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LLM platform

Model access, RAG and evaluation for answers grounded in enterprise data. Data boundaries and usage costs are part of the design.

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On this page4 sections
  1. Scope of service
  2. How we work
  3. Runtime environment and monitoring
  4. Tooling

An application using company knowledge needs clear rules for data access, answer evaluation and cost tracking. We set up model access and RAG to retrieve relevant information, along with evaluations your team can use to compare answers. Whether the model runs on-premises or in the cloud depends on your data privacy, capacity and cost requirements.

Scope of service

  • Model access layer: routing, fallback, per-team quotas and cost limits
  • Grounded answers from enterprise data (RAG): indexing, retrieval and reranking
  • Multi-step agent workflows and tool integrations
  • Evaluation harness: regression, drift and hallucination measurement
  • Observability: request tracing, latency, token and cost tracking
  • Access and privacy: per-department authorization, log redaction, data boundaries

How we work

  1. Evaluation set

    We build an evaluation set from real questions and expected answers to test model and architecture choices.

  2. RAG and retrieval verification

    We verify document preparation, index freshness, access permissions and retrieval/reranking quality separately.

  3. Access and cost control

    We configure per-team token authentication, model authorization, rate limits and caching at the API gateway.

Runtime environment and monitoring

When using cloud provider APIs, we configure processing regions and retention rules. For internal deployments, we run vLLM or Ray Serve on Kubernetes behind an OpenAI-compatible endpoint, partitioning supported NVIDIA GPUs with MIG depending on the model's memory requirements and request load. We track time to first token, token generation speed, KV cache utilization and per-team spend on the same dashboard as service telemetry.

Tooling

Model access
LiteLLMPortkeyAzure OpenAIAnthropicOpen-source models
Retrieval and vector
Postgres pgvectorQdrantOpenSearch
Agent workflows
LangGraphOpenAI Agents SDKClaude Agent SDK
Evaluation and monitoring
LangfuseOpenTelemetry GenAIPrometheusGrafana
In-house serving
KubernetesvLLMRay ServeNVIDIA device pluginMIG slices
API gateway
Apache APISIX (token authentication, access lists and rate limiting)

Let's talk.

Discuss your needs in a 30-minute call.

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