Product overview

A narrow diligence workspace built around repeat buyer questions.

DiligenceFox is not a broad governance suite. It is a focused system for organizing source materials, extracting the right facts, and generating a reusable set of buyer-facing AI diligence outputs.

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A

Input layer

Policies, security overviews, architecture notes, subprocessors, retention guidance, vendor lists, and past questionnaires.

B

Review layer

Organized facts, clear unknowns, and a single workspace that helps the team normalize answers before reuse.

C

Output layer

Reusable DDQ answers, trust-page content, system-card structure, and concise AI policy or data-use summaries.

Product architecture

Simple enough to understand. Structured enough to scale.

The current website preview focuses on the workflow users actually need to believe in. It shows how source materials become consistent diligence outputs without drowning the buyer in dashboards.

Source materials

AI policy Security overview Architecture Retention policy Questionnaire history Vendor list

Diligence workspace

Fact extraction Normalize buyer-relevant facts and separate them from unsupported assumptions.
Output generation Use repeatable structures for answer banks, trust pages, and model or system cards.
Refinement Edit wording, preserve approved answers, and refresh materials when product details change.

Output stack

Reusable DDQ answer bank
A library of buyer-facing responses for recurring security, AI, privacy, and procurement questions.
Trust-page draft
A structured narrative explaining use cases, controls, data handling, and known limitations.
Model / system card
A concise operating card covering inputs, outputs, risks, mitigations, and usage boundaries.
Policy summary
A short internal or buyer-facing summary of AI data-use and governance posture.
Feature set

The first feature set is intentionally opinionated.

DiligenceFox should feel like a serious specialist tool, not a vague content factory. These are the product capabilities the site is built to demonstrate now.

Product profiles

Start from an AI copilot, AI agent, or document AI template so the workspace language matches the actual product being sold.

Sample workspace

Open a fully preloaded fake company and inspect the output shape before trying the personalized flow.

Browser-based trial

Personalize the experience with your own company name and product type. Upload files locally to simulate the input layer.

Generated outputs

DDQ bank, trust page, system card, and policy summary appear side by side with copy and print actions.

Search and review

Filter the answer bank, inspect extracted facts, and compare the different output formats without leaving the workspace.

Minimal friction

No mandatory call. No bloated setup. The product should explain itself through the workspace and the tour.

Inside the workspace

Every output maps back to a clearer buyer conversation.

The product is built around the questions sophisticated buyers keep asking when AI software enters procurement, security review, or trust review.

UseAnswer recurring buyer diligence questions with consistent phrasing.
BenefitReduce founder, CTO, or security lead time spent rewriting the same core answers.
Output styleQuestion and answer entries optimized for reuse, review, and editing.
UseGive buyers a single narrative explaining what the product does and how it is controlled.
BenefitReduce procurement confusion and make trust review faster to navigate.
Output styleSection-based page draft covering use, oversight, data handling, and limitations.
UseCapture system boundaries, risk posture, and mitigations in a concise structured format.
BenefitSupport both internal review and buyer-facing documentation with one standard card.
Output styleBulleted structure covering tasks, inputs, outputs, risks, and mitigations.

Why this narrow shape matters

  • The product stays tied to a repeatable buyer problem instead of drifting into broad governance software.
  • The workspace explains itself in minutes, which is essential for a rep-free trial motion.
  • The output set is valuable even before deep integrations exist.
  • The site and the product tell the same story: organize source material, normalize facts, generate buyer-ready outputs.
Try the product flow

Open the sample company or personalize your own trial preview.

Use the sample workspace if you want immediate context. Use the free-trial flow if you want the workspace to reflect your own company name and product profile.

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