Streaming & AI/LLM Observability · Full‑Stack OTEL
The Outage You Can't Explain.
The Bill You Can't Justify.
Somewhere a consumer is lagging, or an LLM call is quietly retrying itself into a five-figure bill — and your dashboards can't tell you which. Data at Depth wires OpenTelemetry into Prometheus, Tempo, Loki, and Grafana across your streaming pipelines and your AI tooling — token cost, latency, and error rate, correlated with the trace that caused them.
Data at Depth
Services
Fixed-scope. Known outcomes.
Productized engagements so you know exactly what you're getting — no runaway billing, no ambiguous deliverables.
Streaming Infrastructure
Streaming Visibility Audit
1-week assessment of your streaming/event-pipeline stack — Kafka, Kinesis, Pulsar, RabbitMQ, or similar — with a written findings report and live debrief.
$3,500 – $5,000
Streaming Visibility Buildout
Open-standard instrumentation (OpenTelemetry) across metrics, traces, and logs — Prometheus, Tempo, and Loki, visualized in Grafana — deployed on your stack or the backend you already run.
From $20,000 · scoped per stack
Platform Foundation
Serverless data platform built from scratch on your cloud — managed compute, streaming, storage, and catalog services (AWS, GCP, or Azure).
Custom — book a scoping call
Advisory Retainer
Monthly architecture review, async support, and runbook review. Min. 3-month commitment.
$3,000 – $6,000/mo
AI / LLM Integration Observability
AI Integration Observability Audit
1-week assessment of your AI tool telemetry gaps, written report, and debrief.
$3,500 – $5,000
AI Integration Observability Buildout
OpenTelemetry instrumentation for AI tools — cost attribution, latency, and error-rate dashboards across Prometheus, Tempo, and Loki, visualized in Grafana, self-hosted by default or on the managed backend you already run.
From $15,000 · scoped per stack
AI/RAG Integration Audit
1-week assessment of an existing RAG pipeline or agent/LLM integration — retrieval quality, latency, cost, and observability gaps — written report and live debrief.
$3,500 – $5,000
AI/RAG Integration Buildout
RAG pipeline or agent-orchestration integration built with observability instrumented from day one — OpenTelemetry across retrieval, generation, and tool-use steps, on Prometheus, Tempo, Loki, and Grafana.
From $15,000 · scoped per stack
Not sure where to start? The audit is the right first step for most teams.
Results
Before & after
High-volume streaming platform · Millions of events/day
Challenge
Kafka consumer lag spiked silently with no alerting. The team found out pipelines were broken when downstream processes failed — or when a stakeholder noticed. P1 incidents averaged 45+ minutes to detect.
Outcome
Deployed full observability instrumentation across the pipeline — consumer lag tracking, throughput metrics, and dashboards covering error rates and consumer group health. P1 detection dropped to under 4 minutes. Zero missed incidents in the first 90 days.
Series B · Kubernetes · AI assistants · 80+ engineers
Challenge
The engineering org rolled out AI coding assistants and integrated LLMs into their product. No telemetry existed on adoption, latency, cost per team, or errors. Finance couldn't explain the API bill.
Outcome
Built AI tool telemetry pipeline on Kubernetes — token usage, latency, error rates, and cost attribution visible per team per day across both managed and self-hosted backends. Delivered dashboards for adoption rates, p95 latency, and cost attribution by team. Two high-cost integration patterns identified and fixed within 30 days.
About
Data at Depth
Data at Depth is built on 7+ years of production data infrastructure experience — enterprise-scale event streaming pipelines and full observability stacks for AI tool adoption on Kubernetes.
Most engineering teams find out something broke when a customer complains. Data at Depth builds the visibility layer that changes that.
Data at Depth works with Series B–D SaaS and mid-market engineering teams (30–300 engineers) running Kafka or Kinesis, or adopting AI coding tools and LLM features, with no dedicated platform or observability team — not healthcare, health-tech, or insurance.
Production Kafka at enterprise scale
Data at Depth brings 3+ years of production-scale streaming pipeline experience — millions of events per day. Not tutorials. Not side projects.
Full observability, streaming and AI alike
Data at Depth has built and shipped OpenTelemetry → Prometheus, Tempo, Loki → Grafana for both streaming pipelines and AI/LLM tool adoption — token usage, latency, cost attribution — on self-hosted or managed backends, any cloud.
Observability-native AI integration
Data at Depth applies the same instrumentation discipline to your RAG pipeline or agent from day one — OpenTelemetry across retrieval, generation, and tool-use steps, not bolted on after launch.
AWS certified on both tracks
Data at Depth is backed by AWS Certified Solutions Architect (SAA-C03) + AWS Certified Data Engineer (DEA-C01) expertise. The architecture is sound — clients don't have to wonder.
Statistical rigor
Data at Depth's rigor is grounded in an MS in Biomedical Sciences — evidence-based diagnosis and validation, not gut feel, applied to how problems are scoped and solutions are measured.
Ready to see what your pipeline — or your AI stack — is doing?
Most teams already know something's wrong — they just don't have the data to prove it. Let's start there.