Live on AWS for proof-ready AI workflows

Make sensitive Amazon Bedrock workflows easy to approve, prove, and share.

DigiTrust helps teams move sensitive AI work from pilot to production by checking the right baseline items, protecting sensitive data, using an approved Amazon Bedrock path, recording reviewer sign-off when needed, and producing a verifiable Evidence Packet.

Live validation passed Evidence Packet verifier enabled PRAI-1 workflow standard included AWS review-readiness package prepared

Choose the view that works for you.

Start with plain-language proof questions, or open the AWS services view when your technical team wants detail.

For business, risk, compliance, privacy, and audit teams

See what DigiTrust helps you answer without needing to read architecture diagrams.

For AWS, platform, security engineering, and AI teams

See the deployment pattern and the AWS services behind the scenes.

DigiTrust helps your team answer the questions that delay AI launch.

  • Was this AI workflow approved for its business purpose?
  • Was sensitive data protected before model use?
  • Was Amazon Bedrock used through an approved path?
  • Did a person review the work when review was needed?
  • Can we share a clean Evidence Packet with security, compliance, audit, or a customer?

DigiTrust is deployed on AWS and designed for Amazon Bedrock workflows.

It connects baseline checks, sensitive-data protection, approved model paths, Bedrock evidence, packet verification, and TrustOps review into one proof-ready workflow.

Show AWS services behind the scenes
Amazon Bedrock
Amazon Bedrock Guardrails
Amazon Bedrock Knowledge Bases
AWS Amplify Hosting or Amazon CloudFront
Amazon ECS on AWS Fargate
Amazon S3 with AWS KMS
Amazon DynamoDB or Amazon Aurora/PostgreSQL
AWS Secrets Manager
Amazon CloudWatch
AWS CloudTrail
AWS WAF
AWS Config
AWS Well-Architected Tool
AWS Marketplace private offers

Why teams need DigiTrust

AI is moving into customer, claims, healthcare, finance, legal, and support workflows. Teams need more than a model response. They need a clear, shareable record of what happened and why it was acceptable.

Security and privacy

Show how sensitive data was classified, protected, and handled before model use.

Compliance and audit

Share a packet that records the workflow purpose, review outcome, and proof trail.

AI and cloud teams

Use an approved Amazon Bedrock path and see workflow results in TrustOps.

How DigiTrust works

Start with one sensitive workflow and produce one packet your reviewers can use.

1

Start with one workflow

Pick one Amazon Bedrock workflow that needs security, privacy, compliance, audit, customer, or leadership review.

2

Check the baseline

DigiTrust checks identity, logging, encryption, approved environment, storage, and review readiness. If a required baseline check fails, the workflow is not marked as passed.

3

Protect sensitive data

DigiTrust classifies sensitive values and applies the right protection step before model use, such as masking, tokenizing, minimizing, or redacting.

4

Use an approved Bedrock path

DigiTrust records the approved Bedrock model path, region, guardrail reference, workflow purpose, and routing result.

5

Add reviewer sign-off

When the workflow requires a human decision, DigiTrust records the reviewer, outcome, timestamp, and reason.

6

Generate and verify the packet

DigiTrust creates an Evidence Packet and runs packet verification so teams can share proof with the right reviewers.

The proof object your team can review and share.

An Evidence Packet is a clean, verifiable record of a sensitive AI workflow. It is designed for security, compliance, privacy, audit, customer assurance, AI product, and cloud teams.

Important packet rule: DigiTrust Evidence Packets are designed to store metadata, hashes, references, classifications, decisions, summaries, and status results instead of raw sensitive values.

Evidence Packet sections

  • Workflow identity and owner
  • Business purpose and policy result
  • Sensitive-data classification and protection steps
  • Approved Amazon Bedrock path
  • Guardrail and review evidence
  • Output summary and action record
  • Baseline check result
  • PRAI-1 workflow standard result
  • Acceptance result
  • Verification hash, signature, and export record
  • Framework evidence mapping

What is included now

DigiTrust is live on AWS and ready for design-partner validation.

Amazon Bedrock workflow path
Evidence Packet v0.3.1 with Bedrock evidence fields
PRAI-1 proof-ready workflow standard
Evidence Packet Acceptance Protocol
Evidence Packet Verifier
Policy-as-code proof rules engine
Customer Assurance Package
Regulatory and Framework Crosswalk Pack
AI threat model and red-team plan
AWS FTR and Well-Architected review-readiness package
Live Validation Report package
Design Partner Readiness Pack
Bedrock Evidence Packet QuickStart

Start with one workflow. Produce one packet. Decide with proof.

The Bedrock Evidence Packet QuickStart helps a design partner validate one sensitive Amazon Bedrock workflow in a focused engagement.

QuickStart outcomes

  • Select one workflow and business owner
  • Define the sensitive-data profile
  • Confirm the approved Bedrock path
  • Run the workflow with synthetic or approved test data
  • Generate an Evidence Packet
  • Run packet verification
  • Review results in TrustOps
  • Create one proof asset for internal review

Customer assurance materials for qualified reviewers

DigiTrust gives security, compliance, privacy, audit, legal, and AWS teams a clean review package.

Security overview

Baseline checks, shared responsibility, packet storage, and data-handling summary.

Evidence mapping

Framework crosswalk and packet field mapping for customer review.

AI safety testing

Threat model summary, red-team plan, and remediation workflow.

AWS readiness

FTR and Well-Architected review-readiness materials for next-step preparation.

Make your first Bedrock workflow proof-ready.

DigiTrust is live on AWS for proof-ready AI workflow validation. Start with one sensitive workflow, generate a verifiable Evidence Packet, and give every reviewer a clear record they can trust.