spostrzegawczy.pl
AI-native home inspection company in Poland

Spostrzegawczy turns one inspection visit into three AI-generated buying decisions.

This is not inspection software sold to third parties. Spostrzegawczy is a vertically integrated inspection business where Claude is embedded in the operating workflow, converting structured field input and defect photos into a technical report, a repair estimate, and a ready-to-send negotiation letter.

3 customer deliverables per visit technical report, repair estimate, and negotiation letter
Claude across text and vision structured findings, image analysis, and standardized writing quality
Vertical AI service business in-house inspectors, in-house workflow, and in-house output quality
AI-native inspection operations
Inspection package ready 18/12 Slowackiego Street

12 defects detected, PLN 18,400 in projected repair cost, and a buyer-ready negotiation recommendation generated from the same visit.

Detected issues 12
  • 3 critical
  • 5 medium
  • 4 cosmetic
Negotiation - PLN 18,000

Suggested price reduction generated from defect severity and estimated remediation cost.

Letter to the seller tone: diplomatic

The buyer can reference moisture damage, missing electrical grounding, and a leaking plumbing connection as documented reasons to reopen pricing with the seller.

Why the model matters

The moat is not a prettier PDF. It is the workflow that turns field expertise into repeatable financial outputs.

AI as workflow infrastructure

4 integrated automations

structured synthesis, defect classification, repair pricing, and negotiation drafting

Customer value

technical findings become leverage

the client receives issues, cost impact, and a usable pricing argument in one package

Business moat

operations and model learn together

inspectors, prompts, and output formats stay inside one proprietary service loop

Post-inspection package

A single inspection yields three documents the buyer can act on immediately.

All three outputs are generated from the same structured visit, which keeps the data model consistent and eliminates manual rewriting between inspection, estimation, and negotiation.

Technical report Standardized reporting independent of inspector style
  • defect descriptions
  • repair priorities
  • photo evidence
Technical report

Standardized reporting independent of inspector style

The field inspector captures findings in structure, and Claude turns them into a consistent report that reads like it came from one experienced technical team.

Repair estimate Defects translated into budget impact
  • labor
  • materials
  • risk buffer
Repair estimate

Defects translated into budget impact

Repair pricing makes the inspection financially legible by attaching plausible remediation cost to the issues found on site.

Negotiation letter The highest-value post-inspection artifact
  • price-reduction arguments
  • selectable tone
  • target negotiation value
Negotiation letter

The highest-value post-inspection artifact

The letter frames discovered issues as a professional price-reduction case, grounded in evidence and estimated repair cost.

How the pipeline works

Structured capture in the field, Claude-powered synthesis in the back office, decision-ready outputs for the buyer.

01

Inspectors capture findings inside a guided workflow

Instead of free-form notes, the inspection is structured by rooms, systems, and finish elements. That reduces omissions and creates cleaner input for downstream generation.

02

Claude processes observations and photos as one case file

Written findings and defect photos enter the same pipeline. The model helps classify issues, prioritize them, and describe their likely impact on the transaction.

03

The customer receives technical and financial outputs, not raw notes

The workflow does not end at diagnosis. It ends with a report, a repair estimate, and a negotiation letter that translate condition into an actionable buying decision.

What the buyer and business gain

Customers get clarity before signing. The company gets scalable quality and differentiated economics.

The same system that helps a buyer negotiate also helps Spostrzegawczy standardize output quality, compress turnaround time, and build a service moat that traditional inspection offices lack.

For the buyer

Lower uncertainty at the point of purchase

The technical condition is explained in plain language and the most important defects are ranked by budget impact and transaction risk.

For the negotiation

A stronger basis for repricing the deal

The negotiation letter and repair estimate support the conversation with specifics instead of instinct, opinion, or post-viewing emotion.

For operations

Repeatable quality as volume grows

Standardized field input and document generation make it easier to maintain quality as the inspection team and output volume expand.

Founders with code and construction domain knowledge

The technical stack is credible because it is paired with real inspection and renovation experience.

Spostrzegawczy is building a vertically integrated service with its own product, prompts, inspection process, and field experts. That blend of software and domain knowledge is difficult for a traditional inspection office to copy.

Krzysztof Przybylski, construction engineer and lead inspector
Co-founder and Operations Lead

Krzysztof Przybylski

Construction engineer and lead inspector

12 years of practical residential construction experience. He owns the inspection methodology, defect taxonomy, and cost-estimation credibility behind the customer-facing outputs.

Wojciech Apanowicz, product architect and Claude integration lead
Co-founder and Technical Lead

Wojciech Apanowicz

Product architect and Claude integration lead

13 years of engineering experience, battle-tested B2C founder. He designs the full system, from field data structure and prompt engineering to image analysis and document generation across the report, estimate, and negotiation letter.

Building the operating layer

The MVP is designed to prove one thesis: AI can make a home inspection materially more actionable than the market standard.

The product design is defined. The next milestone is a production MVP that connects field capture, vision analysis, and document generation in one fast inspection workflow.

Why this matters If the output quality is high enough, the AI workflow is not a feature. It is the company. Discuss the MVP