Information & photo collection
Collecting the physical evidence needed to scope and estimate the job — without a truck roll. This step is the most important gap in the competitive landscape. No competitor in our research serves it. This is Treehouse's core differentiated territory.
Homeowner wants to share information about their property and electrical setup so the contractor can give them a real quote. Contractor wants enough information to scope the job accurately before dispatching a tech.Hypothesis
This step is Treehouse's strongest differentiator and the step with the least external competition. No competitor in our Tier A or Tier C clusters serves this step. Kopperfield (Tier D) has a capture plan for panel photo capture and AI data extraction — it is the closest external analogue and the highest-priority company to research in depth.Treehouse internal
How competitors approach this
1 company mapped. Click a company's "View flow" link to see their captured screens.
| Company | What they do | What they automate | Contractor control | FSM relationship | Key strength | Key weakness | Treehouse implication |
|---|---|---|---|---|---|---|---|
KopperfieldView flow → | Electrical design and load-calculation software with a panel photo capture feature — AI extraction of breaker inventory and panel data from field photos. Closest external analogue to Treehouse's Panel IQ. Product interior unresearched.HypothesisSource | Claimed: AI extraction of panel data from photos — breaker inventory, circuit labeling, main service size. Whether this is comparable in accuracy to Panel IQ is unresearched.Hypothesis | Unresearched. Capture plan includes a 'manual-correction' step and 'confidence/error states' — suggests the contractor can review and correct AI output.Hypothesis | Unresearched. Kopperfield's research mission is scoping and permit-ready design output — FSM integration is unclear.Hypothesis | Purpose-built for electrical scoping and design. If the panel photo AI is accurate, it reduces the site visit to confirmation rather than primary data collection.Hypothesis | Product interior fully unresearched. Whether it integrates with any FSM is unknown. The business model and go-to-market are unresearched.Hypothesis | Kopperfield is the highest-priority company to research in depth. If Kopperfield's panel photo AI is accurate and its electrical design output is comparable to Edison, it is a direct competitor to Treehouse's core differentiation. Research mission: how does Kopperfield handle the same data that Panel IQ processes?Hypothesis |
Treehouse read
What Treehouse owns, orchestrates, and defers to the FSM — plus six supporting questions that shape architecture decisions. All entries are hypothesis until validated internally.
Panel IQ — the AI that extracts panel data from homeowner-submitted photos. The guided photo-collection flow. The structured panel record that persists across the journey. This is core Treehouse IP.Treehouse internal
The homeowner photo submission experience (web or SMS link the homeowner opens on their phone). The AI extraction pipeline. Human review for low-confidence extractions.Hypothesis
The job record and customer record. Photo attachments may be stored in the FSM's document management — Treehouse mirrors what it needs but does not own the storage layer.Hypothesis
Panel IQ's ability to extract structured electrical data from uncontrolled field photos — the main service size, breaker inventory, and available capacity that no other consumer-facing tool can produce. This is the core moat.Treehouse internal
Photo upload infrastructure, image storage, SMS/web delivery of the photo request link.Hypothesis
The panel record (main service, breaker inventory, available capacity) is the foundation for load calculation, equipment selection, BOM generation, and permit documentation. It must persist reliably from this step forward.Treehouse internal
The extracted panel record with confidence indicators. A checklist of what photos have been received and what is still needed. A 'scope-ready' flag when enough data has been collected to proceed to scoping.Treehouse internal
AI extraction on photo receipt. Confidence scoring. Notification to the contractor when the extraction is complete or when human review is needed.Treehouse internal
Any extraction with confidence below the threshold. Photos where the panel is inaccessible or the main service is not determinable. Jobs where a physical site visit is required regardless.Treehouse internal
Research detail11-field structured template: contractor workflow, information flows, product outputs, FSM read/write
Homeowner wants to share information about their property and electrical setup so the contractor can give them a real quote. Contractor wants enough information to scope the job accurately before dispatching a tech.Hypothesis
Current state (unresearched): contractor dispatches a tech for a site visit to assess the panel, existing circuits, appliance loads, and physical constraints. The site visit exists to collect information that could, in many cases, be collected remotely.Hypothesis
From the homeowner: photos of the main panel (interior and exterior), breaker labeling, main service size, meter base, appliances to be connected. From the job: property address, job type, any preliminary technical notes from qualification.Treehouse internal
Treehouse's Panel IQ: AI extraction of panel data from photos — breaker inventory, main service size, available capacity. Guides homeowner through photo capture with in-app instructions. Flags ambiguous or missing information for human review.Treehouse internal
Review the AI-extracted panel data. Correct or supplement where the AI is uncertain. Request additional photos if coverage is insufficient. Confirm that the extracted data is sufficient to scope the job.Treehouse internal
Photos where the panel is inaccessible, unlabeled, or the main service size cannot be determined visually. Properties with unusual configurations (multiple meters, split panels, older wiring). Jobs where the physical constraint that matters most is not visible in a photo.Treehouse internal
A structured panel record: main service size, breaker inventory, available capacity, meter location. A set of job-qualifying photos attached to the Treehouse project. A confidence score for AI-extracted values.Treehouse internal
Reads: job record to confirm property address and job type. Writes: photo attachments and extracted panel data to the project record. The FSM job record may be annotated with a summary, but detailed technical data lives in Treehouse's project object.Hypothesis
Panel IQ eliminates the site visit for jobs where panel data is the primary scoping input. Homeowner-guided photo collection works asynchronously — the homeowner can submit photos on their schedule.Treehouse internal
Photo quality and homeowner compliance are the primary failure modes — panels that are inaccessible, unlabeled, or in dark spaces. Some jobs require physical access to scope accurately regardless of photos. Homeowner drop-off at the photo step may be a conversion risk.Hypothesis
This step is Treehouse's strongest differentiator and the step with the least external competition. No competitor in our Tier A or Tier C clusters serves this step. Kopperfield (Tier D) has a capture plan for panel photo capture and AI data extraction — it is the closest external analogue and the highest-priority company to research in depth.Treehouse internal
Open questions
- 01What is the homeowner completion rate for a guided photo-collection flow — how many drop off?
- 02What job types can be fully scoped from photos, and which always require a physical site visit?
- 03How does Panel IQ confidence degrade for older panels, unlabeled breakers, or poor lighting?
- 04What is Kopperfield's approach to panel photo capture and AI extraction — is it competitive with Panel IQ?
- 05Could a Treehouse-provided smart meter reader (hardware) eliminate the photo-quality constraint?
- 06What is the conversion impact of asking for photos at the qualification stage vs. after a site visit is scheduled?