Free
Free
- Basic testing
- SDK access
Ashr: Observability, Prompts & Evals
Founded 2025|San Francisco, CA|2-10 people|Unknown
What is Ashr?
Ashr is a test and evaluation platform purpose-built for AI agents. Part of YC W2026, it was founded by Shreyas Kaps (Fortune 100 AI agent experience) and Rohan Kulkarni (CTO, ex-Berkeley AI startup exit). Since agents cannot be unit tested like traditional APIs — inputs are unstructured, outputs are probabilistic, and failure modes are creative — Ashr generates synthetic but authentic user stories that flow through your product.
The platform works across voice, text, image, file generation, and multimodal interactions, catching errors that would take hours of manual testing. It includes prompt versioning with inline diffs and pass-rate tracking per version, full test timelines showing every speaker turn, tool call, and response, plus side-by-side comparison of expected vs. actual results.
Teams integrate via SDK and can run evaluations both pre-production and post-production. Users at UC Berkeley and Stanford are already on the platform. Ashr fills the critical gap of systematic, repeatable testing for probabilistic AI systems.
Key features
Core capabilities this platform advertises.
- Multi-modal synthetic testing
- Voice/text/image simulations
- Pre-production agent stress testing
- Error detection
- Automated test generation
Strengths and tradeoffs
What this tool does well, and the limitations to keep in mind.
Pros
- Addresses critical gap in systematic testing for probabilistic AI agents
- Multi-modal coverage across voice, text, image, and file generation is rare
- Free tier lowers adoption barrier for teams evaluating the platform
- Prompt versioning with regression tracking is a strong developer experience feature
- Both founders have prior AI startup experience including a successful exit
Cons
Plans & pricing
What's included in each plan, and how the tiers compare.
Paid
Contact for pricing
- Full multi-modal testing
- Advanced analytics
Common use cases
Teams building multi-modal AI agents
- Agent testing
- Multi-modal QA
- Pre-deployment validation
- Edge case discovery
Using Ashr with Respan
Ashr tests AI agents before deployment while Respan monitors them in production. Together they provide full lifecycle coverage from pre-production testing to production observability.
- Test agent behavior pre-deployment with Ashr and monitor post-deployment with Respan
- Correlate Ashr test results with Respan production metrics
- Use Respan production data to inform Ashr test scenario generation
Run Ashr in production with Respan
10KFree traces/mo
500+Models
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Compare Ashr
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Last verified: March 27, 2026
