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Sentrial — Observability, Prompts & Evals Platform
Founded 2025|San Francisco, CA|2-10 people|Unknown
What is Sentrial?
Sentrial is a production monitoring platform purpose-built for AI agents — positioned as "Datadog for Agent Reliability." Part of YC W2026, it was founded by Neel Sharma (CEO, UC Berkeley CS, ex-Sense) and Anay Shukla (UC Berkeley CS, deployed DevOps agents at Accenture).
The platform semantically detects when agents loop, hallucinate, misuse tools, or frustrate users in production, then helps engineering teams diagnose the root cause and fix it fast. Integration requires just a few lines of code via SDK or MCP. Sentrial learns what "correct" looks like for each workflow and flags drift from expected behavior.
The founders built Sentrial after encountering real production failures: a support agent misclassifying refund requests as product questions, and a document drafting agent hallucinating missing sections. Traditional observability tools track latency and errors but cannot semantically evaluate whether an agent's output is actually correct — Sentrial fills this gap with AI-native monitoring.
Key features
Core capabilities this platform advertises.
- Agent failure root cause analysis
- Tool selection monitoring
- Cost budget tracking
- Production agent observability
- Real-time alerting
Strengths and tradeoffs
What this tool does well, and the limitations to keep in mind.
Pros
- Addresses genuine growing pain point as agents move into production
- Semantic detection of loops, hallucinations, and tool misuse goes beyond basic logging
- Low-friction integration with just a few lines of code via SDK or MCP
- Proven Datadog-for-X positioning in enterprise software
- Founders have relevant agent deployment experience at Sense and Accenture
Cons
- No disclosed customers, revenue, or traction metrics
- Early feedback flagged website bugs — ironic for a reliability company
- Defining wrong agent behavior universally is technically very challenging
- Incumbents like Datadog and LangSmith are adding agent observability features
Plans & pricing
What's included in each plan, and how the tiers compare.
Paid
Contact for pricing
- Semantic agent monitoring
- Root cause analysis
- SDK + MCP integration
- Real-time alerting
Common use cases
Teams running AI agents in production
- Agent reliability monitoring
- Cost optimization
- Failure debugging
- Production observability
Using Sentrial with Respan
Sentrial monitors agent behavior semantically while Respan monitors the underlying LLM calls. Together they provide both behavioral and infrastructure-level observability.
- Combine Sentrial semantic detection with Respan LLM trace analysis
- Correlate agent behavior issues with LLM performance metrics in Respan
- Use Respan cost data alongside Sentrial quality monitoring
Best Sentrial alternatives & competitors
Top companies in Observability, Prompts & Evals you can use instead of Sentrial.
Respan
LLM tracing, evals, and gateway
LangSmith
Trace visualization for LLM chains
Weights & Biases
ML experiment tracking
MLflow
OpenTelemetry-native tracing
Arize AI
ML observability with LLM support
Langfuse
Open-source LLM observability
Helicone
Datadog LLM
LLM monitoring within Datadog platform
Traceloop
OpenTelemetry
Braintrust
Real-time LLM logging and tracing
HoneyHive
Prompt management
Patronus AI
Automated LLM evaluation platform
Promptfoo
Phoenix
OpenTelemetry-based LLM and agent tracing
Portkey
Humanloop
Sentry
DeepEval
Ragas
RAG-specific evaluation framework
LangWatch
Multi-turn agent simulation testing
Galileo AI
LLM output quality evaluation
PromptLayer
Maxim AI
Distributed tracing for LLM and agent apps
Confident AI
DeepEval open-source evaluation framework
Opik
Agenta
Lunary
Future AGI
Multimodal evaluation (text, image, audio, video)
Parea AI
Moda
Hallucination detection
Ashr
Multi-modal synthetic testing
Athina AI
Chamber
ML infrastructure automation
Compare Sentrial
Side-by-side comparisons with other tools in this category.
Best integrations for Sentrial
Companies from adjacent layers in the AI stack that work well with Sentrial.
Last verified: March 27, 2026