Engagement clarity

Start with a diagnostic. Make the next decision clearer.

Four defined entry points for technical teams. Each answers a specific question before a larger implementation—not an open-ended retainer.

Fitzroy technology assessment and architecture reference illustration
Where we help

Agree the evidence, scope, and controls first.

A technical engagement should have a defined question, named owners, documented access boundaries, and outputs that support a decision.

Written scope and acceptance criteria

Evidence and assumption tracking

Authorized access and approved tools

Named decision owners

Explicit deliverables and exclusions

A readout before the next commitment

Typically two working weeks

Cloud expense & reliability diagnostic

What drives spend, and which changes can reduce it without creating production risk?

What we need

Billing exports, workload inventory, architecture diagrams, utilization evidence, and an engineering-owner readout. Read-only access where sufficient.

Scope boundaries

No production changes, purchase commitments, or guaranteed savings. Implementation is separately scoped.

Outputs to agree

  • Cost-driver baseline and ownership gaps
  • Architecture and utilization findings
  • Assumption-based savings scenarios
  • Prioritized backlog with validation and rollback gates

Typically two working weeks

Backend architecture diagnostic

Which dependencies, APIs, or operational risks are limiting delivery and reliability?

What we need

Service inventory, selected code and API documentation, incident evidence, dependency maps, and stakeholder interviews. Credentials and personal data are not needed for initial scoping.

Scope boundaries

A diagnostic is not a penetration test or implementation engagement. Load testing and code changes require explicit scope.

Outputs to agree

  • Current-state service and dependency map
  • Evidence-led reliability and performance findings
  • Sequenced modernization options
  • Acceptance criteria and implementation roadmap

Typically two working weeks

AI production-readiness diagnostic

Can this use case operate safely and usefully inside the real workflow?

What we need

Workflow owners, model/provider choices, representative approved examples, integration dependencies, and existing evaluation criteria.

Scope boundaries

No client material goes to an AI provider without agreed authorization. A review does not certify regulatory compliance or guarantee model quality.

Outputs to agree

  • Use-case and dependency assessment
  • Evaluation and human-review plan
  • Data-handling and provider-control questions
  • Go / revise / stop recommendation with a production roadmap

Typically one to two working weeks

Robot-learning feasibility review

Is a simulation-trained policy appropriate for this robot, task, and operating domain?

What we need

Robot specifications, task requirements, available simulation assets, control interfaces, success metrics, and physical safety constraints.

Scope boundaries

Factory and household use cases remain separate programs. Training, hardware trials, and safety qualification are not included unless explicitly agreed.

Outputs to agree

  • Domain-specific feasibility assessment
  • Simulation and reward-design requirements
  • Evaluation and sim-to-real risk plan
  • Training and deployment options, including when not to proceed

Duration is an indicative working window, subject to access and stakeholder availability. Each engagement is quoted after scoping; the signed SOW determines the fee, outputs, exclusions, milestones, and acceptance criteria. Implementation and ongoing support are separate decisions.

Start with Fitzroy

Define the next decision before the next build.

Discuss the system question and the information available. Scope, fee, timing, and contractual terms are agreed before kickoff.