Layer 01
SEE — Operational Intelligence
Connect business data into dependable dashboards, scorecards, briefs, and attention signals so leaders and teams know what is happening.
AEC adoption methodology
The intelligent operating layer between information and action
Intelligent Operations is the deliberate design of connected information, workflows, decision systems, automation, and supervised AI agents that help an AEC firm understand what is happening and move appropriate work forward.
The Model
SEE → ACT → IMPROVE
Visibility is useful when it informs action. Action becomes more valuable when outcomes improve the next decision.
Layer 02
ACT — AI Operations
Use integrations, rules, automation, approvals, and supervised agents to help appropriate work move through the organization.
Layer 03
IMPROVE — Continuous Learning
Measure outcomes, exceptions, capacity, adoption, cost, and agent performance, then use that evidence to improve the system.
The learning loop
Data
Intelligence
Decision
Action
Outcome
Learning
01
Start with the operating reality
Sunrise maps the work as it actually happens—including handoffs, exceptions, imperfect data, decisions, and professional constraints. Formal Discovery is paid work within the Blueprint engagement.
- Workflows, systems, data, and recurring decisions
- Bottlenecks, duplicated work, reporting, and manual coordination
- Authority, approvals, risk, data boundaries, and measurement
02
Build the right layer
Approved Blueprint priorities become focused implementations. A build may combine operational intelligence, connected workflow, AI Operations, and governance; not every problem needs every capability.
- Dashboards, scorecards, alerts, briefs, and data connections
- Integrations, workflow redesign, synchronization, and approval flows
- Supervised agents with explicit access, authority, and escalation
03
Learn from use
The operating layer becomes more valuable when actual outcomes inform the next decision. Sunrise reviews evidence before expanding automation or agent authority.
- Capacity, cycle time, quality, adoption, cost, and business outcomes
- Exceptions, failures, human interventions, and trust signals
- Workflow, dashboard, model, permission, and governance changes
Example Use Cases
Supervised agents for real AEC operating work
These examples show the kinds of workflows Sunrise can assess, design, pilot, and build. They are not claims that every agent is a completed product or production-proven client deployment.
Opportunity / RFP Intake
Example use case: collect, classify, summarize, and route inbound opportunities for review.
Proposal Support
Example use case: research, draft, assemble, and track proposal work with human approval.
Project Setup
Example use case: prepare records, check readiness, and coordinate approved project-opening steps.
Executive Intelligence
Example use case: compile operating signals into a concise brief with sources and attention items.
Project Status
Example use case: collect updates, identify missing information, and draft a review-ready status summary.
Knowledge & Coordination
Example use case: retrieve approved knowledge, prepare documents, and route routine internal work.
A defined starting point
Agree on the problem before designing the system.
An introductory conversation establishes fit and enough context for a proposal. Formal Discovery begins after a signed engagement and is part of the paid Blueprint.
Lead→Qualification→Opportunity→Proposal→Signed Engagement→Discovery→Blueprint→Build→Refine
Begin with Clarity
What operating problem is worth understanding properly?
A focused qualification conversation can determine whether a paid Blueprint is the right first engagement.