AI & Automated Systems Disclosure
AI & Automated Systems Disclosure
Effective Date: September 6, 2026 Version: 1.3 Last Updated: September 6, 2026
Estimatics is committed to transparency regarding the artificial intelligence and automated systems embedded in the Platform. This disclosure describes which AI technologies are used, for what purposes, what their limitations are, and how outputs should be interpreted by professionals.
1. Purpose of This Disclosure
Estimatics serves professionals in the U.S. property insurance and restoration industry — an environment where documentation accuracy, defensibility, and professional accountability are paramount. AI-assisted features accelerate workflows, but they do not replace professional judgment. This document ensures users have a clear and accurate understanding of how AI operates within the Platform.
2. AI Systems and Providers
2.1 OpenAI
Estimatics uses models provided by OpenAI for:
- Photo damage detection — identifying and classifying damage types in field photographs
- Photo classification — proposing an area tag and a capture intent for uploaded media
- AI Walkthrough findings — extracting structured observations from guided video inspections
- Policy extraction — parsing insurance policy documents into structured coverage data
- Building-code context — retrieving local code requirements by ZIP and damage type as background context for analysis
Models used: GPT-4.1 (vision and analysis tasks), GPT-4.1-mini (classification and volume tasks).
2.2 Anthropic
Estimatics uses models provided by Anthropic for:
- Scope generation — converting damage findings into structured line-item scopes
- Report narratives — composing the Executive Summary, Damage Findings and Cause & Origin sections of a report
- Inspection narratives — summarizing inspection findings in human-readable form
- Document extraction — parsing non-policy documents (carrier estimates, carrier letters, mold assessments and clearances, inspection reports, estimate invoices) into structured data
- AI Copilot — answering job-specific questions in the context of the open job
- In-app AI assistant — answering user questions about the Platform
Models used: Claude Opus 4.8 (narrative and reasoning tasks), Claude Sonnet 4.6 (scope and code tasks), Claude Haiku 4.5 (fast conversational tasks).
2.3 Google
Estimatics uses models provided by Google for:
- Regional pricing context — assembling regional cost signals for estimate pricing
- Property lookups — supporting property attributes such as year-built context
Models used: Gemini 2.5 Pro and Gemini 2.5 Flash.
2.4 Perplexity
Estimatics uses Perplexity for live web retrieval to support regional pricing and property/year-built lookups. When these features run, relevant query context (for example, a property address or pricing question) is sent to Perplexity, a third-party web-search provider, which retrieves information from the live web.
Models used: Sonar Pro and Sonar.
2.5 Provider Selection Architecture
Estimatics operates a proprietary AI Provider Router that selects the optimal model for each task based on accuracy requirements, cost efficiency, and capability. Model assignments are updated as new frontier models are released. This document reflects the current state as of the last updated date above.
3. AI Features by Platform Tier
Tiers apply per seat, not per account: a Field Inspector seat on a CERTIFY account has FIELD-tier AI.
| AI feature | FIELD | SCOPE | CERTIFY |
|---|---|---|---|
| AI photo analysis (damage findings) | ✓ | ✓ | ✓ |
| AI Scope Generation | ✓ | ✓ | ✓ |
| Regional pricing lookup | ✓ | ✓ | ✓ |
| Policy document extraction | ✓ | ✓ | ✓ |
| Executive Summary section | ✓ | ✓ | ✓ |
| AI Narrative (Damage Findings section) | — | ✓ | ✓ |
| AI Copilot | — | ✓ | ✓ |
| Document extraction, non-policy types | — | ✓ | ✓ |
| Cause & Origin section | — | — | ✓ |
Independently of plan, every AI feature is disabled when the account's billing state does not permit AI use — an unconfigured, paused, past-due or cancelled account.
4. How AI Processes Your Data
4.1 Image Analysis. When you upload photographs to a job, the Platform may transmit those images to OpenAI's API for damage detection and classification. Images are processed transiently — they are not retained by OpenAI for model training under our enterprise data processing agreements.
4.2 Text and Scope Generation. Structured data from your inspection (damage findings, property dimensions, area tags, material types) is transmitted to Anthropic's API to generate scope line items and narrative text.
4.3 No Training on Your Data. Under our agreements with OpenAI, Anthropic, and Google, your Content (photographs, property data, scope items) is not used to train or fine-tune their AI models. Note that pricing and property lookups use live web retrieval: when those features run, query context (such as a property address or pricing question) is sent to Perplexity, a third-party web-search provider, to retrieve current information from the live web. For those specific lookups, we do not represent that your query context never leaves our providers' systems.
4.4 Data Residency. API calls to our AI model providers are processed on infrastructure in the United States. Live web-retrieval queries sent to Perplexity are handled by that provider's own infrastructure and the public web sources it consults.
5. Accuracy and Reliability
5.1 Known Limitations
AI damage detection may produce false positives (finding damage where none exists) or false negatives (missing damage that is present). Accuracy is affected by:
- Photo quality, lighting, and angle
- Damage type and severity
- Similarity to training data distributions
- Obscured or partially visible damage
5.2 Geometry
Interior geometry — floor plans and per-area dimensions — is produced by on-device LiDAR scanning on supported iPhone and iPad hardware. It is a measurement, not an AI inference, and it is not generated by any of the model providers named above.
Scan accuracy varies with the device, the operator's coverage of the space, lighting, reflective and transparent surfaces, and the geometry of the room itself. Dimensions produced by a scan are a starting point and should be verified before being relied on for a scope, an estimate, or a submission. Estimatics does not publish a guaranteed accuracy figure for LiDAR-derived dimensions.
Geometry on the platform is interior only. Estimatics does not produce roof measurements, roof sketches, or any other geometry derived from satellite, aerial, or drone imagery, and no dimension shown in the platform originates from those sources.
5.3 Scope Generation Limitations
AI-generated scopes are based on visual evidence submitted. They may not capture:
- Concealed damage not visible in photographs
- Code-required items not triggered by visible damage
- Regional material or labor variations not reflected in current pricing data
6. Human Review Requirement
All AI-generated outputs require professional review before use in any official claim submission, report, appraisal, or legal proceeding.
The Platform is designed to assist licensed professionals — not to replace their judgment. AI outputs are starting points. The professional using the Platform bears responsibility for the accuracy and completeness of any work product derived from AI features.
7. Automated Decision-Making
Estimatics does not use AI to make fully automated decisions that significantly affect user rights without opportunity for human review. All AI outputs in the Platform are presented as recommendations or drafts that require explicit user review and action before being finalized or submitted.
8. Evidence Integrity and AI
Estimatics records a per-file SHA-256 integrity hash for media as it arrives, together with the file's capture metadata, and writes an evidence event log of what happened to it. This applies on every plan, including FIELD — it is not a paid feature. It supports:
- Recording the state of a file at the time it reached the Platform
- Detecting whether a file has been modified after its hash was recorded
Evidence integrity concerns the underlying file, not the AI's interpretation of it. AI findings are recorded as a statement of what the model observed at a point in time. They are not certified, not verified, and carry no integrity guarantee of their own — Section 6 applies to them in full.
9. Transparency Commitment
Estimatics will update this disclosure when:
- We add new AI capabilities or use cases
- We change AI providers or model tiers
- We change our data processing agreements with AI providers
- Material limitations or accuracy changes are identified
10. Contact
Questions about our AI systems:
Estimatics, Inc. legal@aiestimatics.com aiestimatics.com/legal/ai-disclosure
Questions about this document? legal@aiestimatics.com
