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Clyvel

© 2026 Clyvel

Operate

AI GatewayRoute and control every model request.ObservabilitySee every request, token, error and latency signal.ReliabilityIncidents, provider health, latency and failures.

Analyze

Costs & FinOpsUnderstand spend, budgets and cost allocation.OptimizationFind measurable savings across models and routing.

Control

GovernancePolicies, roles, approvals and audit controls.Clyvel AIAsk what changed, why it happened and what to do next.

One platform for production AI operations.

View all products
EngineeringDebug production AI traffic from one operational layer.Platform teamsStandardize routing, providers and reliability controls.FinOps & FinanceControl AI spend, budgets and optimization outcomes.Security & GovernanceApply access, policy and audit controls at scale.
Pricing
All integrations

LANGCHAIN INTEGRATION

LangChain LLM Observability, Cost Monitoring and Gateway Integration

LangChain applications can coordinate prompts, models and tools while the actual provider calls remain distributed across the runtime. Clyvel focuses on the model request boundary: route supported traffic through the Gateway, then inspect provider, model, latency, tokens, status and cost evidence in one production view.

Start with Clyvel Explore the AI Gateway

WHEN THIS FITS

A practical production use case.

LangChain applications that use supported OpenAI-compatible model clients.

Teams that want model-request telemetry alongside application or agent traces.

Platform owners consolidating AI cost and provider evidence across several LangChain services.

CONNECTION PATH

Connect the model request layer, then verify evidence.

01

Identify the model client used by the chain

Start with the component that actually sends the provider request. Clyvel does not need to replace the LangChain orchestration layer to observe supported model traffic.

02

Point supported model traffic at the Clyvel Gateway

Use the gateway endpoint and Clyvel workload credential for the compatible model client while keeping provider credentials managed behind Clyvel.

03

Correlate request evidence with application behavior

After a test run, inspect model, provider, latency, tokens, status and cost. Use that request evidence alongside your LangChain-level execution context when debugging a workflow.

OPERATIONAL OUTCOMES

What changes once traffic is visible.

Read the LLM observability guides
01

Provider and model evidence for production LangChain traffic.

02

Request-level cost and latency visibility across applications.

03

A shared gateway layer for routing, reliability and governance as usage grows.

FAQ

Integration questions.

Is Clyvel a replacement for LangChain tracing?

No. LangChain-level traces explain orchestration and application execution. Clyvel focuses on the production AI request layer, including model, provider, tokens, latency, status and cost evidence.

Can Clyvel work with LangChain without changing the whole application?

The intended path is to route the supported model client through the Clyvel Gateway rather than replacing LangChain itself. Validate the specific client and features your application relies on before production migration.

LangChain documentation

NEXT STEP

Connect one workload before expanding the rollout.

Start with a controlled request, confirm that operational evidence is trustworthy, and only then move more production traffic or add routing and reliability policy.

Open Quickstart View pricing