#4830“Where is my parcel?”#4827“Driver never showed up”#4819“Tracking says delivered”#4812“Can I change the address?”
Building a startup? Claim startup creditsWhere startups ship with confidence.
Where startups ship with confidence.
Not crossed fingers.
Trace every interaction, let your domain experts flag what's wrong, and turn their feedback into evals your coding assistant can fix against. Ship reliable AI at startup speed.
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Evals ran to date[ 0+ ]
Get alerted of dissatisfied customers before they churn.
See which conversations leave users frustrated or confused, grouped by the issue behind them. Fix what's driving churn before it shows up in your retention numbers.
Customer Profile
One account's sentiment, conversations, and activity over time.
Turn live traces into evals so users don't complain twice.
Trace real interactions and let the people who know your product flag what's wrong. Turn their feedback into evals without adding a separate review tool to your team's workload.
Expert Review Queues
Flagged traces routed to reviewers, then into your evals.
Ship at the speed of agents without sacrificing quality.
Bring failing test cases and production traces into your coding assistant through MCP. Fix issues where you already build, then rerun evals to check the change.
Built with MCP & Agent Skills
Shared eval context inside the coding assistant.
THE PLATFORMIdentify, prioritize, improve.
Identify, prioritize, improve.
Complete the AI quality loop for founders.
INTEGRATIONSStay in your stack.
Stay in your stack.
We'll meet you there.
OTel-native, 30+ integrations, and SDKs in Python and TypeScript that feed straight into traces and evals.
THE FRONTIER
New features every week.
A new release lands every week. Here's what shipped in the last eight.
- Lost in TranscriptionTranscribe Recorded Calls with Any STT Engine · Multi-Turn & Voice Experiments · Voices, Accents & Phone Lines for Personas · Annotation Folders, Sections & Spreadsheet Import · Run Workflows on Existing Traces, Spans & Threads · Failure Modes from Failing Metrics · Trace & Span Metrics for AI Connections · Organization Security Overview · Confidence Thresholds for Issue Classifiers · UI Transformers for Spans, Threads & Queue Items · Statistical Significance on Regressions · More Filters · Skip Already Evaluated in Observatory · Higher Trace Ingestion Throughput · Reliable Workflow Chains with Skip Reasons · Faster Span, LLM & Tool Pages · Higher Eval Worker Concurrency
- Can You Hear Me Now?ElevenLabs Integration · Traceable Voice Simulations · Metadata in Voice Connections · Agent State Events in the LiveKit Simulator · End Reasons in Voice Connection Logs · Online Evals Wait for Late-Arriving Spans · Separate Thread & Trace Idle Time for Online Evals · Journey Discovery from Annotation Queues · Hardcoded User Messages in Journey States · Filter Goldens During an Evaluation · Classifier Timelines with Step-by-Step Reasoning · Eval Mode for Classifiers · New LLM Span Attributes · Encrypted Credentials · Red Teaming Moves to the Organization Level · Multi-Turn Evals Without Simulations · Golden & Metric Editor Updates · Browser Translate No Longer Breaks the UI
- Nav a Nice DayNested Side Nav · LLM Analytics · Dedicated Metric & Classifier Pages · Validate Metrics & Classifiers on Real Data · Revamped Workflows with Live Counts · Journeys Public Endpoints & MCP Tools · Voice Metrics on Traces · Generate with AI for UI Transformers · Multi-Turn Goldens from Trace Ingestion · Filterable Annotation Queues · Custom Model Parameters for Prompts · Inference Settings & Embedding Model Config · AWS SigV4 Auth & Turn-Level Metadata for AI Connections · Agent Entrypoint Control for Failure Mode GitHub Connections · Per-Project Limits for Classifiers & Online Evals · Clearer Rate Limit Errors on Metrics · Worker Stability · Zero-Downtime Rollouts & Readiness Gates · Leaner Queue Jobs in Redis · Helm Chart v1.0.0
