Oodle.ai

Oodle.ai

Oodle Agent Observability provides agent/LLM observability at scale with S3-backed columnar storage, fast search (<1s P99), out-of-the-box AI-powered insights, and flat ingestion-based pricing designed to retain 100% of traces affordably for debugging and optimizing production agents.

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#481 in AI Agents (481 tools)
Added 1 month ago
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Quick Overview

Best for: AI Agents

What it does

AI Agents software for decision-makers comparing workflow fit and alternatives.

Best fit

AI Agents

Pricing snapshot

Free from Examples shown: $10 per million spans; ingestion $0.30 / GB; retention example $0.001 / GB / mo; unlimited queries

Next step

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Oodle.ai

Oodle Agent Observability is a production observability product purpose-built for agentic and generative AI systems. It stores full agent traces in S3-backed columnar storage with serverless compute to enable fast, low-cost querying and retention of 100% of traces. The product surfaces AI-powered insights (quality, performance, efficiency) and provides LLMOps capabilities such as evals, prompt versioning, regression checks, cost estimation, and a live playground for iterating without redeploying. It is aimed at engineering teams and companies from startups to enterprise, with onboarding that can begin in minutes and a free tier available.

End-to-end visibility across LLM calls, APIs, and infra - so you can ship your AI with confidence, not hope. Agent observability at $10 per million spans.

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Key Features

Fast trace search

<1s P99 query using columnar storage and serverless compute for fast searches over large agent traces.

Low-cost S3-based storage

S3-backed storage with pricing examples such as $10 / million spans and ingestion pricing (e.g., $0.30/GB) to retain 100% of traces affordably.

Out-of-the-box AI Insights

Automatic detection of silent failures, high-duration traces, low user satisfaction, cost optimization, caching inefficiency, and excessive LLM turns without writing rules.

Full LLMOps workflow

Prompt versioning, build eval datasets, run experiments, and score results with built-in or custom evaluators alongside production traces.

Agent transcript and span detail

Inspect multi-turn conversations, system prompts, tool calls, multi-agent handovers, and token breakdowns per span.

Cost estimation and model pricing

Estimated cost per trace/model/service with 50+ model pricing definitions (OpenAI, Anthropic, Google, Mistral, Cohere, etc.) and support for custom models.

OpenTelemetry (OTLP) ingestion

Consumes standard OpenTelemetry traces using the Generative AI semantic conventions; point your OTLP exporter at Oodle.

Playground for prompt iteration

Iterate on prompts, swap models, tweak parameters, and compare outputs live without redeploying.

Pricing

Free Tier Available

Free tier included โ€” no credit card required; Try in Playground available.

Pay-as-you-go / Ingestion-based

Examples shown: $10 per million spans; ingestion $0.30 / GB; retention example $0.001 / GB / mo; unlimited queries
  • Flat ingestion-based pricing (no per-query / per-user charges)
  • Unlimited queries (UI, MCP, CLI, API)
  • Configurable retention with all retained data queryable at same speed

Use Cases

Production agent debugging

Detect silent failures, incomplete tool call chains, and unhandled exceptions across agent traces to debug agents in production.

Agent performance and reliability monitoring

Identify high-duration traces, stuck loops, slow tool calls, and retry storms impacting agent performance.

LLM cost optimization

Spot over-provisioned model calls, calculate estimated costs per trace or model, and identify opportunities to use cheaper models or caching.

Regression checks and evals

Build eval datasets from production traces or CSV, run experiments, and compare model outputs to maintain quality over time.

Migration from legacy observability

Replace or complement ELK, Grafana, Datadog traces with an object-storage-native, serverless architecture tailored for agent traces.

Voice AI monitoring

Catch silent failures and other issues specific to voice agents in production (explicitly called out in case studies).

Integrations

OpenTelemetry (OTLP)

Consume standard OpenTelemetry traces using the Generative AI semantic conventions.

LLM providers

Cost estimation and support for OpenAI, Anthropic, Google Gemini, Mistral, Cohere, Azure OpenAI, AWS Bedrock, and self-hosted models.

Cloud marketplaces / cloud commits

Use cloud commits via cloud marketplace (site references cloud marketplace options).

Benefits

Fast query performance (sub-second P99) for large agent trace datasets.
Lower storage cost via S3-based architecture and flat ingestion pricing (example: $10 / million spans).
Retain 100% of traces (no sampling) while controlling budget.
Automatic AI-powered insights to surface failures and inefficiencies without manual rules.
Integrated LLMOps workflow: evals, experiments, prompt versioning, and playground iteration.

Limitations

No verified limitations are available.

Frequently Asked Questions

Do I need a separate SDK to instrument my LLM calls?
No. Oodle consumes standard OpenTelemetry traces using the Generative AI semantic conventions. If your instrumentation library already emits these attributes, you point your OTLP exporter at Oodle.
Which LLM providers and models are supported?
Any provider that your code calls โ€” OpenAI, Anthropic, Google Gemini, Mistral, Cohere, Azure OpenAI, AWS Bedrock, and self-hosted models. Cost estimation ships with 50+ model pricing definitions and you can add custom models.
How is this different from standalone LLM observability tools?
Standalone tools create another data silo. Oodle shows LLM spans inside the same traces as API, database, and cache calls so you see the full picture when something breaks.
Does Oodle do prompt versioning or evals?
Yes. Oodle includes a full LLMOps workflow: version and label prompts, build eval datasets (or import via CSV), run experiments against any model, and score results with built-in or custom evaluators alongside production traces.
Do you sample LLM traces?
No. Retain 100% of your traces with full prompt and response content.

Getting Started

  1. 1 Sign up and access the free tier or Try in Playground (free tier included, no credit card required).
  2. 2 Instrument your application to emit OpenTelemetry (OTLP) traces using Generative AI semantic conventions.
  3. 3 Point your OTLP exporter at Oodle and begin sending traces (start sending traces in under 15 minutes).
  4. 4 Use the Playground to iterate on prompts and run evals or experiments.

Support

Docs

Documentation and product docs linked from the site (Docs link present on the product page).

Playground

Interactive Playground to try features and iterate on prompts without deploying.

Schedule Demo / Sales

Schedule Demo call to see the product in your environment.

Community / Chat

Community links such as Discord and LinkedIn referenced on the site.

Status

Status page and support policy links are available from the site footer.

API

Available: Yes

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