Pricing

Start with one workflow. Scale to an AI workforce.

Begin self-serve with a Team plan and shared workspace credits, then move to a custom enterprise engagement when you need on-prem GPU, deep integrations, and SLAs.

The Team plan scales by monthly credit volume. Enterprise pricing depends on deployment model, number of agents, integrations, security requirements, model usage, and support level — scoped around measurable business value.

4ways to begin
3deployment options
Day onegovernance and controls
Customenterprise scope

Plans

Simple pricing that scales with your usage.

Start with a workspace agent, pick the monthly credit volume your team needs, and move to enterprise scale whenever you are ready.

Team

£40/ month

Shared workspace credits
Get started
  • Role-based agent across your approved tools
  • Persistent workspace knowledge and context
  • Integrations and tool execution
  • Scheduled tasks, reports, and check-ins
  • Human approval controls and audit log
Enterprise

Custom

Flexible pricing for scale

Contact sales

Everything in Team, plus:

  • Invoicing and custom billing terms
  • Security review support and DPA
  • SLA and priority support
  • Dedicated onboarding and tailored limits
  • On-prem or private GPU deployment option

How credits work

Credits are model costs, passed through.

No markup on what the models charge — and smart caching brings the cost down further.

No markup on model costs

Every credit maps to what Anthropic, OpenAI, and other providers actually charge. There is no platform fee layered on top — you would pay the same going direct.

Smart caching cuts your bill

BlueMouse caches context and reuses results across tasks. Repeated workflows cost fewer credits than calling the models fresh every time.

Automations scale with frequency

Scheduled automations (crons) run on credits too, so how often they run is what drives the cost. You set the cadence.

Your whole team gets an analyst, an ops lead, and an engineer. For the price of lunch.

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Enterprise engagements

How we deliver beyond the Team plan.

When you outgrow self-serve credits, these engagements take you from first workflow to a managed AI workforce — each scoped around measurable business value.

Workflow Discovery

Best for companies that want to identify where AI agents can create value.

  • Workflow analysis
  • Automation opportunity mapping
  • Deployment recommendation
  • Pilot proposal

AI Agent Pilot

Best for teams that want to test one high-impact workflow.

  • One AI agent prototype
  • Test workflow design
  • Human approval flow
  • Performance review

Enterprise Deployment

Best for organizations ready to deploy production AI agents.

  • Production architecture
  • Multiple agent workflows
  • System integrations
  • Monitoring dashboard

Managed AI Workforce

Best for companies that want continuous support, improvements, and expansion.

  • Agent monitoring
  • Workflow improvements
  • Usage reporting
  • Governance reviews

GPU and Hosting Options

For teams that need on-premise GPU, dedicated off-site GPU, managed private cloud, or hybrid deployment support.

Token and Model Usage

For commercial APIs, cost depends on token usage, provider pricing, model choice, data handling, and throughput needs.

Cost factors

What affects AI agent pricing?

Workflow and integration complexity

Pricing changes with the number of agents, data sources, system integrations, fine-tuning needs, approval flows, dashboards, and support level.

Infrastructure and model choice

On-premise GPU, private cloud, dedicated off-site GPU, and commercial API usage each create different cost and control profiles.

Right-sized scope

Find the right plan for your first workflow.

We will help you estimate the effort, deployment model, operating cost, and expansion path before you commit.