Onside
ZayReporting workflows
Recurring reports assembled from fragmented source systems, addressed to different stakeholders.
Enterprise AI workforce · deployed · supervised
AI workforce for real operations.
01 · What Rhea deploys
An agentic workforce for your operations.
Rhea replaces manual, repetitive work with AI agents. They do the same work your teams do today, faster, more consistently, and without human bias or fatigue. Where a decision matters, a person stays in the loop.
Not a chatbot, not a platform migration. A workforce that runs inside the systems you already use.
For example
Invoice screening
Incoming invoices analyzed for anomalies and fraud signals; suspicious ones escalate to a reviewer.
Sales ops
Customer onboarding tracked end to end, with stalled accounts and drop-off points surfaced to the team.
Delivery ops
Courier performance analyzed for anomalies, with feedback delivered to the ops team.
Customer feedback
Reviews collected from TrustPilot, Google Maps, and app stores, then summarized with recommendations.
Internal coordination
Status collected, decisions logged, and follow-ups routed across teams.
02 · How it works
No standard pipeline. A workflow built around your process.
We start from how the work actually happens in your organization, then design the workflow and place agents where they replace or outperform manual steps.
01 · Map
Map the process
We study how the work actually moves today: the steps, the systems, the people, and where time and errors accumulate.
02 · Design
Design the workflow
A workflow is built around your process, not a template. Agents take the manual steps; people keep the decisions that matter.
03 · Run
Deploy and improve
Agents run inside your systems, monitored end to end. Efficiency compounds as the workflow expands to the next process.
03 · Cases
Deployments, not demos.
We do not deliver just slide decks and recommendations. Every engagement ends with a workflow running in production, with measurable results.
Chief of Staff agent
Weekly reports for the CEO and CTO on engineering performance, built from GitHub and Jira activity. The findings drove real staffing and process decisions.
−15.4%PERSONNEL COSTS
+40.2%DELIVERY PACE
PM agent
Optimizes product work in Linear, keeps issues and priorities in shape, tracks delivery metrics across the team, flags risks early, and reports to the CEO every week.
WeeklyCEO REPORT
LiveDELIVERY METRICS
04 · Safe to deploy
Built for enterprise and government environments.
Your data stays inside
On-premise or in your private cloud tenancy. Agents run inside your perimeter. Documents, secrets, and internal data never leave your infrastructure.
Local compliance by design
Data residency, personal-data regulation, and sector-specific requirements are part of the deployment architecture, including the standards government-linked organizations are held to.
Your systems, unchanged
Agents work inside the ERP, document stores, and internal tools you already run. We adapt to your processes, not the other way around.
Human control over AI
Decisions that matter pause for human approval. Every agent action is logged, auditable, and observable, so you can always see why something happened.
05 · Commercial path
Sprint. Pilot. Managed ops.
01 · Opportunity sprint
2–3 weeks
We pick one high-value process and ship a working prototype on your real data.
02 · Production rollout
6–8 weeks
The prototype becomes a production solution, deployed in your infrastructure, integrated with your systems, monitored end to end.
03 · Managed agent ops
Ongoing
We keep the workforce improving: monitoring, new capabilities, and expansion to the next processes.
Start with one process.
A working prototype on your real data in 2–3 weeks, then a production solution running inside your infrastructure.
06 · For procurement and evaluation
Common questions.
Where does our data live, and who can access it?
Inside your perimeter. Agents run on-premise or in your private cloud tenancy; documents, secrets, and internal data never leave your infrastructure. Access follows your org structure, and every access event is logged.
How do you handle data residency and local regulation?
Compliance is part of the deployment architecture, not an add-on: in-country hosting, personal-data regulation, and the standards government-linked organizations are held to are addressed during design, before anything runs.
Do we need to change our systems or processes?
No. Agents work inside the ERP, document stores, and internal tools you already run, through their existing interfaces. We adapt to your processes, not the other way around.
What do we get, and how fast?
A working prototype on your real data in 2–3 weeks. If it proves out, it becomes a production solution in your infrastructure within 6–8 weeks, then runs under managed agent ops.
Who is accountable when an agent makes a mistake?
Decisions that matter pause for human approval, so accountability stays with a named person on your side. Every agent action is logged and auditable, so you can always see what happened and why.
Who owns the workflows and the IP?
You own your data, your process definitions, and the outputs. Rhea retains its underlying platform and tooling. Everything built for your processes during an engagement is yours to keep.
Can we exit, and what happens then?
Yes. Engagements are structured per process with defined off-boarding: documentation, process definitions, and audit history are handed over in open formats.