Autonomous agents built for construction
Not chatbots. Not copilots. True autonomous agents that observe your project data, reason over it, and take action, continuously, without prompting.
How an agent thinks and acts
Every Arlyn agent follows the same five-phase loop, triggered by real project events, not manual prompts.
Trigger
An event fires (a schedule variance, a new document upload, a threshold breach) and the agent wakes automatically.
Observe
The agent pulls live context from connected systems: Procore, Autodesk, ERP, field data, historical project records.
Reason
Using construction-domain LLMs, the agent applies reasoning chains, cross-references policies, and generates an action plan.
Act
The agent executes: drafts a change order, sends a RFI, updates a schedule, flags a compliance issue, all autonomously.
Learn
Every outcome is logged. The agent improves from feedback loops, human corrections, and cross-project pattern matching.
Six categories of specialized agents
Each agent is purpose-built for a specific construction workflow, not a generic AI adapted from another industry.
Document Agents
Process submittals, RFIs, specs, and contracts. Extract, classify, and route structured data automatically.
Scheduling Agents
Monitor CPM schedules, detect float erosion, identify critical path delays, and suggest recovery options.
Financial Agents
Track cost codes, flag budget overruns, draft change orders, and produce WIP reports on demand.
Compliance Agents
Monitor OSHA standards, LEED requirements, and contract obligations. Flag non-conformances in real time.
Procurement Agents
Level bids, score subcontractors, track procurement timelines, and flag scope gaps in proposals.
People Agents
Optimize craft labor scheduling, manage certifications, and surface workforce analytics for foremen.
Why construction AI requires a different approach
Generic AI tools fail in construction because they don't understand the domain. Arlyn agents are trained on construction contracts, schedules, specs, and project data. They know what a schedule float is, what a T&M markup means, and how OSHA 1926 applies to your site.
Construction-domain trained
Our LLMs are fine-tuned on construction contracts, specs, schedules, and project data, not generic text.
Multi-agent orchestration
Agents communicate and hand off context to each other. A schedule agent can trigger a finance agent when delays cause cost exposure.
Always-on monitoring
Agents watch your project data 24/7. You get notified when something needs attention, not after it becomes a problem.
Explainable AI
Every agent decision comes with a reasoning trace. Your team knows exactly why an action was taken and can override it.
Ready to deploy your first AI agent?
Most customers are live with their first agent in under two weeks.