USE CASE · FINANCIAL SERVICES

Disclosures. KYC. Policy lookups.
Same questions. All day.

Banks, asset managers and insurers run the most repetitive AI workloads on the planet — disclosure summaries, regulatory Q&A, policy and product fact lookups, KYC walkthroughs. MEMStorage routes the repeats to siloed memory and only escalates the genuinely novel queries.

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65%
avg query repetition in financial AI workflows
50–65%
typical inference cost reduction
Siloed
per-tenant memory · no cross-org leakage
The problem

Compliance volume is repetitive.
Compliance budgets are not.

Financial workflows have the highest structural overlap of any AI use case we've measured: disclosure language, fund fact sheets, KYC scripts, regulatory Q&A. The questions repeat. The bills do not stop.

📋
Disclosure and policy Q&A is mostly the same query
"What is the redemption window on Fund X?" "What is the surrender charge on this annuity?" "Does this prospectus cover non-US persons?" The answers do not change daily. The model recomputes them anyway.
65%
avg measured repetition rate in financial AI deployments
🛡️
Vendor caches are off the table
Provider-side prompt caching means your sensitive prompts sit on someone else's infrastructure. Most compliance teams will not approve it. So you pay full cost on every call, forever.
🔍
Audit trail requirements rule out black-box savings
"It just got cheaper" is not a satisfactory answer for an examiner. Every routing decision needs to be logged, attributable, and reproducible. Most cost-optimization layers cannot meet that bar.
✦
Memory routing is the audit-friendly fix
A per-tenant siloed layer that logs every routing decision, every score, every served answer — and runs on your infrastructure if needed. Cheaper inference without giving up the audit trail.
Why it fits financial services

Built for regulated workloads
from day one.

🔐
Per-tenant isolation, no cross-org leakage
Every client's memory is a separate logical store. Embeddings cannot be reverse-engineered to source content. Configurable per business unit so wealth, retail and institutional do not share a memory.
🏠
On-prem or private-cloud deployment
Run MEMStorage entirely inside your VPC or on-prem cluster. Nothing leaves the perimeter. The router talks to your existing model endpoint — internal or vendor — without changing your data path.
📜
Full audit trail for every decision
Every query is logged with score, matched memory ID, served answer, and tier (hit / confirm / inference). Reproducible months later. Exportable to your existing compliance and observability stack.
⏱️
Configurable freshness windows
Memory entries can carry per-class TTLs: market data answers expire daily, policy text expires when the document version changes, KYC scripts persist until you say otherwise.
🧾
Document-version-aware
Memory is scoped to source document versions. When a prospectus is reissued, the prior memory entries are invalidated automatically. The next query rebuilds from the new doc.
🛂
Confidence thresholds tuned for risk class
Tighter thresholds on suitability, AML and disclosure questions; looser on FAQ-style policy lookups. The router's behavior is configurable per intent and per risk tier.
Estimated cost reduction

For a typical mid-size asset manager.

Modeled on a $75K/month inference spend across an internal disclosure / Q&A copilot used by ~400 RMs and a client-facing FAQ assistant. Your numbers depend on intent mix; the pilot reports actuals.

Current monthly state
$75,000
Monthly inference calls~280,000
Avg cost per call$0.27
Repeat rate (measured)65%
Repeat compute paid for$48,750
Vendor prompt caching is unavailable due to data-residency policy. Every call is billed at full rate.
With MEMStorage
$31,500
Memory hit rate (steady state)~58%
Inference paid only on novel queries$31,500
MEMStorage fee (Scale tier)$8,000
Net monthly savings$35,500
Projected annual savings$426,000
Conservative model uses an 88% capture of the 65% repeat baseline. Most fin-services pilots run higher because policy text changes rarely.
Demo scenario

A morning at an asset manager.
Routed live.

Five real-world queries from an internal RM-facing copilot. Memory handles the policy and disclosure repeats. Confirm validates a borderline suitability question. Full inference only on the genuinely novel ask.

memstorage · advisor copilot — 9:42am
MEMORY HIT
"What is the redemption window on the Diversified Income Fund Class I?"Score 94% · matched stored "fund redemption · DIFC-I" intent · doc v2026-Q1
0 tokens
MEMORY HIT
"Does the IRA rollover form 5498 cover Roth conversions?"Score 89% · matched stored "IRA rollover form 5498 scope" intent
0 tokens
CONFIRM
"Is a 70-year-old client suitable for the Strategic Alpha Plus sleeve?"Score 41% · suitability tier · routed to Claude for 20-token confirmation
~20 tokens
MEMORY HIT
"Summarize the surrender charge schedule on the Variable Annuity Series B."Score 91% · matched stored "VA Series B · surrender" intent
0 tokens
FULL INFERENCE
"For a non-US trust held under an irrevocable grantor structure, does Treasury Reg §1.1471-4 apply to a passive NFFE distribution back to the grantor?"Score 7% · novel · escalated and stored to memory
~720 tokens
80%
Hit Rate (5 queries)
~740
Total tokens used
~$0.06
Total spend (vs $1.35)
Get started

Pilot it inside your perimeter.

We deploy MEMStorage on-prem or in your VPC, mirror traffic from your existing copilot, and report the actual hit rate, latency improvement, and dollar delta against your current model bill — fully audit-logged.

30-day financial-services pilot

Per-tenant siloed memory, on-prem or VPC deployment, full audit trail. We run it against 30 days of your real inference traffic and only invoice if the savings clear the fee. SOC 2 Type I in pilot phase, Type II roadmap 2026.

Start the pilot → Read the SEC-corpus benchmark