Evaluating agentic systems is complex. SuperAnnotate’s customizable UI gives teams control to visualize, evaluate, and refine agent flows. With drag-and-drop tools and API connectivity, it accelerates dataset creation and performance insights.
Evaluating agentic systems involves unique hurdles. Standard tools fall short of addressing the following challenges:
Obscured Reasoning
Choosing which LLM and embedding model to use can be challenging, especially as high scores on general benchmarks do not translate well to more specific data domains.
Resource-Intensive Dataset Creation
When RAG systems underperform, it’s typically due to complex, hidden bottlenecks. SuperAnnotate’s evaluations provide clarity, pinpointing specific areas for enhancement.
Inflexible Evaluation Tools
Embedding models excel with robust, domain-specific datasets. SuperAnnotate simplifies the dataset creation process, improving model relevance and efficiency.
Limited Accessibility for Domain Experts
Many tools are developer-centric, but SuperAnnotate’s platform allows non-technical experts across your organization to contribute effectively, building robust datasets and fostering trust.
A Smarter Way to Evaluate Agentic Systems
SuperAnnotate simplifies agent evaluation with a data annotation and evaluation platform featuring a fully customizable UI. Adaptable to visualize each agent step and decision path, it lets teams analyze, adjust, and refine workflows for high-quality dataset creation and ongoing optimization.
Adapt to Your Agent Setup
SuperAnnotate’s flexible annotation interface offers complete visibility into each step of an agentic system, including inputs, reasoning paths, and tool use. This allows reviewers to evaluate, refine, edit actions, capture critical performance data, and generate high-quality datasets that support continuous system improvement.
SuperAnnotate integrates with your data and AI platforms, enabling direct imports of agent data like tool actions, decisions, and responses. This streamlined integration enhances your ability to assess and refine agent behaviors.
SuperAnnotate
Tool actions
Decisions
Responses
Amazon Web Services
Azure
Databricks
Snowflake
Google Cloud Platform
Custom Integration
Collaborative Workflows
Engage multiple experts or leverage LLMs as evaluators through collaborative workflows. SuperAnnotate’s interface allows input from diverse roles, ensuring evaluations are informed, thorough, and high-quality.
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EvaluationJMAKAI
Tool use
Reasoning
Task fit
3.7/5Needs revision
Data security
With SOC2 Type 2 and ISO27001 certifications, SuperAnnotate ensures data security in the cloud or on-prem. Role-based access control and data segmentation keep sensitive information secure across teams.