NeodyAI
AvailableBanks · Payments · Finance · Healthcare · Investment · Gaming

Run AI on the data you can't send to AI.

  • PCI · card data
  • PHI · HIPAA
  • MNPI · inside information
  • PII · personal data

Neody is a framework for using regulated data with large language models. Card numbers, patient records, inside information and customer PII are protected field by field, before any model sees them. The model works on format-preserving stand-ins; only the people and systems you approve ever see the real values — and every access is on the record your examiner will ask for.

Every claim on this page is enforced by a test that gates our build. If a test is ever disabled, the claim comes off this page the same day.

dispute · case D-2047 · the model's-eye view live demo
What your analyst sees

Card 4111 1111 1111 2847

Cardholder Maria Lopez

SSN 123-45-6789

statement.pdf (scanned)

Draft: refund $412.60

What the model saw

Card 4111 11XX XXXX 2847 pv_01HX…

Cardholder [PII:name#a1]

SSN [PII:ssn#b7]

statement.pdf → 14 spans protected

Draft: refund $412.60

  1. Revoke the key — the same request now fails, and the refusal is logged.
  2. Point the agent at an unapproved destination — refused, naming the rule.
  3. Open the evidence record — for each field: its class, tier, who could read it, when it was resolved.
Built for regulated work

The work your teams can't hand to a general AI assistant — now they can

Banks & credit unions

PCIPII

  • Card disputes — evidence packs with card data protected on your premises
  • KYC refresh — customer documents reviewed on stand-ins, not identities
  • Third-party risk reviews — SOC reports and questionnaires against your policy

“Start PCI-free with KYC or TPRM. Add card data when the on-premises protection zone is live.”

Healthcare — payers & providers

PHI · HIPAAPII

  • Prior authorisation — clinical packets triaged against medical policy
  • Claims and fraud, waste & abuse — validated and referred, never denied by an agent
  • Minimum necessary, enforced per field and per agent

“Prior auth and fraud on PHI, with the minimum necessary enforced per field.”

Investment & asset management

MNPIPII

  • Deal analysis — data rooms and memos, visible only to the deal team's agents
  • Portfolio operations — manager reports consolidated and checked
  • Information barriers and restricted lists, enforced at run time

“A deal wall that's enforced, not a policy — with detection limits stated plainly.”

Payments — processors & PSPs

PCIPII

  • Chargebacks and disputes — evidence assembled with card data protected
  • Merchant onboarding (KYB) — business documents checked against your risk policy
  • Transaction-monitoring alerts — triaged and summarised for your analysts

“The model works on card-number stand-ins that still validate and match — never the card itself.”

Finance — lenders & fintech

PIIPCI

  • Loan files — income, bank statements and IDs reviewed against your credit policy
  • Underwriting QC before sign-off, with every exception traced to the document
  • Customer communications checked against your compliance rules before they go out

“Review the whole loan file without the model ever seeing who the borrower is.”

Gaming — casinos, iGaming & sportsbooks

PIIPCI

  • Player KYC and age verification — documents reviewed on stand-ins
  • AML and source-of-funds reviews — cases prepared for your compliance team to decide
  • Responsible-gaming case review — patterns surfaced, a person always decides

“Player identities and payment details stay protected, case after case.”

The framework

Protect the field, not the payload — so AI can still do the work

Encrypting a whole document makes it useless to a model; redacting it removes what the model needs. Neody protects individual values and leaves the structure readable.

  1. 1

    Classify every field

    Each value carries its data class — PCI, PHI, MNPI, PII, trade secret — inside documents, emails and tool calls, including scanned PDFs, verified by re-extraction.

  2. 2

    Protect it before the model sees it

    The model gets format-preserving tokens and short references — a tokenized card number still validates and joins, but it isn't the card. The model never handles ciphertext.

  3. 3

    Decide who reads plaintext

    Per data class and per agent: platform-managed, per-agent keys, or sealed so the platform itself cannot read it. Written into the agent's charter and enforced — not configured.

  4. 4

    Enforce at the boundary

    Nothing unprotected crosses the egress boundary. Destinations come from a list your institution approves; keys are per tenant, customer-held and revocable.

  5. 5

    Govern every agent and prove it

    Ours, your vendors' or your own: autonomy earned on measured agreement with your reviewers, and one evidence record per field, ready for model risk, third-party risk and audit.

By data class

One framework, the rules of each data class

Card data

PCI DSS v4

Card numbers are protected on your premises before anything reaches Neody.

The goal is that Neody stays out of your PCI scope: cardholder data is sealed so the platform cannot read it, and the model sees only a format-preserving stand-in.

Available. We say “out of your PCI scope” only with a QSA scoping opinion in writing — ask us about its status.

Health data

HIPAA

Minimum necessary, enforced per field, per agent.

Each agent sees only the PHI its task requires, on stand-ins wherever possible; every access is recorded with its purpose.

Available. HIPAA is a contract as well as controls — ask us about BAA readiness and terms.

Inside information

MNPI · Reg FD

Only the deal team's agents see the deal.

Access scoped to named people and data classes, wall-crossing and restricted lists enforced at run time, and a record of who saw what and when.

We detect MNPI and enforce barriers — and state the limits plainly: there is no checksum for materiality.

Personal data

GLBA · state privacy laws

The model reasons over stand-ins, not your customers.

Names, SSNs, account numbers and addresses are tokenized consistently, so the model can still match and compare records without seeing who they are.

Available.

What we claim — and what we don't

Security reviews punish overclaiming. So we don't.

Every statement on the left is enforced by a test that gates our build. If that test is ever disabled, the claim comes off this page the same day.

We sayWe don't say
Regulated data is protected before it reaches a public model, and nothing unprotected crosses the egress boundary“End-to-end encrypted” — we run the agents, and at some tiers we decrypt to process
Cardholder data never leaves your premises unprotected“We never see your data” — true only for sealed data classes
Per-tenant keys, customer-held and revocable“Your data never leaves your building” — impossible while we run your agents
MNPI detection plus barrier enforcement, with the limits stated in the productThat MNPI is reliably detectable — materiality has no checksum
Sealed data classes make us unable to read a valueThat per-agent keys keep data confidential from us — they limit the blast radius of a key compromise

Start with one process on one data class

We map every field — its class, who can read it, where it goes — in a Data Path Report before anything runs, then pilot in shadow mode alongside your reviewers and measure how often they agree.