- Off the RailsSpan Classifiers · Workflow Chaining for Spans & Threads · Audio Classifiers · Audio Review Step for Audio Classifiers · Revamped Audio Player in Observatory · Multiple Issues per Classification · Evidence in Failure Modes · Scheduled Failure Modes & Code-Aware Write-Ups · GitHub Integration for Classifiers · Classifiers Page, Collections & Tasks · Credits & Trace Storage (GB-Months) with Self-Serve Upgrades · BYE Support for SIP Voice Connections · Media Encryption & SRTP for SIP Voice Connections · Pipecat Audio Tracing · Custom Token Request Auth for AI Connections · Refreshed Dashboard · New Onboarding Wizard · Agent Skills for Onboarding · Fully on AWS
- What a JourneyJourneys (Beta) · Voice Connections · Pipecat / Daily Integration · Individual Metrics · Full Workflows Support · Personas on Single-Turn Goldens · Audio & Voice Model Configs · Scheduled Workflows for Recurring Tasks · Onboarding Skills in the European Union · Golden Expectations · Tool Versioning · Red Teaming Probes View · Signals Evidence Highlighting & Label Coverage · Failure Analysis on Signals · Dynamic Model Credentials
- Tool Me Once, Shame on YouTool Failure Analytics · Workflow Chains for Classifiers & Ingestion Tasks · Span Trees · Revamped Trace Message & IO Views · Validation Data in Eval Human Alignment Graphs · Test Cases in Annotation Queues · Persona Metadata Keys in AI Connection Payloads · More Flexible Golden Schemas for AI Connections · Prompt-Based Evaluator · Z.ai Models
- Note-WorthyRevamped Annotation Analytics · Auto-Annotate Hot Keys · Recurring Queue Ingestion Tasks · Validations for Metric Alignment · Error Analysis Visualizations & Filters · EvalMode & Decision Models for Every Metric · Trajectory Custom Metrics · Span Filters for Traces, Signals & Dashboards · LiveKit Audio Recordings on Traces & Spans · Persona Metadata & Background Noise · Findings Alerts for Regressions, Anomalies & Signal Spikes · Snowflake Export Integration · Multiple Credentials per Project for Bedrock & Azure OpenAI · OAuth 2.0, mTLS & Client Secret Auth for AI Connections
- Search and RescueSearch for Traces & Spans · Annotation-Triggered Workflows · Item Status on Annotation Queues · V2 API with 200+ Endpoints · Live Threads with Configurable Idle Time · Latency Scatterplot · Export Schedules for Annotations & Test Runs · AI-Generated Dashboard Widgets
FAQ
Have a question?
Checkout our FAQs below, or talk to a human. They won't hallucinate.
Yes. Sign up through Try Now For Free to explore Confident AI. You can start with a small dataset and a few quality checks, then build coverage around the issues your users encounter.
Run the same dataset against each version and compare metric scores and individual failures. Add evaluations to CI so your team checks changes before release.
Yes. Add production traces to datasets and have your team review the examples and expected answers. Use those cases to test whether the next change addresses the problems you saw in production.
No. Founders, engineers, and domain experts can share the work. Assign conversations for review, collect ratings and explanations, and keep feedback alongside the data your engineers use for evals.
Yes. Connect a compatible coding assistant through the Confident AI MCP server to access traces, datasets, and test results from your editor. Use that context to investigate failures and check fixes against your team's evals.
Yes. Create a dataset with example inputs and outputs, choose your metrics, and run an evaluation in the platform. Add production tracing when you're ready to build coverage from real usage.
Filter which traces enter an annotation queue, sample matching items, and cap the number added. Assign reviews to the people who know the use case so they can focus on relevant examples.
Yes. Configure classifiers for sentiment or failure patterns. Signals surfaces label trends and spikes, with links to the conversations behind them so you can investigate.