JustSolve AI Engineering Assurance helps you assess whether your AI product is ready to scale safely, responsibly and at enterprise standard.
A working prototype can still fail at scale. AI Engineering Assurance helps you know what is safe, scalable and supportable before you commit bigger spend.
Confirm the foundations your AI product depends on before you scale it.
Check that intelligence is
designed into your architecture, workflows and controls from the start.
Test your AI product against the engineering, testing and review standards it needs to operate reliably.
Receive a readiness scorecard, risk register and clear recommendation that support your next investment decision.
Review system boundaries, integration points, dependencies and deployment assumptions.
Confirm product purpose, user groups, success measures and risk profile.
Check secrets, credentials, permissions, tool access and environment controls through a focused AI security review.
Test whether outputs can be validated against intent, business rules and acceptance criteria.
Assess prompt structure, agent responsibilities, tool access and versioning.
Assess load, latency, rate limits, token usage and cost exposure.
Review logs, metrics, escalation paths, support ownership and incident readiness.
Trace what data enters the workflow, where it is stored and how it is protected.
Review how the product is built, tested, released and maintained.
Confirm accountability, approval paths, auditability and decision rights.
Confirm scope, access, data-handling rules and stakeholder availability.
Map product purpose, architecture, integrations, prompts and support assumptions.
Review your product across all ten lenses and log the evidence behind each finding.
Rank AI security risks and delivery risks, and separate must-fix, should-fix and optimise- later actions.
Present findings to executive and technical stakeholders and hand over every artefact.
We assess the conditions that must be true for AI to operate reliably in the real world, whichever
model or platform you use.
We review Claude Code,
Google AI Studio, ChatGPT
Codex and other tools against
the same readiness conditions.
A structured, independent AI
assurance pack supports your
executive, procurement,
architecture and risk decisions.
Every finding is tied to
evidence and ranked by
severity, likelihood and
business impact.
Each sprint focuses on one
product, workflow or use case
and ends at a clear decision
point.
We start with walkthroughs,
architecture artefacts and
redacted prompts, and agree
deeper access only where
approved.
Every engagement ends with a
Proceed, Remediate, Extend or
Pause recommendation and the
right follow-on route.
Closing the AI execution gap starts with foundations. We help you move from AI ambition to AI-native execution, built responsibly and made to scale.
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An AI risk assessment through AI Engineering Assurance reviews one specific AI product, workflow or use
case before it scales. Enterprise-wide AI governance design sets policies across the organisation and is a
separate piece of work.
Software QA checks that features work as specified. AI assurance also reviews AI behaviour, output
verification, data exposure, monitoring, human review and governance, so it complements your existing QA and
testing.
AI Engineering Assurance surfaces readiness and governance considerations, and it does not provide legal,
regulatory or cyber-security certification. It complements your security, legal and compliance functions.
