Real estate guide
Token compression for lead qualification
Lead qualification AI sends buyer preferences, property matches, and agent notes with every query. Compression keeps only the qualification-relevant data.
Lead data compression
from supercompress import Compressor
comp = Compressor()
def qualify_lead(buyer_profile, matched_properties):
context = f"Buyer: {buyer_profile}\nMatches: {matched_properties}"
result = comp.compress(context, "Qualify this lead")
return llm.generate(
f"Lead qualification:\n{result.compressed_text}"
)Frequently asked questions
Does compression lose buyer details?
No. Only irrelevant preferences are removed. Budget, location, and must-have features are preserved.
Can I qualify leads in real-time?
Yes. Compression adds only ~60ms, making it suitable for real-time qualification.
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.