Turn the conversations already captured by your LiteLLM proxy into customer health signals, session stories, and recommended actions. Give product and customer-success teams a clearer starting point for deciding who needs attention and what to improve.
Review health and churn-risk signals alongside the customer’s session history to decide where a closer look would help.
See the goals customers pursued, the obstacles they encountered, and the moments they recovered.
Explore adopted features and successful sessions to identify experiences worth introducing to more customers.
Bring a customer’s health, behavioral profile, session history, and recommended actions into one view. Follow the journey from early friction to successful adoption, then use the suggested next steps to plan a relevant conversation.
A health score and churn-risk tier help focus attention. Session summaries explain the experiences behind those indicators.
Recommended actions connect a proposed follow-up to the behavior that prompted it.
Start with a question about customer health, friction, or adoption. Ask brings together your workspace data and completed analyses, so you can move from a broad pattern to a customer or session worth exploring.
LiteLedger
Add a reachable LiteLLM proxy URL and credential, test the connection, and sync the conversation logs it makes available.
Select customers and an analysis window. LiteLedger uses human messages to build session stories, health signals, and proposed next actions.
Read a customer report, explore shared themes, or ask a follow-up question. Use the evidence to decide what your team should do next.
LiteLedger stores the conversations you sync, with retention settings managed by your workspace admin. Revisit the history you retain to investigate a change in customer experience or run analysis over a different period.
Review spend, volume, and customer activity in one dashboard, with operational measures such as success rate, cache hits, latency, and cost per request. Add analysis views to explore the experience behind those numbers.
LiteLedger
Read health signals, session stories, and proposed follow-up actions. See an example →
Connect human messages to customer and cohort findings. Follow the process →
Give analysis and Ask the documentation that explains your product. Explore Primer →
Configure supported AI providers using your own credentials. Explore cost and processing choices →
Search customers by name or key alias, add recognizable display names, and exclude internal or test accounts from your working customer list. Recognized account-key families are grouped into one customer so related activity can be analyzed together.
Workspace members share workspace data, while admins manage membership and settings. Configure the provider credentials used for analysis and review the data-handling model as part of your evaluation.
Analysis uses the supported provider configuration and credentials you supply.
Manage who joins the workspace and how retained conversation data is handled.
For teams operating AI products through LiteLLM, customer conversations offer a direct view of the experience people are having.
Understand how customers use the product, where they make progress, and which experiences deserve attention.
Investigate recurring friction and connect product decisions to evidence from customer conversations.
Prepare relevant follow-up with a view of the customer’s goals, recent sessions, and suggested next actions.
Submit your work email to request an invitation to LiteLedger.