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.
Oodle.ai is ai agents software teams evaluate for ai agents. Use this page to review pricing, integration signals, and the best alternatives before you commit.
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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
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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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Claim this listingKey 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 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
Limitations
Claim this listing to add transparent limitations.
Frequently Asked Questions
Do I need a separate SDK to instrument my LLM calls?
Which LLM providers and models are supported?
How is this different from standalone LLM observability tools?
Does Oodle do prompt versioning or evals?
Do you sample LLM traces?
Getting Started
- 1 Sign up or try the Playground (free tier available; no credit card required).
- 2 Instrument your agents to emit OpenTelemetry (Generative AI semantic conventions) or point your existing OTLP exporter at Oodle.
- 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
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