TripleCloud
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Stop running AI pipelines
blind.

LLM observability for AI pipelines — quality, cost and stability control, built for the teams shipping LLMs in production.

Open source on GitHub
TripleCloud LLM observability overview dashboard with traces, latency and token-cost metrics

The LLM observability platform

Quality. Cost. Stability.

One platform for AI observability — every signal your AI pipeline emits, from the first token to the last billing line.

Quality

Trust every answer your model ships.

Catch regressions before users do — with online evals and human feedback wired into every turn.

  • Scoring: faithfulness, relevance, context recall
  • Hallucination & PII leak detection (regex + LLM)
  • Human 1–5 feedback loops with sampling controls
  • Per-conversation eval pass-rate with drill-down
Cost

Know what every token costs.

Rollups by model, provider, user and prompt. Projected EOM. Budgets and alerts before you bleed.

  • Spend MTD, EOM, cost per conversation
  • Daily spend stacked by model / workspace / user
  • Token cache hit-rate and savings
  • Budgets with multi-channel alerting
Stability

Stay on top of every incident.

Traces, errors, SLOs and on-call paging — the SRE stack your AI agents have been missing.

  • Distributed traces across agents and tool calls
  • Alerts with PagerDuty / Slack / on-call routing
  • SLOs with burn-rate and 30d error budgets
  • Provider downtime feeds (OpenAI, Anthropic, etc)

A look inside

LLM observability built for the way AI teams debug.

Cost & usageSpend rollups, projected EOM, per-user breakdowns.
TripleCloud cost dashboard: spend rollups, projected end-of-month total and per-user breakdowns
SLOsSLOs with burn-rate and 30-day error budgets.
TripleCloud SLO dashboard with burn-rate and 30-day error budgets
AlertsAlerts with on-call paging and acknowledgements.
TripleCloud alerts view with on-call paging and acknowledgements
ScoresOnline monitors: LLM-as-judge, regex, human feedback.
TripleCloud quality scores from online monitors: LLM-as-judge, regex and human feedback

Pricing

Pay as you go.

Transparent, usage-based. No seats. No platform fee. Bring your storage if you want.

TripleCloud pricing pipelineYour OpenTelemetry exporter pushes spans into Ingest (€0.25 per GB ingested), where the LLM processor parses them (€5.00 per GB processed) before they are written to Store (€0.25 per 10GB per month). Stored spans are then evaluated by Score (€0.75 per 10k span evaluations) — evaluation orchestration only; bring your own judge-model provider.
OpenTelemetry
Ingest€0.25 / GB
Process€2.50 / GB
Store€0.25 / 10GB·month
Score€0.75 / 10k
See full pricing details
€0.25/ GB
Ingest
Raw events, logs and conversation payloads.
€2.50/ GB
Process
Trace ingestion, parsing and enrichment across agents.
€0.25/ 10GB·month
Store
Hot, queryable retention. BYOStorage available.
€0.75/ 10k scores
Score
Evaluate LLM spans for their result. Orchestration only - BYO model provider.
SSO · Dedicated instance · Certifications available

Open source

The engine is open source.

TripleCloud runs on IceGate — an Apache-2.0 observability data lake engine. Self-host the exact engine we run, or let us operate it. No black box, no lock-in.

OpenTelemetry-native

Point any OTel SDK at IceGate. Exactly-once delivery, straight into open Parquet — no agents to rewrite.

Open formats, no lock-in

Apache Iceberg, Arrow and Parquet under a Rust-native DataFusion query engine. Your data stays portable.

Your storage, your bucket

WAL, catalog and data all live in S3-compatible object storage. Self-host the whole thing under Apache 2.0.

Star on GitHub