End-to-End Self-Healing AI Evaluation
Complete self-healing evaluation from detection to deployment. Zero human intervention. Your AI workflows fix themselves while you ship features.
Complete Autonomous Solution
While others require human oversight at every step, Barcable runs the entire evaluation-to-deployment cycle autonomously.
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Zero Human Intervention
Complete autonomous cycle: detect → analyze → fix → test → deploy → monitor
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End-to-End Workflow Coverage
From failure detection to production deployment, every step runs automatically
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Autonomous Deployment
Fixes deploy directly to production without code reviews or manual approvals
Engineering Teams Need Reliable AI
Current AI evaluation approaches leave engineering teams vulnerable to production issues and constant maintenance overhead.
Common Pain Points
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Production failures from edge cases
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Manual testing after each deployment
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Fragile AI workflows that break unexpectedly
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Time spent debugging instead of building features
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No systematic way to catch prompt degradation
What Teams Need
A continuous, self-healing safety net that catches issues before they impact users and turns fragile AI workflows into resilient, testable systems.
Proactive issue detection
Automatic adaptation
Production confidence
Autonomous Evaluation Cycle
End-to-end autonomous system that runs the complete evaluation workflow: detection → analysis → fix generation → testing → deployment → monitoring. Zero manual intervention required.
Autonomous Detection
Continuously monitors and automatically identifies prompt failures, edge cases, and performance degradation without human oversight.
Autonomous Fix Generation
Generates, tests, and validates prompt improvements automatically using your production data and success patterns.
Autonomous Deployment
Deploys validated fixes directly to production with built-in rollback capabilities. No code reviews or manual approvals needed.
How It Works (vs Their Manual Processes)
Others:
Configure → Test → Review → Manually Fix → Repeat Forever
Barcable:
Deploy → Forget → Ship Better Code
Deploy once
Connect your AI pipeline
Automatic learning
We identify failure patterns and fix them
Silent improvements
Your code gets better without interrupting your workflow
Continuous optimization
Performance improves over time, not over meetings
Complete Autonomous Workflow
Six autonomous capabilities that run the complete evaluation cycle from detection to deployment without human intervention
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Automated Pipelines
Queue and run prompt experiments whenever a new feature is shipped, a flow breaks, or edge cases from users create unseen failure modes.
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Regression Testing
Run features against existing and updated prompts to detect breakages caused by new releases or prompt drift.
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Trace Logging
Provide deep visibility into how agents behave under the hood for debugging and analysis.
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Self-Healing Loops
Maintain experiment context and semantics so the system can suggest or auto-adjust fixes when prompts degrade.
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Prompt-Centric Focus
Prioritize evaluation on prompts (instead of tweaking parameters like temperature).
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Autonomous Deployment
Validated fixes deploy directly to production with automatic rollback capabilities. No manual approvals or code reviews required.
Multimodal Evaluation
Voice, Image, Video, and Text — built to evaluate LLMs across real-world inputs.
Voice
Upload audio, measure transcription accuracy and response latency for spoken prompts.
Image
Test vision understanding with captions, OCR, and grounding on complex scenes.
Video
Evaluate temporal reasoning and narration quality across frames and dynamic contexts.
Text
Score instruction following, factuality, and style with customizable rubrics.
Frequently Asked Questions
Start Autonomous AI Evaluation
Engineering teams get complete autonomous evaluation: detection → analysis → fixes → testing → deployment. Zero human intervention from failure to fix.
Early access for engineering teams. Technical docs included.