Atteston vs ChatGPT
General AI capabilities and a questionnaire-specific workflow solve different layers of the job
Where each approach fits
The honest case first: ChatGPT is genuinely useful for drafting a one-off answer. Depending on plan and configuration, it can also cite connected company sources, retain project context, support shared work, expose enterprise compliance logs, and update spreadsheets. For occasional work without a governed questionnaire process, that may be enough.
Atteston is the specialized layer for recurring questionnaire work: explicit review states, source anchors when available, exact previously approved answer reuse, approval-controlled export, and workbook drift validation tied to the questionnaire record.
Capability comparison
| Dimension | ChatGPT | Atteston |
|---|---|---|
| Evidence citations | Depending on plan and configuration, Company Knowledge and connected sources can return citations. A one-off pasted chat may not preserve a governed link to the evidence snapshot used for a questionnaire decision. | When resolved evidence is available, candidates carry source anchors into review. A question with no admissible evidence, or one that waits for input the owner must give, is grouped Needs you. |
| When evidence is missing | Behavior depends on the model, prompt, connected sources, and workspace configuration. A reviewer still needs to confirm that cited material supports the answer. | A question with no admissible evidence is grouped Needs you and shown as not found in the sources searched, instead of being presented as Ready to review. |
| Excel handling | ChatGPT for Excel and other spreadsheet tooling can inspect and update workbooks. Suitability for preserving a customer questionnaire depends on the workbook, workflow, and review. | Supported layouts use surgical writes limited to approved answers, and a drift check against the original workbook. SIG workbooks remain clearly labeled Assisted Beta. |
| Memory across questionnaires | Projects can retain files and chats, and shared projects can provide team context. Project memory is broader conversational context, not a questionnaire-specific exact-reuse decision. | Only an exact, policy-qualified previously approved answer can enter verified reuse. Other generated candidates stay in review for a person to decide. |
| Team review and approval | Business and Enterprise workspaces and shared projects support team access. They do not provide Atteston’s questionnaire-specific approval-to-export gate and work-state model. | Generated candidates pass through the review workspace. Exports use approved answer versions, and roles are account-scoped. |
| Audit trail | Enterprise compliance logs can provide immutable workspace events. They are not a questionnaire-specific approval record tied to Atteston answer, evidence, and export identifiers. | The append-only audit ledger includes event types for questionnaire jobs, approvals, and exports; answer versions and reviewer actions preserve review details. |
| Data boundaries | Data controls vary by plan, workspace settings, and connected sources. Business and Enterprise offerings provide administrative and data-governance controls. | A dedicated workspace with database-enforced tenant isolation and a published list of default and optional subprocessors by task lane. |
See the difference instead of reading about it
The homepage sample demo is a static replay of real product states: answer candidates with source anchors, evidence checks, unanswered rows flagged honestly, and export readiness. It is the fastest way to judge whether the evidence-review workflow fits how your team works.