Oodle.ai

Oodle.ai

Oodle Agent Observability provides scalable, low-cost observability for AI agents with S3-backed storage, sub-second search, out-of-the-box insights, and full-trace retention to debug and optimize agentic systems in production.

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Free API 70/100
#393 in AI Agents (393 tools)
Just launched
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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 $10 per million spans (headline); example ingestion rate $0.30/GB and retention $0.001/GB/mo shown in pricing calculator

Next step

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Oodle.ai

Oodle Agent Observability is designed to help engineering teams observe, debug, and optimize production AI agents at scale. The product emphasizes full-trace retention (no sampling), S3-based storage to control costs, and fast search over large agent traces. It targets teams running agentic systems (including Voice AI) that need reliable end-to-end visibility into prompts, tool calls, model responses, and multi-turn conversations.

Oodle combines a serverless, object-storage-native architecture with out-of-the-box insights and LLMOps workflows (playground, evals, experiments) so teams can surface silent failures, optimize model usage, and reduce incident resolution time and cost.

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 search (<1s P99)

Sub-second P99 queries over traces using columnar storage and serverless compute to find traces in seconds rather than minutes.

$10 / million spans and ingestion-based pricing

Costing highlighted as $10 per million spans and a flat ingestion-based pricing model with no per-query or per-user charges.

S3-based storage and full retention

Store 100% of traces on object storage (S3) and retain them for months or years at configurable retention periods while keeping data queryable at the same speed.

Out-of-the-box AI Insights

Automatically detect issues such as silent failures, high duration traces, low user satisfaction, model cost inefficiencies, caching inefficiencies, and excessive LLM turns without writing custom rules.

Full trace visibility

Inspect multi-turn conversations including system prompts, tool calls, handovers, and token breakdowns per span to diagnose runaway prompts and budget overruns.

LLMOps: Evals, Playground, Experiments

Built-in workflows to version and label prompts, build eval datasets, run experiments against models, and score responses with built-in or custom evaluators.

OpenTelemetry (OTLP) compatibility

Consumes standard OpenTelemetry traces using the Generative AI semantic conventions—point your OTLP exporter at Oodle if your instrumentation already emits those attributes.

Cost estimation for models

Configurable cost estimation per trace / per model with 50+ model pricing definitions shipped by default and support for custom or fine-tuned models.

Pricing

Free Tier Available

Free tier included with no credit card required.

Ingestion-based pricing

$10 per million spans (headline); example ingestion rate $0.30/GB and retention $0.001/GB/mo shown in pricing calculator
  • Flat ingestion-based billing
  • No per-query or per-user charges
  • Configurable retention with all retained data queryable at the same speed

Use Cases

Debugging production AI agents

Surface silent failures (fake 'I did it' messages, silent tool errors, mid-conversation failures), inspect full traces, and resolve incidents faster.

Cost optimization for LLM usage

Detect over-provisioned model calls, caching inefficiencies, and estimate trace/model costs to reduce unnecessary spending.

LLMOps and model evaluation

Build eval datasets from production traces or imports, run experiments, version prompts, and score outputs with built-in or custom evaluators.

Observability for multi-service systems

View LLM spans alongside API, database, and cache calls to see the full picture when something breaks.

Integrations

OpenTelemetry (OTLP)

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

LLM providers (OpenAI, Anthropic, Google Gemini, Mistral, Cohere, Azure OpenAI, AWS Bedrock, self-hosted)

Cost estimation and model support ship with 50+ model pricing definitions and explicitly list major providers; you can add custom models.

Benefits

Very fast trace queries (sub-second P99) for rapid debugging
Lower storage cost via S3-based architecture and an ingestion pricing model ($10 / million spans cited)
Keep 100% of traces (no sampling) so failures are never missed
Out-of-the-box insights that surface quality, performance, and efficiency issues without manual rules
Integrated LLMOps tooling (playground, evals, experiments) to iterate on prompts and models alongside production traces
Simplified pricing with no per-query charges and configurable retention

Limitations

Claim this listing to add transparent limitations.

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, point your OTLP exporter at Oodle.
Which LLM providers and models are supported?
Any provider your code calls, including 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. Oodle retains 100% of traces with full prompt and response content.

Getting Started

  1. 1 Sign up or try the Playground (free tier available; no credit card required).
  2. 2 Instrument your agents to emit OpenTelemetry (Generative AI semantic conventions) or point your existing OTLP exporter at Oodle.
  3. 3 Start sending traces and use the UI, CLI, or API to search traces, run evals, and view AI-powered insights (go-live in ~15 minutes as advertised).

Support

Docs

Documentation linked from the site (Docs in the site navigation).

Playground

Try in Playground to experiment with features and prompts.

Schedule Demo

Option to schedule a demo via the site navigation.

Community & Status

Community and status channels referenced on the site (Discord, Status).

API

Available: Yes

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