STRATEGIC TECHNOLOGY PARTNER · LANGFUSE
Instrument, evaluate and operate LLM-powered applications with Langfuse. Bassirah aligns traces, feedback, prompts and quality measures with enterprise development and governance workflows.
Langfuse is one of Bassirah’s Strategic Technology Partners. Our relationship is subject to the applicable Langfuse program and agreement. Implementation scope, resell rights and support entitlements are confirmed in each customer engagement. Available features depend on the Langfuse version and edition deployed.
WHY LANGFUSE
Move beyond AI demos with visibility into model behavior, cost, quality and operational regressions.
LLM applications and agents behave differently from conventional software. The same input can produce different outputs, a prompt change can shift quality across thousands of conversations, and a multi-step agent can fail in ways no single log line reveals. Teams need to see what happened in each request, measure quality systematically and detect regressions before users do.
Langfuse is an LLM engineering platform for tracing, evaluation and prompt management. Bassirah deploys and integrates it so that traces, user feedback, evaluation scores and prompt versions become part of your development lifecycle, your release process and your governance reviews.
WHAT BASSIRAH DELIVERS
Our Langfuse engagements connect tooling, infrastructure and process.
USE CASES
Solution concepts. Each design is validated against your applications and data.
Capture the steps of each instrumented LLM request, score outputs and compare quality across model, prompt and code changes.
Version prompts, run experiments against evaluation datasets and promote changes with evidence rather than intuition.
Give engineering, product and risk teams a shared view of agent behavior for development, incident analysis and periodic reviews.
RUNTIME STACK
Self-hosted Langfuse depends on several infrastructure components. Each one needs sizing, security, backup and monitoring. Bassirah designs the full stack for the Langfuse release you select, and can operate it under contracted managed support.
| Component | Role in a self-hosted deployment | Design considerations |
|---|---|---|
| Langfuse Web | User interface and API that receives traces and serves queries | Scaling, authentication, network exposure |
| Langfuse Worker | Processes ingestion and background work asynchronously | Throughput sizing, scaling with ingest volume |
| PostgreSQL | Transactional application state and configuration | Required in supported self-hosted patterns; HA and backup design |
| ClickHouse | Stores and serves trace, observation and score analytics. Partner-led ClickHouse or ClickHouse OSS | Do not write custom events directly to Langfuse internal tables; sizing and retention |
| Redis (or compatible) | Ingestion queue and application cache | Queue durability, eviction mode and sizing require design |
| S3-compatible object storage (for example MinIO AIStor) | Event payloads and multimodal assets | Bucket configuration, encryption, lifecycle and residency |
Model inference, retrieval and vector search are not provided by the Langfuse observability platform. They remain application-side decisions, and Bassirah designs them separately. Exact features and component requirements depend on the Langfuse version and edition deployed.
We will size and design the full Langfuse runtime stack for your environment.
RESPONSIBLE AI OPERATIONS
Observability lets you trace, evaluate and monitor AI application behavior. It cannot by itself guarantee that outputs are correct. We design Langfuse programs around three principles.
Define evaluation criteria with domain experts, not just generic metrics, and track them consistently over time.
Traces can contain prompts, outputs and personal data. Masking, access control, retention and data location are designed before production traffic flows.
Connect findings from traces and evaluations to prompt changes, model choices, test datasets and release gates.
WORKS WELL WITH
Langfuse self-hosting uses ClickHouse, Redis and object storage in supported architectures. Pair it with enterprise data sources and AI application frameworks.
Analytical storage for Langfuse traces, observations and scores, on partner-led ClickHouse or ClickHouse OSS.
Langfuse ingestion queue and cache, plus optional, separate semantic caching for applications.
S3-compatible storage for event payloads, multimodal assets and telemetry retention patterns.
SEE IT IN CONTEXT
HOW WE ENGAGE
Langfuse is an LLM engineering platform. It captures traces of LLM application and agent requests, supports evaluations and scoring, manages prompt versions, and tracks cost and latency. Bassirah integrates it with your applications, development lifecycle and governance processes.
No observability platform can guarantee correct outputs. Langfuse helps you trace, evaluate and monitor AI application behavior so that quality issues are detected, measured and addressed through prompt, model, data and process improvements.
It depends on data sensitivity, residency requirements, operational capacity and the features you need. Self-hosting gives you control of data location and infrastructure but requires operating PostgreSQL, ClickHouse, Redis and object storage. We compare both routes during design.
In supported self-hosted patterns, Langfuse Web and Worker services run alongside PostgreSQL, ClickHouse, Redis or a compatible cache and queue, and S3-compatible object storage. Exact requirements depend on the Langfuse release, so we size each component against your expected trace volume and retention.
We design masking and redaction at the application or SDK level, restrict access by role and project, set retention rules and decide where telemetry is stored. These controls are agreed with your security and privacy owners before production traffic is captured.
Langfuse provides SDKs and integrations for common languages and AI frameworks, and supports OpenTelemetry-based ingestion. We confirm compatibility with your specific frameworks and versions during the workshop.
The analytical engine behind Langfuse traces, on partner-led ClickHouse or ClickHouse OSS.
Operations & Reliability
Langfuse v4 makes observations the main table. What breaks, the Cloud cutover on 16 November 2026, and a safe self-hosted upgrade path.
ClickHouseLangfuseOpenTelemetry
Read article : Langfuse v4: Planning the Move to the Observations Data Model→
Tell us about your AI applications, agents and governance needs. We will help you instrument, evaluate and operate them in production.
