TrimLayer FAQ
Clear answers for
every context decision.
Find practical answers about verified optimization, privacy, provider credentials, recovery and rollout before you connect TrimLayer to production traffic.
Clear answers, zero ambiguity
Frequently Asked Questions
Everything you need to know about TrimLayer's security guarantees, token savings, privacy architecture, and drop-in integration.
IntegrationHow does TrimLayer fit into my AI application?
TrimLayer is an optimize-only context layer. Your application sends source context and an optional task to TrimLayer, receives optimized_context, and then makes its own model call using its existing provider credentials. TrimLayer does not call or resell model APIs.
Safety & AccuracyCan context optimization cause hallucination or lose critical facts?
TrimLayer uses evidence-preserving safety gates for numbers, dates, formulas and task-relevant instructions. When it cannot establish a useful safe candidate, it returns the original context unchanged. Applications should still evaluate answer quality and enforce their own consequential domain checks.
Privacy & RecoveryHow is source content handled? Is it used for training?
TrimLayer does not use customer source content for model training and does not store request bodies in usage analytics. Normal optimization is processed transiently and telemetry is content-free. If a customer enables exact recovery, the scoped original is encrypted in a tenant-isolated temporary store and deleted when its short retention period expires.
PerformanceHow does TrimLayer affect end-to-end latency?
Optimization adds processing time, and the net effect depends on source size, task, downstream model and whether recovery is needed. Measure optimization latency alongside returned-token reduction and your model’s end-to-end latency on representative traffic.
Integration & MCPWhat happens if later work needs information that was omitted?
When recovery is enabled, a result can include a short-lived, tenant-scoped recovery ID. Your application or MCP host can request the exact original source when a named missing detail is needed. Include that recovery turn when calculating effective token savings.
EvaluationCan I evaluate savings before using optimized context in production?
Yes. Use the dashboard playground or send representative source-and-query requests to the optimize API. Compare original versus returned tokens, protected outcomes, latency and recovery cost before your application adopts optimized_context in a production model call.
Models & ProtocolsWhere can I use optimized_context?
Use optimized_context with any model, RAG pipeline, agent system, MCP host or internal workflow you control. TrimLayer returns context only; it does not proxy a model request or require a provider-specific protocol.
Structured ContentHow are code repositories, logs and structured JSON handled?
TrimLayer uses structure-aware projection for supported code and document formats instead of crude character truncation. Syntax, related imports, identifiers and protected values are checked before a candidate is accepted. Unsupported or uncertain inputs safely return the original content rather than risking a malformed result.
Our engineering team can evaluate your production traffic and run a tailored context reduction assessment.