INTRODUCING PREAMP
Fewer Tokens.
Better Margins.
AI applications often send more context to foundational models than a task actually needs. PreAmp identifies the evidence needed for the question before it reaches the LLM.
Less context means lower inference cost.
Model-agnostic. Designed to work with existing retrieval and RAG workflows.
PREAMP
Reduce the cost of asking AI questions.
PreAmp sits between your information sources and the foundational model. It narrows the material sent to the model while keeping the source evidence needed to answer the question.
INPUTS
Large text corpus
Documents, knowledge base, retrieval output
PREAMP
Focused evidence
Reduce unnecessary input before inference
MODEL
Foundation model
Less context sent for the same task
Less context
Reduce unnecessary input before inference.
Model-agnostic
Works across foundational models.
Fits existing stacks
Complements retrieval and RAG.
VALIDATION
Up to ~90% less LLM input text
Internal benchmarks have shown up to approximately 90% less input text under tested conditions.
WHAT WE MEASURE: Cost per accurate, complete, evidence-supported answer.
Results vary by corpus, task, model, and deployment.
WHERE IT FITS
Built for context-heavy AI.
PreAmp is built for AI applications that work with large amounts of text.
- Large proprietary text collections
- Frequent information requests
- Long retrieved contexts
- High inference volume
- Subscription or fixed-price economics
- High requirements for answer quality
Potential applications include legal and professional services, intelligence and defense, scientific and technical research, enterprise knowledge systems, and other document-intensive AI products.
Built on research.
Focused on economics.
PreAmp builds on more than a decade of DARPA-funded R&D in language understanding and information processing.
Causerie.ai is bringing that work to commercial and government applications where model cost, scale, and answer quality matter.
We are looking for partners with real workloads to test PreAmp and develop pilots.
CONTACT
See what PreAmp can do with your workload.
If you are building an AI product around large amounts of text, we’d like to hear what you’re working on.