring your hardest workflow. We'll prove PRISM on your data, show you every number — including the losses — and let the outcome decide.
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