Repath vs exprtLabs
A side-by-side comparison built from both listings. Blank cells mean the company has not given that detail; we never guess.
Repath compared with exprtLabs
| Detail | 
Repath | 
exprtLabs |
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| What it does | Canary rollouts for prompts and models with automatic quality gates and rollback
| Foundations for systems that cannot lose their way
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| Stage | Not given
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| Founded | Not given
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| Based in | Not given
| VN
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| Pricing model | Free trial
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| Pricing | 7-day free trial with 1,000 judged evaluations (no card required). Indie: $20/month or ₹1,699/month (3,000 judged evaluations/month). Starter: $49/month or ₹4,099/month (10,000 judged evaluations/month). Pro: $149/month or ₹12,499/month (100,000 judged evaluations/month). Enterprise: custom pricing.
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| Key features | - Canary deployments for prompts and models with progressive traffic steps
- LLM judge scoring responses on helpfulness, accuracy and clarity
- Automatic rollback when quality drops below threshold
- Drop-in replacement for OpenAI-compatible clients
- Support for OpenAI, Anthropic, Gemini, OpenRouter and Vercel AI Gateway
- Request log with prompts, responses, cost and judge verdict
- Failover and routing across providers
- Alerts via email, Slack and webhooks
- Dashboard and API for managing rollouts
- Controller makes routing decisions every 30 seconds
| - Enterprise framework for distributed services
- Protected services and recoverable workflows
- AI agents and team project collaboration
- Records each call and steers next reply
- TypeScript models and validation
- OpenAPI document generation
- Generated code at build time
- Day-two operations support
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| What makes it different | - Automatically detects and rolls back silent quality failures that don't trigger errors or alerts
- Quality decisions based on real traffic and LLM judging, not health checks alone
- Minimal latency overhead of about 0.4ms median in request path
- Every decision audited with exact metrics that triggered routing changes
- Can run in the cloud or inside customer's own network for data privacy
| - Systems built for realities after launch with controls and exception visibility
- Explicit state and controls for auditable, predictable behavior
- Integration boundary design with security and recovery in system design
- Fits existing enterprise services and policies
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| Community votes | 0 | 0 |
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| DR (Domain Rating by Ahrefs) | Not checked yet ● no change since last check | Not checked yet ● no change since last check |
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| Trust Flow (Majestic) | 0 | 0 |
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| Citation Flow (Majestic) | 15 | 0 |
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| Referring domains (Majestic) | 2 | 0 |
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3 details filled in for both companies.
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