About Sentiora
Sentiora monitors what AI applications say to customers in production. You create a project API key and add the SDK, or a REST POST, to the handler that already calls your model, and every production turn is stored rather than sampled. Policies then run on that traffic to surface risky replies, policy misses and prompt injection attempts as findings.
Findings can be opened to see why they were flagged, assigned to someone and resolved, keeping an incident trail in Sentiora instead of Slack. Teams use the evidence from real conversations to tighten prompts and policies and to spot regressions after a change. The loop is described as observe, detect, investigate and improve, and the project shows as connected once a real conversation arrives. The site positions this against sampling chats in a spreadsheet or learning about failures from customer complaints, and it has pricing and FAQ sections.
Key features
- Storage of every production conversation turn
- Policy checks on live traffic
- Detection of risky replies and injection attempts
- Incident assignment and resolution trail
- SDK or REST integration in the model handler
- Regression checks after prompt changes
Good fit for
- Monitoring customer-facing AI assistants
- Investigating a bad AI reply with evidence
Sentiora: questions and answers
- What is Sentiora used for?
- Sentiora is an AI safety platform that records production AI conversations, detects policy violations and gives teams an incident workflow with owners and evidence. It is a good fit for monitoring customer-facing AI assistants and investigating a bad AI reply with evidence.
- How much does Sentiora cost?
- Paid plans for Sentiora start at $99 per month, and there is no free plan. A free trial is available.
- Is Sentiora open source?
- No. Sentiora is proprietary (closed-source) software and can't be self-hosted. In the AI Infrastructure category, open-source options include Opik, Helicone and TraceRoot.
- What are some alternatives to Sentiora?
- Sentiora competes with Galileo, Fiddler AI and Arize AI.
Open-source alternatives to Sentiora
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Opik
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Debug, evaluate, and monitor your LLM applications, RAG systems, and agentic workflows wit
Apache-2.0vs Weights & Biasesβ 22k
Helicone
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π§ Open source LLM observability platform. One line of code to monitor, evaluate, and expe
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TraceRoot
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TraceRoot - open source self improving layer for ai agents YC S25
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Arize Phoenix
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AI Observability & Evaluation
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LangWatch
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The platform for LLM evaluations and AI agent testing
Apache-2.0vs LangSmithβ 4.9k
Laminar
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Laminar - open-source observability platform purpose-built for AI agents. YC S24.
Apache-2.0vs Weights & Biasesβ 3.3k
SaaS alternatives to Sentiora
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Galileo
AI Infrastructure
Evaluation and monitoring platform for generative AI applications
SaaS
Fiddler AI
AI Infrastructure
AI observability and model monitoring platform with explainability
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Arize AI
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Observability and evaluation platform for machine learning models and LLM applications
SaaS
LangSmith
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Observability, tracing and evaluation platform for LLM applications
SaaS
Portkey
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AI gateway and observability platform for managing LLM requests
SaaS
AiSanity
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Quality layer for AI apps that monitors outputs for hallucinations
SaaS

