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Trust infrastructure
for the AI era

Detect forged documents, fake IDs and deepfakes before you fund a loan or pay a claim. Built for mortgage, HELOC and insurance teams.

Get an API key
curl https://demo.trustable.ai/v1/documents \
  -H "Authorization: Bearer $TRUSTABLE_API_KEY" \
  -F file=@statement.pdf
FAKEREALFAKEREALPASSALERTTRUST CHECK

Built for fraud, underwriting and claims teams

Mission

Make trust verifiable in every interaction. Human or AI.

The trust layer we’re building

01

Detect

Spot fakes.

02

Verify

Confirm source and identity.

03

Authorize

Set agent limits.

04

Record

Keep the evidence.

05

Compliance

Meet AI rules.

06

Copyright ©

Prove who owns it.

Detection

It starts with documents. Images, video and IDs too.

  1. Forged statements, pay stubs and IDs.

  2. AI-generated or edited photos.

  3. Face swaps and other deepfakes.

  4. Where a file came from.

  5. What was flagged, and where.

  6. A trust check before agents act. In development.

Illustration: a bank statement with an altered amount and a font mismatch marked. Illustration: a portrait photo with an edited region outlined and no camera data. Illustration: video frames pulled apart, one frame flagged as a possible face swap. Illustration: a file with its content-credential history and one missing step. Illustration: a heat map over a file beside a short list of findings. Illustration: an agent’s file paused at a trust check and held for review.

[ How it checks ]

  • File forensics

    Edits to text, pixels and layers.

  • Generator traces

    Marks AI generators leave.

  • Provenance & metadata

    Camera data and file history.

  • Explainable output

    Every flag, shown on the file.

Evidence

See what was flagged, and where.

Each finding comes with its reason and strength.

Read our approach

Signals · altered bank statement

  1. 01Font mismatch: strong
  2. 02Edited text layer: moderate
  3. 03Totals don’t add up: moderate
  4. 04Known fake template: weak
  5. 05Metadata gap: weak

Illustrative example

Not a real result.

Detection is just the start.

What we’re building around every check.

Uncertainty, surfaced

Unsure results go to a person.

In development
Illustration: a document under a magnifier, flagged as low confidence and sent to a reviewer.

Cross-document checks

Income compared across pay stubs, W-2s and deposits.

In development
Illustration: a pay stub, W-2 and bank deposits feed an income cross-check that flags a mismatch for review.

Agent trust check

Agents check a file before they act.

In development
Illustration: an agent trace that receives an invoice, checks it, finds an edited amount and holds the payment for review.

Workflow routing

Pass, review or hold.

In development
Illustration: an upload is checked and routed to pass, review or hold.

Review console

All the evidence in one place.

In development
Illustration: a review queue with flagged and cleared files and a highlighted region.

Where trust breaks

Fake documents, images, videos and IDs cost real money.

  • Altered statements and pay stubs inflate income.

    Document

  • Edited income documents slip past lighter checks.

    Document

  • Fake damage photos and invoices inflate payouts.

    Image · Document

  • Onboarding & KYC

    Synthetic selfies and edited IDs.

    ID · Video

  • Payments & disputes

    Edited receipts and screenshots.

    Image · Document

  • AI agents

    Agents acting on fake files.

    Any file

Evidence, handled
with care.

Illustration: a file kept inside an enclosed environment.

Your files, your control

We agree how files are handled before you share any.

People decide

Every flag comes with its evidence.

Illustration: three cards for evidence, uncertainty and human review.

Security

Security built for regulated teams.

Our cloud, yours or on-prem

Host in the US, EU or APAC, deploy in your own VPC or on-prem, or keep files in your cloud while Trustable runs the checks.

SOC 2 Type II and GDPR

Independently audited controls, with personal data handled under GDPR.

FAQ

Questions, answered.

Can Trustable detect fake bank statements?

Yes. Trustable flags edited text, font and layout mismatches, metadata gaps and totals that don’t add up, and marks where each one is on the page.

How are fake pay stubs and W-2s detected?

Each pay stub and W-2 is checked for edited figures, font mismatches and rebuilt templates. Cross-checking income across a whole loan file is in development.

Why do HELOC lenders need document fraud detection?

HELOCs often close with lighter checks than a first mortgage, so an edited pay stub or statement is easier to miss.

Can Trustable detect AI-generated or edited claim photos?

Yes. It looks for edits, AI-generation traces and missing camera data in damage photos, and checks repair invoices and receipts for edits.

Does missing metadata mean a file is fake?

No. Messaging apps, screenshots and re-saves often strip it, so it’s one signal among several, never proof on its own.

Is Trustable SOC 2 compliant?

Yes. Trustable is SOC 2 Type II audited and handles personal data under GDPR. It runs in our cloud with US, EU or APAC hosting, in your own VPC or on-prem.

Is Trustable always right?

No. No AI is 100% accurate. Results can be wrong in either direction, flagging a genuine file or missing a fake, so a person should review each flag before acting on it.

Who makes Trustable?

Trustable is a product of Reality Inc., based in San Francisco and Toronto. About the company.

Trust you can verify.