Donna G · AI Engineer & Systems Architect
I build AI systems that earn the right to act.
I build AI systems and automations you can check before anything important happens.
- Automate repetitive work such as enquiries, documents and hand-offs, with a person approving before anything is sent.
- AI assistants that stick to approved facts and say when they don’t know.
- Keep sensitive data protected before it reaches an outside AI service.
Working demonstrations
Try it in your browser
Three working prototypes and six concept labs, all with fictional data. External actions are simulated and labelled; none of them is a production system. They are public demonstrations, separate from the prototypes I’ve built for clients, which stay confidential.
Working prototypes
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Workflow Automation Builder
Set required fields, routing rules and approval for a fictional enquiry, run it, and download the work item as JSON and a readable summary.
Working prototypeSimulated: email, CRM and booking actions
Open the builder: Workflow Automation Builder -
Content Workflow Prototype
Turn a fictional brief into a plan, check a draft's claims against its sources, request revisions and see the gate decision.
Working prototypeNo writing model: sample and template drafts, deterministic checks
Open the prototype: Content Workflow Prototype -
Enquiry Automation Walkthrough
A fictional enquiry goes from intake to human approval to a simulated result. A browser simulation, separate from the AIUNIQ Enquiry Desk application.
Simulated actionsSimulated: email, notifications and CRM updates
Open walkthrough: Enquiry Automation Walkthrough
Concept labs
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Privacy Boundary Lab
Names and emails are swapped for placeholder tokens before text would reach an AI service, then restored on your side.
Local deterministic demoSimulated: the external AI service
Open lab: Privacy Boundary Lab -
Governed AI Run Simulator
Follow a fictional brief to a publishing decision: ready, needs human review, or blocked.
Interactive reconstructionSimulated: the AI stages and reviewers
Open lab: Governed AI Run Simulator -
Independent Review & Evidence Ledger
Simulated reviewers raise findings against evidence, and a person makes the final call.
Fictional simulationSimulated: the reviewers
Open lab: Independent Review & Evidence Ledger -
Reliability and Recovery Lab
Failures, limited retries and recovery from a checkpoint, without doing the same work twice.
Fictional simulationSimulated: the delivery service and its failures
Open lab: Reliability and Recovery Lab -
AIUNIQ Control-Plane Demo
Jobs admitted against a budget, approval gates and operator controls.
Fictional simulationSimulated: jobs, budget units and operators
Open lab: AIUNIQ Control-Plane Demo -
Fleet Operations Lab
Simulates the control behaviour proposed for Multi-Agent Fleet Orchestration on OpenClaw: 5 to 20 agents, dependent tasks, retries, recovery, cost limits and a human approval checkpoint.
Fictional simulationSimulated: the agents, tasks, faults and costs (OpenClaw is not connected; not a benchmark)
Open lab: Fleet Operations Lab
Engineering showcase: prototypes, labs and the projects they relate to All labs, with details and timings
AIUNIQ applications
Applications built for real workflows
AIUNIQ services
What I can build for your business
Discuss an AIUNIQ project Opens an email to Donna. No forms, no prices quoted on this site, and nothing is sent from it.
About
Meet Donna G
Donna is an AI Engineer and Systems Architect who designs and builds AI tools, automation workflows and connected systems around business needs. Her work spans client prototypes, system architecture and implementation, with a focus on reliability, privacy and human oversight.
Proof, not adjectives
Systems I have shaped
Real projects, described honestly: what was built and verified, what was design work, and what is still planned. Open any case study for the full technical detail.
For recruiters
A short review route
Think in flows
Explore the architecture
Choose a system, then inspect each boundary to see what it owns and why it exists.
Choose a stage
Click any node in the architecture to inspect its responsibility and control boundary.
Interactive proof · preview
See a privacy boundary at work
A short preview of the Privacy Boundary Lab: fictional names and emails become placeholder tokens before text would reach an AI service, then are restored on your side. Same engine as the full lab.
Open the full Privacy Boundary Lab All interactive labs Enquiry automation walkthrough
Deterministic tokenization
Demo authorization is assumed in this preview; this is not real authentication.
Not yet protected.
Protected payload will appear here.
Experience
From support to systems
A career shaped by operating real systems, diagnosing failure, and building better boundaries.
Recent engineering
Strategy and data accountability
Earlier experience: operations leadership and IT support
How I contribute
Architecture through acceptance
Hiring, or planning an AIUNIQ project?
Need an AI system—not just an AI feature?
I’m open to AI engineering, orchestration, governance, privacy engineering and technical integration roles, and I take AIUNIQ enquiries for AI engineering and workflow automation projects. Email me or connect on LinkedIn.
donna@dgraciella.co Not yet available
GitHub