Picks The Best Brain

Leo is model-agnostic and chooses the right AI model for each job, so teams get higher quality outputs without managing multiple tools or subscriptions.

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The Reality

Why This Matters

Most teams face a simple reality: no single AI model excels at everything.

One Model ≠ Best Results

Each AI model has strengths and weaknesses. Some are better at structured reasoning, others at writing, long context, coding, or fast summarisation. Relying on just one means accepting compromises in quality.

Tool Sprawl & Complexity

When teams need better results, they start juggling multiple tools and models. This increases costs, admin overhead, inconsistency, and security risk—slowing teams down instead of helping them move faster.

The Flexibility Gap

Teams want the freedom to use the right model for the job—without added complexity. Leo removes the trade-off by giving model flexibility in one controlled, simple platform.

Comparison

Generic AI vs Leo

See what changes when security is built into the foundation.

What you experience

Output quality

Limited by one model’s strengths.

Better results by matching model to task.

Vendor lock-in

Hard to switch as needs change.

Model-agnostic, so you can switch without disruption.

Subscriptions

Teams buy multiple licences to compare.

One interface instead of many tools.

Governance

Inconsistent usage across tools.

Standardised, governance-friendly access in one place.

Keeping up

New models mean new rollouts.

New models can be added as they become available.

Fear of Leakage

Users avoid sensitive topics entirely

Stripped Details

Key context removed = inaccurate answers

Reduced Value

Quality drops, time gets wasted

The Challenge

AI is only useful if teams trust it

In everyday work, teams constantly interact with AI across research, writing, analysis, and decision-making. But when the model itself becomes the product, the first question is no longer the task — it’s which tool to use.

People end up testing multiple AI tools, copying prompts between them, and debating which response is “correct.” Results vary by team and personal preference, and knowledge becomes fragmented across platforms instead of shared.

A scalable AI setup should remove tool choice from daily work — not make it a constant decision.

The Solution

What Changes with Leo

Leo is built to remove friction from everyday AI use. It gives teams access to the best models available, while keeping the experience consistent, controlled, and easy to trust.

Move Faster

Leo automatically selects the best model for each task — whether it’s reasoning, writing, coding, or summarisation. Teams spend less time testing tools and more time getting real work done.

Model Choice Without the Burden

Leo can switch between leading models like OpenAI, Anthropic, and Google Gemini as needed. Switching is automatic in most cases, and manual control is available when a task has specific requirements.

Consistent Outcomes for Everyone

All teams work within the same AI environment, with the same capabilities and standards. This reduces variation, improves trust in results, and creates a shared way of working with AI.

Practical Capabilities

Leo supports multiple AI models, including GPT, Claude, and Gemini, with more options available over time.

Leo can automatically select the best model for the task to save time and improve results.

Leo lets teams switch models easily when a task needs a different strength or capability.

Leo reduces vendor lock-in by keeping your workflows stable even as models change.

Leo provides a unified interface, reducing the need for multiple subscriptions and logins.

Leo supports governance-friendly standardisation, so teams use AI consistently and safely.

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User Experience

How It Feels to Use

Before Leo

Tool choice creates friction

A marketing lead wants a clear narrative draft, but the model struggles with tone and structure.

An analyst needs precise reasoning and summaries, but gets inconsistent results.

An engineer switches tools to get reliable coding help.

Teams end up juggling multiple AI tools, comparing answers, and debating which one to trust.

With Leo

The experience is calmer

People ask normal work questions without worrying about which model to use.

Leo automatically selects the most suitable model for the task — or lets users choose when they want.

Teams get stronger, more consistent outputs without changing tools or workflows.

Work moves forward faster, with less friction and less second-guessing.

Scale with Confidence

Built for trust as models change

Model choice should not weaken governance. Leo keeps the experience consistent for employees and controllable for administrators, even when new models are introduced.

Your teams get the benefit of the latest AI intelligence, while you keep standardisation, privacy, and role-based access in place.