ENSign inOpen console

Who it’s for

The AI products that
feel context-heavy.

TrimLayer is for teams where every model call carries too much history, retrieval, structure or tool output. Bring your own provider account; we make the input lighter.

Find your integration pathReview benchmarks
WHERE SAVINGS APPEAR
Long contextKeep the active evidence
Repeated payloadsSend less on each turn
High-stakes detailVerify or leave unchanged

Use cases

One product layer.
Six clear customer jobs.

The best fit is not a particular model. It is a workflow where useful context is buried inside history, retrieval, structure or repetition.

CUSTOMER SUPPORT SAAS

Keep the case. Lose the old chatter.

Focus long support histories on the active issue without dropping account facts, promised timelines or operational next steps.

  • Lower cost per conversation
  • Faster hand-offs
  • Current issue stays grounded
See how it works
RAG & KNOWLEDGE

Send evidence, not the whole library.

Select the passages that answer the current question while keeping source recovery available for the next follow-up.

  • Smaller retrieved context
  • More focused answers
  • Recovery when needed
See how it works
AGENT WORKFLOWS

Stop paying for the same context twice.

Reduce repeated tool results, previous-agent hand-offs and background context across multi-step agent workflows.

  • Lighter agent chains
  • Less repeated input
  • Scoped recovery paths
See how it works
STRUCTURED AI PRODUCTS

Keep the contract. Trim the payload.

For teams sending large JSON schemas, tool results and structured context with every model request.

  • Schema-aware handling
  • Protected fields
  • Measured input reduction
See how it works
CODE & DEVELOPER TOOLS

Make room for the code that matters.

Reduce surrounding logs, diffs, generated output and repeated instructions while preserving code boundaries and identifiers.

  • Cleaner coding context
  • Less log overhead
  • Safer tool output
See how it works
BYO-KEY AI TEAMS

Keep your provider account.

Add a cost-control layer in front of OpenAI, Claude, Gemini or compatible endpoints without changing who provides the model.

  • Your key stays yours
  • Provider flexibility
  • Usage and savings visibility
See how it works

A good fit

Context is long, repeated, structured or recoverable.

The honest choice

If safety is not proven, the original request still goes through.