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Advanced AI without surrendering your competitive advantage

Psodo gives professional organisations one controlled workspace designed to keep confidential work out of provider training data while teams use leading AI models together.

Access, protection, and collaboration in one workspace

Give your team the capabilities they already want without accepting unmanaged training-data exposure.

Training-data protection

Use AI without contributing confidential work to training

Psodo is designed to prevent your organisation’s files, conversations, documents, and intellectual property from being used to train external AI models. The applicable provider settings and protections are reviewed as part of your rollout.

  • Keep client information out of unmanaged consumer accounts
  • Reduce exposure to external model-improvement processes
  • Review the protections that apply to your rollout
  • Protect the knowledge that differentiates your firm
Discuss your requirements
Leading AI models

Access leading models through one controlled workspace

Give your team access to models from OpenAI, Anthropic, Google, and other leading providers without managing separate personal accounts for confidential professional work.

  • Chat with leading AI models
  • Choose the model that suits the task
  • Upload and analyse relevant files
  • Keep professional and personal AI use separate
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Secure collaboration

Work with AI as an organisation

Save and share chats, files, and AI-created documents with authorised colleagues. Teams can review and continue useful work without moving sensitive material between disconnected tools.

  • Create and refine documents with AI
  • Share conversations and source files
  • Continue another team member’s work where authorised
  • Keep valuable knowledge inside the organisation
Request access

Why training-data exposure matters

Confidential information can influence future AI capabilities where appropriate protections are absent

Provider terms differ

Whether information may be retained, reviewed, or used to improve models depends on the provider, product, account type, settings, and contractual agreement.

Future systems can learn patterns

The risk is not limited to word-for-word reproduction. Proprietary context, terminology, relationships, and reasoning approaches can contribute to future model capabilities.

Use can be difficult to observe

Once intellectual property enters an external training or improvement process, the organisation may not know what was learned, what it influenced, or whether it can be fully removed.

Competitors use the same models

A competitor may never see the original prompt, yet still benefit from a later system whose reasoning or capabilities were influenced by proprietary information supplied across the market.

Built for valuable legal knowledge

Your legal strategy should not become training material for systems later used by opposing firms

Protect legal strategy and reasoning

Develop arguments, test approaches, and analyse matters through an environment designed to keep confidential legal reasoning out of future model training.

Work with sensitive matter information

Analyse case material, client information, legislation, and internal precedents without placing them into unmanaged personal AI accounts.

Create legal documents

Draft and refine submissions, correspondence, negotiation positions, and internal notes while protecting the reasoning behind the work.

Collaborate between authorised lawyers

Share chats, files, and documents inside the firm so useful analysis can be reviewed and continued without leaving the organisational workspace.

Built for proprietary financial insight

Your best investment ideas should not improve the AI tools available to your competitors

Protect investment theses

Research markets, challenge assumptions, and test investment ideas through an environment designed to keep proprietary financial insight out of future AI training.

Analyse market information

Work with research, market signals, risk assessments, and portfolio analysis while keeping files and conversations together.

Keep trading ideas private

Reduce the risk that a valuable strategy or market insight contributes to systems later used by competing traders, funds, or analysts.

Retain research inside the firm

Turn proprietary analysis into internal reports that authorised colleagues can review and build on without moving work into personal tools.

Stop treating intellectual property as the price of using AI

Give your organisation access to leading models through a workspace designed to prevent confidential work from becoming external training material.