Archive position — measured, not model output
0 likes on Devpost
2,264 of the 7,856 archived projects have more likes, and 5,592 share exactly 0 — so this project's #3,708 place in the like-ranked listing is a tie-break inside that group, not a ranking.
Projects (log scale)
Likes on Devpost. ▲ marks this project's group.
Show the figures
| Likes | Projects | Share of archive |
|---|---|---|
| 0 | 5,592 | 71.2% |
| 1 | 1,758 | 22.4% |
| 2 | 285 | 3.6% |
| 3–4 | 132 | 1.7% |
| 5–9 | 75 | 1.0% |
| 10+ | 14 | 0.2% |
Executive Summary
What the company appears to be
DepositProof is a self-reported tool that processes move-in and move-out photos to generate a timestamped PDF report using GPT-5.6 for change detection. It claims to operate without requiring an API key in its default workflow, relying instead on Codex-generated task files.
What changed
The project was submitted as part of the OpenAI 2026 hackathon and is described as a proof-of-concept tool with no verified traction or commercial use.
Single most important open question
Is there any evidence that DepositProof has been used in real-world rental disputes, or that it has moved beyond a prototype?
What The Product Actually Is
The description states that DepositProof:
- Processes move-in and move-out photos
- Uses GPT-5.6 to match photos of the same room and camera angle
- Flags visible physical changes with severity and bounding boxes
- Allows manual pairing of unmatched photos via drag-and-drop
- Exports a timestamped PDF report including paired originals, annotated findings, and source filenames
- Does not assign blame or repair costs — it organizes what is visible
The tool is described as operating in-memory only, with no server-side storage of images. It uses Codex for its build system, and the default workflow requires no Platform API key.
Evidence Self-reported by author.
Inference The product is a photo-processing tool designed to help resolve deposit disputes through structured visual evidence.
Positioning & Claim Evolution
The description states that DepositProof was inspired by real-world tenant experiences with move-out deposit disputes, where tenants lose deposits not due to lack of photos but due to poor presentation of them — “hundreds of unnamed files, no pairing, no way to show 'this wall, before and after.'”
It positions itself as a solution to this problem by:
- Pairing before/after photos
- Using GPT-5.6 for change detection
- Providing a structured, timestamped PDF output
The tool is described as deliberately not assigning blame or legal conclusions — it keeps the human in control of the record.
Evidence Self-reported by author.
Inference The positioning is rooted in user pain points around evidence presentation in rental disputes.
Target Customer & ICP
The description states that DepositProof targets tenants and landlords involved in move-out deposit disputes, where:
- Tenants often lack a structured way to present their photos
- Landlords have checklists but may not be able to verify tenant-provided images
It is implied that the tool is for individuals or small parties involved in rental agreements, not large property management companies.
Evidence Self-reported by author.
Inference The ICP appears to be individual renters and landlords, with a focus on dispute resolution.
Business Model & Pricing Evidence
The description states:
- The default workflow requires no API key
- An optional Responses API path is available when a key is present
- No pricing or monetization model is described
Evidence Self-reported by author.
Inference There is no clear business model or pricing structure evidenced. The tool may be free to use in its default mode, with optional paid features.
Technical & Delivery Signals
The description states:
- Built using Codex as the build system (not autocomplete)
- Uses FastAPI + Pydantic strict models + vanilla JS + ReportLab
- Implements backend and interface via Codex
- Generates synthetic benchmark images with Codex tools
- Runs browser and PDF verification passes
- Has 18 passing tests, including boundary/PDF/HTTP tests
- Build logs are checked in under codex_log/
- An independent review pass caught a slider-direction bug
Evidence Self-reported by author.
Inference The tool is built with a clear technical stack and testing approach. It was submitted to a hackathon, suggesting it’s a prototype or proof-of-concept.
Traction & Maturity Signals
The description states:
- No revenue, customer or traction data is available
- All demo photos are synthetic and contain no real tenant data
- The tool is described as a hackathon submission
- No live Responses API benchmark is claimed — it's labeled as pending
Evidence Self-reported by author.
Inference There is no evidence of traction, adoption, or commercial use beyond the hackathon submission.
Competitive Context
The description does not mention any competitors. It is unclear whether similar tools exist in the market for managing move-in/move-out photos or resolving deposit disputes.
Evidence Self-reported by author.
Inference No competitive landscape is described or evidenced.
Key Risks & Red Flags
- No real-world usage or adoption: The tool is described as a hackathon submission with no verified users or customers.
- Unverified claims: GPT-5.6 performance is claimed in synthetic benchmarks but not tested in live conditions.
- No monetization model: No pricing, revenue or business model details are provided.
- Limited scope: The tool does not claim to handle legal or financial aspects of disputes — it only organizes visual evidence.
- Self-reported only: All claims are unverified and based on the author's own description.
Evidence Self-reported by author.
Inference The lack of real-world usage, monetization, or competitive analysis raises significant questions about viability.
Diligence Questions To Ask The Founders
- Has DepositProof been used in any real-world rental disputes?
- What is the current status of the optional Responses API? Is it functional?
- Are there any plans to monetize the tool or offer paid features?
- How does the tool handle edge cases, such as poor lighting or low-resolution images?
- Has the team considered legal implications or liability issues with its use?
Investment/Partnership Verdict
The description states that DepositProof is a hackathon submission and no commercial traction, revenue, or customer data is available.
Evidence Self-reported by author.
Inference At this stage, there is insufficient evidence to support an investment or partnership decision. The tool appears to be a prototype with no demonstrated market need or business model. It may have potential if it evolves into a product with real-world adoption and monetization strategies.
Source
Submitted to the OpenAI 2026 hackathon on Devpost. Project home on DevPost.
The analysis above was generated by a language model from the project's own one-line description. It is not independent research and contains no verified traction, revenue or customer data.