Finance optimization
Token compression for financial AI
Financial documents are long, structured, and every number matters. Token compression preserves all financial figures while removing boilerplate disclosure text.
Financial context challenges
Financial AI applications process: regulatory filings (10-K, 10-Q reports), transaction histories, compliance documentation, audit trails, and customer financial profiles. These documents are typically 5,000-50,000 tokens each.
Without compression, a financial analysis query across 5 filings could cost $0.50+ per call in GPT-4o input tokens alone.
Savings example
| Document Type | Original Tokens | Compressed | Savings |
|---|---|---|---|
| 10-K Filing | ~15,000 | ~2,250 | 85% |
| Transaction history | ~8,000 | ~1,200 | 85% |
| Compliance report | ~5,000 | ~750 | 85% |
Frequently asked questions
Does compression preserve exact financial figures?
Yes. SuperCompress selects original lines, never rewrites numbers.
Can I use this with SEC filing analysis?
Yes. Compress filings 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.