What it sells
LLM context compression for better accuracy
Business model breakdown
Buyer: who owns the budget?
UnverifiedAI/ML engineering lead or head of platform at companies with large LLM token spend.
Trigger: what makes them buy now?
High LLM bills and latency from long prompts that carry far more tokens than the model uses.
Workflow: what inputs become what output?
pip install the SDK, send long context plus the query to the compression API, get back a query-aware compressed context, then pass it to the LLM; includes cost receipt and playground.
Economics: what it saves and how it charges
Value claim: up to 90% fewer tokens, avg 10x compression, up to 226x in demo, +3.7pp accuracy uplift; example Boeing 10-K query $0.263 to $0.037.
Distribution: how it reaches customers
Developer-led: pip SDK, docs and playground, with book-a-call for enterprise; cloud API or on-prem in customer VPC.
Funding history and coverage
| Round date | Stage | Amount | Investors | Source |
|---|---|---|---|---|
| — | Y Combinator Winter 2026 | — | Y Combinator | ycombinator.com |
Profiles summarize public reporting and company websites. Business-model notes are MaxBC's reading of that material, not confirmed facts; unknowns are left blank rather than guessed. Updated 2026-10-12.