Real estate guide
Token compression for real estate AI
Real estate AI platforms process thousands of property listings, each with descriptions, features, pricing, and legal notes. SuperCompress keeps only the properties relevant to your analysis query.
Real estate data is repetitive
Property listings follow templates: "Beautiful 3BR/2BA home in [neighborhood]. Features include [amenities]. Located near [landmarks]. Priced at [amount]." When asking about "homes with pools under $500K," only properties matching those criteria matter. The rest are noise.
Integration
from supercompress import Compressor
comp = Compressor()
def analyze_properties(listings, query):
result = comp.compress(listings, query)
return llm.generate(query, result.compressed_text)Frequently asked questions
Does compression preserve property prices?
Yes. Price data is preserved when relevant to the query.
Can I use it with MLS data?
Yes. Compress MLS listings before sending to any LLM for analysis.
Build with less context
Put compression in front of your next LLM call.
Use the hosted API or run SuperCompress locally. Keep the evidence, drop the token waste, and measure the savings before it reaches your model.