# Knowledge Base

Guides and in-depth comparisons covering the questions we get most — on LLM evaluation, observability, and choosing the best AI testing tools and platforms. Updated continuously.

## Playbooks

Step-by-step guides to set up and run LLM evaluation workflows.

### [Playbook Overview](/content/knowledge-base/playbook/playbook-overview/index.html)
What this handbook is for, who should read it, and what you will walk away with.

### [What Makes a Good Eval](/content/knowledge-base/playbook/what-makes-a-good-eval/index.html)
Good evaluation is automated metrics locked to human judgment — neither side alone is enough.

### [What Should I Measure?](/content/knowledge-base/playbook/what-should-i-measure/index.html)
Before you pick a metric, figure out which business outcome it needs to predict — everything else follows from that.

### [When Should I Start Tracing?](/content/knowledge-base/playbook/when-should-i-start-tracing/index.html)
Set up tracing before you need it — everything else (datasets, annotations, evals) depends on having the data flowing first.

### [User-Facing vs. Non-User-Facing Apps](/content/knowledge-base/playbook/user-facing-vs-non-user-facing-apps/index.html)
The same LLM stack does not imply the same definition of quality — user-facing and internal apps optimize different dimensions.

### [Single-Turn vs. Multi-Turn Use Cases](/content/knowledge-base/playbook/single-turn-vs-multi-turn-evaluation/index.html)
Multi-turn failures show up across turns — not in any single response — which is why a separate evaluation strategy matters.

### [Dev, Staging, and Production](/content/knowledge-base/playbook/dev-staging-and-production/index.html)
Evaluation is different work in each environment — dev is for iteration, staging is for regression, production is for monitoring.

### [Setting Up Trigger Moments (Online Evals)](/content/knowledge-base/playbook/setting-up-trigger-moments-online-evals/index.html)
How to choose where to run online evaluations in your LLM app, and in what order.

### [Setting Up AI Agent Observability](/content/knowledge-base/playbook/ai-agent-observability/index.html)
What agent observability actually captures, why traditional application monitoring and generic LLM observability miss agent failures, and how to turn traces into a quality loop instead of a log dump.

### [Evaluating AI Agents](/content/knowledge-base/playbook/how-to-evaluate-ai-agents/index.html)
What to measure at each layer of an agent, how to build a test harness that survives contact with production, and how to gate releases on agent quality without slowing the team down.

### [Setting Up Multi-Turn Agent Observability](/content/knowledge-base/playbook/multi-turn-observability/index.html)
The unit of quality for a multi-turn agent is not the request — it is the thread. How to instrument production agents and chatbots so the conversation is a first-class object in the trace store, not something you reconstruct from a session ID after a complaint comes in.

### [Evaluating Multi-Turn Chatbots](/content/knowledge-base/playbook/evaluating-multi-turn-chatbots/index.html)
A chatbot can score green on every individual reply and still fail the user's actual request twelve turns later. How to evaluate both trace-level turns and conversation-level outcomes with scenario-based simulation and CI gates.

## Compare

In-depth comparisons and rankings of the best LLM evaluation, observability, and AI testing tools and platforms.

### [7 Best Web Search APIs for Grounding LLMs in 2026](/content/knowledge-base/compare/best-web-search-apis-grounding-llms-reducing-hallucinations-2026/index.html)
Compare the seven best web search APIs for grounding LLMs in 2026, including Firecrawl, Brave Search, Exa, Tavily, Parallel, Google Search grounding, and SerpApi.

### [7 Best AI Evaluation Tools for Enterprises in 2026](/content/knowledge-base/compare/best-ai-evaluation-tools-for-enterprises-2026/index.html)
Compare the 7 best AI evaluation tools for enterprises in 2026. We rank platforms by their ability to standardize evals and observability across the org.

### [Top 9 Platforms for Pre-Deployment AI Testing in 2026](/content/knowledge-base/compare/top-8-platforms-for-pre-deployment-ai-testing-2026/index.html)
Compare the top 9 platforms for pre-deployment AI testing in 2026. We rank tools by evaluation depth, testing the app as deployed, and security testing.

### [9 Best LLM Evaluation Tools for Product Managers in 2026](/content/knowledge-base/compare/best-llm-evaluation-tools-for-product-managers-2026/index.html)
Compare the 9 best LLM evaluation tools for product managers in 2026. We rank platforms by no-code accessibility, custom metrics and alignment, and monitoring with dashboards.

### [6 Best LLM Evaluation Tools for Startups in 2026](/content/knowledge-base/compare/best-llm-evaluation-tools-for-startups-2026/index.html)
Compare the 6 best LLM evaluation tools for startups in 2026. We rank platforms by automation and setup speed, production-trace workflows, and startup-friendly pricing.

### [Top 6 Human-in-the-Loop Tools for AI Agent Evaluation (2026, Tested and Reviewed)](/content/knowledge-base/compare/best-human-in-the-loop-ai-agent-evaluation-tools-2026/index.html)
AI agents fail across tool calls, retrieval, and handoffs. We reviewed the six human-in-the-loop tools that get SMEs and QA into AI agent evaluation.

### [Top 8 CI/CD Tools for AI Applications in 2026](/content/knowledge-base/compare/best-ci-cd-tools-ai-applications-2026/index.html)
The eight best CI/CD tools for AI applications in 2026, ranked for LLM regression testing and release gates.

### [Best 7 Tools for Testing LLM Apps Before Production in 2026](/content/knowledge-base/compare/best-tools-testing-llm-apps-before-production-2026/index.html)
The best tools for pre-production LLM app testing, ranked by how well they test whole-app behavior and catch regressions.

### [Top 7 AI Agent Observability Platforms for 2026](/content/knowledge-base/compare/best-ai-agent-observability-tools-2026/index.html)
The seven AI agent observability platforms that matter in 2026 are the ones that score what they capture, surface failing runs, and turn production traces into the next test cycle.