Shipping agents is easy. Observing agents is hard.
Searching Agent Traces is slow
Agent Traces have large metadata - prompts, tool calls, etc. - search results can take minutes to load.
Storing Agent Traces is expensive
Agents fail non-deterministically - so you can't afford to miss any trace - but you can't afford to keep them all either.
Surfacing agent failures is hard
Agents fail in so many ways - fake 'I did it' messages, silent tool errors, give up mid-chat...
Oodle: Agent Observability that “just works” at scale
<1s P99 query
Fast search over traces
Columnar storage, serverless compute - find the trace in seconds, not minutes.
$10 / million spans
S3-based storage
Store 100% of traces and keep your budget too. Retain for months or years - you choose.
Every trace, analyzed
Out-of-the-box Insights
Detect user frustration, tool call optimizations, anomalies before you write a single eval
Customers love us!
3M+ agent traces/day. Zero sampling.
Catch silent failures on Voice AI agents.
Trusted by engineering teams
Shipping agents is easy. Observing agents is hard.
Storing Agent Traces is expensive
Agents fail non-deterministically - so you can't afford to miss any trace - but you can't afford to keep them all either.
$10 / million spans
S3-based storage
Store 100% of traces and keep your budget too. Retain for months or years - you choose.
Searching Agent Traces is slow
Agent Traces have large metadata - prompts, tool calls, etc. - search results can take minutes to load.
<1s P99 query
Fast search over traces
Columnar storage, serverless compute - find the trace in seconds, not minutes.
Surfacing agent failures is hard
Fake 'I did it' messages, silent tool errors, gave up mid-way - so many ways agents can fail.
Every trace, analyzed
Out-of-the-box Insights
Detect user frustration, tool call optimizations, anomalies before you write a single eval
Battle-tested in production.
Trusted by engineering teams
Flat ingestion-based pricing
No per query / per-user charges.
| Dimension | Value | Unit Price | Monthly Cost |
|---|---|---|---|
| Ingestion | 1200 GB/mo | $0.30 /GB | $360 |
| Retention | 90 days | $0.001 /GB/mo | $2 |
| Queries (UI, MCP, CLI, API) | unlimited | $0 | $0 |
| Total | $362 /mo |
How It Works
Blog · Engineering
How We Achieved $10/Million Agent Spans
At Oodle we built a new high performance, low cost database backed by object storage for each kind of observability signal...
Vijay Karthik
14 Jul 2026 · 5 min read
Blog
You Can't Sample Your Way to Reliable Agents
Building agents has become easy. A few lines of code and you have a working agent. But once it's in production, how do you know it's actually working...
Vijay Karthik
09 Jul 2026 · 4 min read
Blog · Architecture
How Oodle Keeps Observability Fast at Scale
If you've ever kept a giant observability cluster alive “just in case,” you know the vibe: half your spend goes to idle capacity, and the other half goes to hoping ...
Vijay Karthik
23 Mar 2026 · 7 min read
How Oodle Agent Observability Works
See how you can setup Agent Observability on Oodle to surface silent agent failures and debug your agents in production from day 1.
Surface issues before users notice.
Insights automatically detect silent failures across your agent traces - no rules to configure.
Error Recovery Failures
Agents that hit errors and fail to recover gracefully. Incomplete tool call chains, unhandled exceptions mid-conversation.
High Duration
Traces taking significantly longer than baseline. Catches stuck loops, slow tool calls, and retry storms.
Low User Satisfaction
Responses flagged by sentiment and quality scoring as negative or off-topic. Identifies patterns in poor experiences.
Model Cost Optimization
Traces where a cheaper model could produce the same result. Spots over-provisioned calls burning budget on simple tasks.
Caching Inefficiency
Repeated identical prompts that could be cached. Flags redundant LLM calls wasting tokens and adding latency.
Excessive LLM Turns
Conversations that spiral into too many turns. Detects prompt loops, circular reasoning, and agents that can't converge.
Complete LLMOps Platform
Monitor, debug, and optimize every layer of your AI stack.
Observe Agent Transcripts for Deep Dives
Read the exact multi-turn conversation: system prompt, tool calls, multi-agent handovers. Input, output, and reasoning tokens broken down per span - spot runaway prompts and budget overruns before they hit your bill.
Evals for Your Agents
Configure eval pipelines for accuracy, relevance, and safety. Score every response automatically - use our out-of-the-box evals or write your own.
AI-powered Insights for your Agentic stack
Surface issues on Quality, Performance, Efficiency out-of-the-box - improve your agents from day 1
Refine Your Prompts with Playground
Iterate on prompts in a live playground. Swap models, tweak parameters, and compare outputs - without redeploying.
Regression Checks for Your Agents - Datasets & Experiments
Build eval datasets from production traces or CSV imports. Run experiments against any model and compare results side-by-side.
Cost Estimation with Configurable Pricing
Estimated cost per trace, per model, per service. 50+ model pricing definitions shipped by default - OpenAI, Anthropic, Google, Mistral, Cohere, and more. Add custom or fine-tuned models in the UI.
See It In Your Environment
Start sending traces in under 15 minutes. Free tier included - no credit card required.
Frequently Asked Questions