Attesta
Built for AI vendors facing enterprise buyer reviews

Enterprise Trust Evidence for AI API Vendors.

Attesta helps AI API, inference, and model-routing companies respond to US and EU enterprise security, privacy, procurement, and AI governance reviews with evidence-backed data handling materials.

Buyer Review Packet
Draft response structure

  • Data Flow Diagram

    Customer → API Gateway → Inference Endpoint → Logging Layer

  • No-Training Evidence

    Vendor policy + provider terms + configuration evidence

  • Logging & Retention

    Retention period, region, access controls, deletion path

  • Model Provider Disclosure

    Upstream providers, regions, subprocessors, pass-through terms

  • Jurisdictional Access Risk

    Data location, support access, residual risks

Confidential — buyer-specificIllustrative

The problem

Enterprise AI deals often stall at trust review.

Once procurement, security, privacy, or AI governance teams enter the conversation, the questions get specific — and your answers need evidence, not slide decks. Reviews can delay deals for weeks when answers are scattered across engineering, legal, provider documentation, and internal policies.

  • 01Where is customer data processed and stored?

  • 02Are prompts, outputs, files, or metadata used for training?

  • 03Which upstream model providers process customer data?

  • 04How long are logs retained?

  • 05Who can access customer data or logs?

  • 06Can China-based or Asia-based personnel access customer data?

  • 07Does customer data enter China or other sensitive jurisdictions?

  • 08Who is responsible for security, privacy, model behavior, misuse, and incidents?

  • 09Can you provide evidence, not just statements?

What Attesta does

Buyer-specific trust response packets.

Attesta works from the buyer's actual questions, your architecture, cloud setup, model providers, contracts, policies, and available evidence — then prepares clear materials that security, privacy, procurement, and AI governance teams can review. No generic template.

Data Flow Mapping

Document exactly where customer data goes — from SDK call to inference, storage, logs, and any upstream providers.

No-Training Evidence

Compile contract clauses, provider statements, and configuration evidence behind your no-training claim.

Logging & Retention

Clear logging matrix: what is logged, where, who can access, and for how long — with deletion paths.

Model Provider Disclosure

Disclose upstream models, regions, processors, and sub-processors in a format enterprise reviewers expect.

Shared Responsibility Matrix

Explicit boundaries between vendor, customer, model provider, and infrastructure — for security and incidents.

China-Origin Risk Mitigation

Address concerns about Asia-based personnel access, jurisdictional exposure, and supplier risk — with controls.

Security, Privacy & AI Governance DDQ

Draft buyer-specific DDQ responses across security, privacy, and AI governance frameworks.

When to use Attesta

Use Attesta when a buyer review is blocking the deal.

Most of these conversations start the same way: a security questionnaire shows up, the deal slows down, and the team starts rebuilding answers from scattered engineering notes, provider documentation, contracts, and internal policies.

  • A US/EU enterprise buyer sends a security or privacy questionnaire
  • Procurement asks for AI governance evidence
  • A buyer asks where customer data goes
  • A buyer asks whether prompts or outputs are used for training
  • A buyer asks which model providers are involved
  • A buyer is concerned about China-origin supplier risk
  • The sales or solutions team is stuck answering trust questions manually

Deliverables

Three engagement formats.

Each engagement is scoped around the buyer review in front of you, not a generic compliance product roadmap.

Diagnostic

48-Hour Trust Review Diagnostic

Rapid review of the buyer's questionnaire, blocker email, procurement request, or DDQ.

Outputs

  • Buyer blocker summary
  • Evidence required vs. available
  • Green / Yellow / Red assessment
  • Recommended response plan
  • Legal / security / privacy escalation items
Most popular

Enterprise AI Trust & Data Handling Packet

Buyer-specific packet prepared after evidence intake.

Typical modules

  • Data flow diagram
  • No-training evidence summary
  • Logging and retention matrix
  • Upstream model / provider disclosure
  • Shared responsibility matrix
  • China-origin risk mitigation statement
  • Buyer-specific DDQ response draft
  • Residual risk and gap memo
Retainer

Ongoing AI Trust Desk

Retainer support for repeat enterprise buyer reviews.

Includes

  • Reusable answer bank
  • Updated trust packet
  • New buyer questionnaire responses
  • Evidence folder maintenance
  • Gap tracking
  • Legal / security escalation coordination

How it works

A clear, five-step process.

Buyer Review → Evidence Intake → Trust Packet → Review & Escalation → Reusable Trust File.

  1. 01

    Buyer Review Intake

    Send us the questionnaire, blocker email, or DDQ. We map what is being asked.

  2. 02

    Evidence Collection

    We work with your engineering, security, and legal contacts to pull real evidence.

  3. 03

    Trust Packet Preparation

    We assemble a buyer-specific trust packet — clear, evidence-backed, reviewer-ready.

  4. 04

    Review & Escalation

    Internal review, then flag any item needing legal, privacy, or security escalation.

  5. 05

    Reuse & Maintain

    Reusable trust file kept current for the next buyer review — without starting over.

Scope

Focused on AI vendor trust evidence.

Attesta supports

  • AI API data handling evidence
  • Data flow mapping
  • No-training evidence
  • Logging and retention review
  • Upstream model provider disclosure
  • Shared responsibility matrix
  • Security / privacy / AI governance DDQ support
  • China-origin and jurisdictional access risk mitigation
  • Buyer-facing trust packet
  • Residual risk and gap memo

Outside our scope

  • Legal opinions
  • Compliance certification
  • KYC / KYB
  • AML
  • Payment compliance
  • Stablecoin payment compliance
  • Transaction monitoring
  • Wallet screening
  • On / off-ramp compliance
  • Unauthorized token resale
  • Unverifiable no-training claims

Attesta may identify export-control, restricted-party, or entity-list exposure as a trust review input, but formal legal advice, transaction-level screening, or regulated financial compliance should be handled by qualified specialists.

Important boundaries

What Attesta is — and is not.

Attesta prepares trust materials based on vendor-provided information, architecture, contracts, cloud configurations, policies, and available evidence.

Attesta does not independently certify vendor claims. Buyer-facing claims must be supported by vendor-provided evidence and vendor confirmation before submission.

Attesta does not

  • Provide legal opinions
  • Certify compliance
  • Guarantee buyer approval
  • Guarantee deal closure
  • Replace legal counsel, auditors, security engineers, or KYC/AML providers
  • Support unauthorized token resale
  • Support unverifiable no-training claims
  • Obscure actual data flows or unresolved risks

Security posture

How Attesta handles customer materials

Controlled handling

Customer materials are handled through confidentiality workflows and used only for the agreed engagement scope.

Restricted access

Materials can be maintained in restricted-access workspaces with access limited to the engagement team.

Evidence-based review

Client documents inform an evidence-based review — not generic templates or unverifiable statements.

Deleted or returned

Where applicable, materials can be handled under NDA and deleted or returned on request after the engagement.

Formal third-party security attestations will be added as Attesta scales.

Final step

Have a buyer review blocking an AI deal?

Send us the buyer's questionnaire, security review, procurement request, or blocker email. We'll identify what the buyer is asking, what evidence is available, what is missing, and what response packet is needed.

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