AI OS for Public Workflow Automation
Budget: $250 – $750 USD
The company is civic.ai
Our city-focused “AI Operating System” has one overriding goal: accelerate municipal workflows by automating the repetitive administrative tasks that slow public servants down. I already have the concept, local data access, and a clear roadmap; what I need now is the engineering muscle to turn that vision into a working, extensible platform.
The system must ingest diverse local datasets (permits, 311 tickets, budget ledgers, council minutes, etc.), normalise them, and expose a streamlined, chat-style interface that any department can use. Task automation sits at the core: think auto-generated agenda briefs, instant form validation, or automatic routing of routine approvals. By capturing each step we also preserve institutional memory, so future staff can trace why a decision was made without digging through email chains.
Key deliverables
• Data connectors that pull from our existing APIs, CSV exports, and legacy databases in near-real-time.
• A modular automation engine that lets non-technical staff define or tweak administrative workflows through a simple UI.
• A conversational layer (Python + FastAPI or similar) that surfaces both insights and one-click actions.
• Marketplace hooks—secure endpoints and SDK stubs—so third parties can publish add-on tools without touching the core codebase.
Acceptance criteria
• At least three high-volume administrative processes fully automated end-to-end (e.g., purchase-order approvals, leave requests, meeting-minute summaries).
• System latency under two seconds for standard queries on a dataset of 1m+ records.
• Role-based access controls and audit logging that meet typical municipal compliance requirements.
If you’ve built SaaS automation platforms, leveraged LLMs with city-scale datasets, or shipped secure public-sector software, I’d love to get your thoughts on architecture, tech stack, and realistic milestones so we can move quickly from prototype to pilot deployment.
Name is civic.ai.
Our city-focused “AI Operating System” has one overriding goal: accelerate municipal workflows by automating the repetitive administrative tasks that slow public servants down. I already have the concept, local data access, and a clear roadmap; what I need now is the engineering muscle to turn that vision into a working, extensible platform.
The system must ingest diverse local datasets (permits, 311 tickets, budget ledgers, council minutes, etc.), normalise them, and expose a streamlined, chat-style interface that any department can use. Task automation sits at the core: think auto-generated agenda briefs, instant form validation, or automatic routing of routine approvals. By capturing each step we also preserve institutional memory, so future staff can trace why a decision was made without digging through email chains.
Key deliverables
• Data connectors that pull from our existing APIs, CSV exports, and legacy databases in near-real-time.
• A modular automation engine that lets non-technical staff define or tweak administrative workflows through a simple UI.
• A conversational layer (Python + FastAPI or similar) that surfaces both insights and one-click actions.
• Marketplace hooks—secure endpoints and SDK stubs—so third parties can publish add-on tools without touching the core codebase.
Acceptance criteria
• At least three high-volume administrative processes fully automated end-to-end (e.g., purchase-order approvals, leave requests, meeting-minute summaries).
• System latency under two seconds for standard queries on a dataset of 1m+ records.
• Role-based access controls and audit logging that meet typical municipal compliance requirements.
If you’ve built SaaS automation platforms, leveraged LLMs with city-scale datasets, or shipped secure public-sector software, I’d love to get your thoughts on architecture, tech stack, and realistic milestones so we can move quickly from prototype to pilot deployment.
Name is civic.ai.
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