Requirements Analyst
Turn product requirements into structured stories and acceptance criteria.
Making AI work across your business takes more than adding agents. It takes software that can support them, existing systems they can work with, and clear controls over how they act.
ART AI Stack™ brings these capabilities together in a modular framework, configured around your business.
Specialised agents · Coordinated workflows
ART AI Stack™ helps you build modern applications, modernise existing systems and run them in production—with governance and guardrails built in, and every capability shaped around your business.
Connect requirements, architecture, development and testing through agents that share context, work in parallel and bring decisions back to your engineers.
Turn product requirements into structured stories and acceptance criteria.
Review designs, document decisions and assess trade-offs.
Break the build into independently testable units.
Build bounded services with authorisation, audit and tests.
Create interface slices with design tokens and accessibility checks.
Check changes against architecture, requirements and scope.
Turn test cases into verified Playwright specifications.
Generate tests for expected behaviour and regressions.
Assess coverage, mutation results and assertion quality.
Assess logging, secrets, resilience and deployment safety.
Keep technical documentation and runbooks aligned with the code.
Assemble implementation tasks and supporting evidence for delivery.
Named human owners review decisions and approve the work at agreed checkpoints.
Reuse task instructions, code-generation patterns and review checklists, configured for your stack.
Generation · Review · TestingCarry requirements, domain rules and repository knowledge through the build.
Requirements · Architecture · RepositoriesCoordinate parallel tasks, dependencies and feedback, with engineers approving key decisions.
Parallel work · Handover · ReviewConnect agreed models and tools to your repositories, development environment and delivery pipelines.
Models · Repositories · CI/CDDefine access boundaries, review sensitive changes and retain evidence for each release.
Permissions · Security checks · TraceabilityBring senior engineering judgement and agent execution into one delivery process, configured around your product and technology stack.
Connect sources, transform and validate data, and deliver reliable pipelines, warehouses and real-time streams for your applications and AI workloads.
Agent-driven migration from legacy source to target repository, with human approvals and traceability throughout.
Specialised roles, coordinated around each work unit
Sequences the work and enforces approval gates.
Maps the source, dependencies and open questions.
Interprets existing system behaviour and business logic.
Documents the rules the rebuild must preserve.
Plans the target design and work-unit implementation.
Builds the target implementation from approved inputs.
Challenges generated code against scope and rules.
Adds domain critique during implementation review.
Preflight validation and source preprocessing run as scripted steps. Testing and integration follow the agreed delivery pipeline.
Plan a modernisation programme around the applications, data and business rules you need to carry forward.
Specialised agents and senior practitioners working across your operations, connected to your systems and governed by your rules.
Gather signals, requests and information
Investigate and determine the next action
Execute approved tasks and escalate exceptions
Use outcomes to refine the workflow
Answers before tickets
Zendesk Jira Service Management + Rovo Freshservice
First human response
Datadog PagerDuty incident.io Rootly
Engineers investigate and resolve
Coralogix Grafana ClickHouse Raygun
Ongoing reliability across every level
Prometheus AWS Azure Argo CD
Start with a defined operational process. Connect the systems, agree approval points and establish how quality and outcomes will be measured.
Discover where AI is used, apply controls to how it operates and keep oversight as systems evolve. Cybersecurity and enterprise risk controls support every layer.
Monitoring & observability · Human oversight · Regulatory alignment & evidence
AI security testing · Model lifecycle approvals · Data governance & privacy · Guardrails
AI risk register · Shadow AI inventory · Vendor due diligence
Controls, assessments and decisions mapped to requirements for review.
Models, vendors, use cases and treatment actions kept together.
Security monitoring with a defined incident-response path.
A clear view of risks, control gaps and actions that need attention.
Define the controls, expertise and ongoing support your business needs.
Our services provide the team and delivery engagement. ART AI Stack™ is the framework of specialised agents, reusable workflows and controls that supports that work. The approach is configured for each engagement.
We start by assessing the systems, data and interfaces you already use. The integration work and any changes needed are agreed around the selected workflow.
We use code analysis and business-rule discovery to understand the existing system, then plan migration in manageable stages. Behaviour comparisons, testing and human review help validate the replacement before cutover.
Yes. We can define one bounded use case, agree its inputs, approval points and success measures, and evaluate it before expanding.
Your team owns business policies and decisions. We define where agents can act, when they must escalate and which actions require explicit approval.
We agree acceptance criteria, test representative cases, assess integration and data requirements, and review quality and controls before deployment.
Deployment, licensing, ownership and handover requirements are agreed for the engagement. We clarify what is reused, what is built for you and how it will be operated.
Bring us a product, a system to modernise or a workflow to improve. We’ll help define the scope, controls and measures of success.