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AI Copilot — Your Inspection Assistant
How to use the AI Copilot to ask questions about your job, get contextual analysis, and receive AI-powered guidance during the inspection process.
4 min read
AI Copilot — Your Inspection Assistant
The AI Copilot is a conversational assistant built into the Analyze module. It understands the full context of your job — photos, findings, property details, insurance information, and notes — and can answer questions, provide analysis, and help you draft documentation. Think of it as a knowledgeable colleague who has already reviewed every piece of data in the job.
AI Copilot is available exclusively on the CERTIFY plan.
Where to find it
- Open a job on the web dashboard
- Navigate to Analyze → Copilot
- The chat interface opens with your full job context already loaded
If you are on the FIELD or SCOPE plan, the Copilot tab is visible but displays an upgrade prompt. No job data is sent to the Copilot until you have an active CERTIFY subscription.
What the Copilot knows
The AI Copilot has access to everything associated with the current job:
- Photos and media — all images uploaded to the job
- AI findings — every damage finding generated by AI detection or walkthrough extraction
- Manual findings — any findings you added yourself
- Property details — address, property type, year built, construction type, square footage
- Insurance information — carrier, policy type, date of loss, and any policy context you provided
- Notes and annotations — all notes attached to the job or to individual photos
- Narrative report — if one has been generated
This context means you can ask specific, detailed questions without re-explaining the job.
Example questions
Here are practical questions you can ask the Copilot:
- "What damage types were found on this job?"
- "Is the damage on the north elevation consistent with wind?"
- "What building codes apply to this property for roof replacement?"
- "Summarize the inspection so far in three paragraphs."
- "How many high-severity findings do I have?"
- "What areas of the property have not been photographed yet?"
- "Draft a scope of work summary for the carrier."
- "Compare the damage patterns on the front and rear elevations."
The Copilot responds based on your actual job data — not generic information.
Multi-turn conversations
The Copilot maintains conversation history within a session. You can ask a follow-up question that builds on a previous answer:
You: What damage was found on the roof?
Copilot: Three findings on the roof: two high-severity hail impacts on the main roof field and one moderate wind-lifted shingle on the south slope...
You: Is that consistent with the reported date of loss weather event?
Copilot: Based on the date of loss and the damage patterns observed...
This makes it practical to work through an analysis step by step without repeating context.
Use cases
- Quick analysis questions — get instant answers about your findings without scrolling through cards
- Code compliance checks — ask about local building codes, material requirements, or installation standards relevant to the property
- Report drafting assistance — ask the Copilot to draft specific sections of your report using the job data
- Consistency checks — ask whether the observed damage patterns align with the reported cause of loss
- Pre-submission review — before submitting to a carrier, ask the Copilot to identify any gaps in your documentation
Plan availability
AI Copilot is a CERTIFY plan exclusive feature. Users on FIELD and SCOPE plans can see the Copilot tab but cannot send messages. Upgrading to CERTIFY unlocks the full conversational interface immediately.
AI Damage Detection — How Findings Work
Understand how AI findings are generated from your inspection photos.
AI Narrative Report
Generate a professional written summary from your findings.
AI Walkthrough — Guided Inspection Narration
Narrate your inspection and let the AI extract findings from your voice.
Last updated: April 2026 · Questions? Use the Resources panel in the app or email support@aiestimatics.com
Last updated: April 2026 · Feedback on this article