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Platform

Give AI adoption a governed path before workflows scatter

InfoDump sits between people, models, agents, and organizational knowledge so teams can move from scattered AI experiments to controlled, repeatable work.

Governance Layer

A public view of the control surface

Users

Brought under shared privacy, permission, ownership, and review expectations.

Models

Brought under shared privacy, permission, ownership, and review expectations.

Agents

Brought under shared privacy, permission, ownership, and review expectations.

Sources

Brought under shared privacy, permission, ownership, and review expectations.

Tools

Brought under shared privacy, permission, ownership, and review expectations.

Policy

Brought under shared privacy, permission, ownership, and review expectations.

Data Readiness

Scan, parse, and prepare documents for governed AI

InfoDump helps turn approved files, scans, tables, and multilingual documents into structured context that AI systems can use with privacy, permission, and ownership controls intact.

Source intake

PDFDOCXCSVScansImagesEmailTablesForms

Parsing

43 languages

Layout
Text
Tables
Entities

AI-ready output

Extracted context

languagedetected
document_typeclassified
entitiesmapped
tablesstructured
permissionsapplied

Governed AI access

{

  "source": "approved",

  "permissions": "enforced",

  "language": "detected",

  "status": "ready"

}

Scan and parse

Read documents, scans, images, tables, and long-form files so AI workflows can work from usable source context instead of loose uploads.

Extract across languages

Identify key fields, entities, and structure across multilingual business content while preserving the governance expectations around each source.

Make sources AI-ready

Turn approved documents into controlled knowledge that agents and models can use with clearer permissions, ownership, and auditability.

Capabilities

The control surface organizations need when AI becomes operational

Model access control

Give teams approved paths to the models they need while keeping usage aligned with organizational rules.

Agent permissions

Make agent purpose, tools, source access, and review expectations clear before repeatable work begins.

Controlled source access

Let AI workflows use approved knowledge without turning every file, system, or dataset into open context.

Privacy guardrails

Apply privacy expectations where people, agents, tools, and models actually interact.

Auditability

Keep AI activity understandable so teams can review what happened, which boundaries applied, and what needs attention.

Model flexibility

Support hosted and local model strategies without making provider choice the only governance decision.

Integrations

Govern AI across the tools teams already use

InfoDump connects governance to approved sources, systems, models, and controls so teams can expand AI adoption without losing ownership or auditability.

Explore integrations

Knowledge sources

Collaboration tools

Business systems

Model providers

Security and identity controls

Agent Permission Simulator

See how agent access decisions change when governance conditions shift

Pick a common agent task, then adjust the permission and policy signals. The result shows how source access, sensitive data, approved model paths, and auditability shape the decision.

Agent task

Governance conditions

Current decision

Allowed with guardrails

The agent can be useful, but the workflow should stay inside approved source and model boundaries because sensitive data is involved.

Keep the task on an approved model path and preserve a clear review trail.

Controls involved

Summarize an internal strategy memo

Sensitivity: confidential

Controlled source access

User permission check

Audit trail

Talk to us about agent permissions

How It Works

A practical layer above scattered AI usage

01

Connect people, models, and sources through one governed layer

InfoDump gives teams a clearer path for using AI without pushing every decision into separate tools, personal accounts, or unmanaged workflows.

02

Define what agents can know and do

Reusable agents should carry visible boundaries around purpose, source access, allowed tools, outputs, and review expectations.

03

Keep privacy and ownership visible as adoption grows

The governance layer helps organizations preserve control as useful AI workflows spread across teams.

Built For

Teams that need AI adoption to stay explainable

Security teams defining approved AI paths

Platform teams supporting model and agent access

Operations teams turning repeated work into governed workflows

Legal and privacy teams setting data ownership expectations

Governed AI Adoption

Ready to make AI adoption easier to govern?

Talk with InfoDump about privacy, policy enforcement, AI usage monitoring, and data ownership before unmanaged workflows become the default.

Request access