Beyond the LangChain ecosystem.
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LangSmith is purpose-built for the LangChain ecosystem. If your entire LLM stack is LangChain, the integration is seamless: prompt playground, annotation queues, dataset management, and detailed trace visualization. We respect that focus. This page is an honest look at where IAPM takes a different approach, where LangSmith excels, and how you can evaluate both.
Any LLM framework. Full application context. One view.
Deep LangChain Integration, Narrow Visibility
What happens when your LLM app outgrows a single framework?
- LangSmith sees the LangChain layer, but production AI applications rarely stay within one framework. You might use LangChain for orchestration, a custom retrieval pipeline, and a fine-tuned model served via vLLM.
- No application-level visibility: LangSmith does not see the API gateway routing requests, the vector database latency, or the service topology your LLM application depends on.
- Proprietary SDK: LangSmith uses its own SDK. If your stack evolves beyond LangChain, your observability instrumentation does not travel with you.
Framework-agnostic. Application-level correlation. No lock-in.
Framework-Agnostic, Application-Level Observability
Works with any LLM framework. Correlates with everything else.
- Built on OpenTelemetry, not on any single LLM framework. IAPM works with LangChain, LlamaIndex, Semantic Kernel, custom pipelines, or any combination.
- Your LLM traces live alongside your application metrics and service topology in a single 3D spatial environment.
- When your LangChain agent slows down, IAPM shows you whether the issue is in the chain logic, the model provider, the retrieval layer, or the application underneath.
No framework lock-in. Application-level correlation.
Architecture: How We Differ
Open standard instrumentation vs proprietary SDK.
LangSmith has the deepest integration with LangChain of any observability tool. The prompt playground, annotation queues, and dataset management make it a strong choice for teams doing active LLM development within the LangChain ecosystem.
IAPM works with any LLM framework via OpenTelemetry. It provides the same deep tracing for LangChain, LlamaIndex, Semantic Kernel, or custom pipelines, and correlates that LLM telemetry with your full application health.
| Aspect | IAPM | LangSmith |
|---|---|---|
| Scope | Application monitoring (APM) + LLM observability | LLM tracing and evaluation (LangChain-centric) |
| Framework Support | Any OTel-compatible framework | LangChain primary, limited support for others |
| Instrumentation | Standard OpenTelemetry SDKs | LangSmith SDK (proprietary) |
| Visualization | 3D spatial topology + web dashboards | Trace trees, limited charting |
| Service Topology | Auto-discovered 3D service map | No service maps |
| Application Metrics | Application metrics via OTel correlated with traces | No application-level metrics |
| Prompt Management | Via codebase workspace (Tessa) | Prompt playground, versioning, hub |
| Annotation / Evaluation | Evaluation via OTel-compatible pipelines | Annotation queues, dataset management, online evals |
| Vendor Lock-in | None. Standard OTel. Change one endpoint to leave. | LangSmith SDK + LangChain ecosystem coupling |
Tessa fixes code. You review it. You own it.
| Capability | Tessa (IAPM) | LangSmith |
|---|---|---|
| AI Diagnosis | Cross-signal anomaly detection with spatial context | No AI diagnosis |
| Codebase Access | Full workspace: read, search, rename, modify | No codebase access |
| Code Fixes | Fixes code in your workspace. You review, you own it. | No code changes |
| Root Cause Analysis | Application-level: LLM + app + dependencies | LLM trace-level only |
| Accountability Model | Human on the loop | Manual debugging by engineer |
AI: Tessa vs Manual Debugging
Human on the loop.
Tessa accesses your codebase workspace, diagnoses from 3D topology, and makes the fix. You review, you own it. When your LangChain agent produces degraded results, Tessa does not just show you the trace. She correlates the retrieval latency with the vector database performance, checks the embedding service health, and proposes a fix in your codebase.
LangSmith helps you find the problem in the trace tree. Tessa finds the problem across your entire stack and writes the fix.
One platform for LLM + application monitoring. One price.
Pricing: Application Observability Value
One platform vs LLM tool + APM tool.
- One platform, not three: IAPM includes LLM observability, APM, and AI diagnosis. LangSmith covers the LLM layer only.
- No framework tax: IAPM works with any LLM framework via OpenTelemetry. No SDK lock-in, no ecosystem dependency.
- Predictable pricing: Nodes x tier price = monthly cost. No per-seat or per-trace charges.
- AI included: Tessa is included in every paid tier. No separate AI add-on to budget for.
| Capability | IAPM | LangSmith |
|---|---|---|
| LLM Observability | Included | Developer free / Plus $39/seat/mo / Enterprise custom |
| Application Monitoring (APM) | Included | Not available (requires separate tool) |
| APM / Distributed Tracing | Included | Not available (requires separate tool) |
| AI Assistant | Included (Tessa) | Not available |
| 3D Spatial Topology | Included | Not available |
| Application Observability Total | $45/node/month (Analyze) | LangSmith + APM tool = multiple bills |
IAPM pricing from immersivefusion.com/pricing. LangSmith pricing from langchain.com/pricing. Verify current pricing before purchase. All prices USD.
You don't have to rip and replace
Already Using LangSmith? Add Application Context.
No rip and replace required.
- Keep LangSmith for LangChain workflows: Prompt playground, annotation queues, dataset management. Add IAPM for application monitoring and cross-signal correlation.
- Complement or replace: Use IAPM alongside LangSmith, or consolidate when ready. Your choice.
- Framework freedom: As your stack evolves beyond LangChain, your IAPM observability evolves with it via OpenTelemetry.
- Exit guarantee: If IAPM is not right for you, change one endpoint URL. Your instrumentation stays exactly the same.
OTel Collector Config
exporters:
otlp/iapm:
endpoint: "https://otlp.iapm.app"
headers:
API-Key: "YOUR-API-KEY"
service:
pipelines:
traces:
exporters: [otlp/iapm]
metrics:
exporters: [otlp/iapm]Standard OTel Collector config. Application and LLM telemetry flow to IAPM. Keep LangSmith alongside if needed.
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