Agentic AI Evaluation & Observability
Know Whether Your AI Agents Are Ready for Production.
Find hidden failures, evaluate performance against your business requirements, and generate evidence stakeholders can trust before and after deployment.
What You’ll Discuss
In a focused 30-minute conversation, we’ll help you think through:
- Which agent workflows should be evaluated first
- What rubrics, benchmarks, or human review may be needed
- What evidence your team needs for governance and ship/no-ship decisions
Not ready to discuss yet?
Explore Your Agent Evaluation Use Case
Tell us a little about your agents, and we’ll match you with the right evaluation expert.
Evaluation Demo
See AI Agent Evaluation in Action
Watch how Innodata evaluates agent decisions in a financial crime workflow using trace-level review, custom criteria, and evidence a reviewer can act on.
What to notice: every step is scored against business and regulatory criteria, not just token-level metrics, and failures are flagged with the evidence a reviewer needs to act.
Capabilities
From Agent Risk to Validated Performance
Trace Failures
See where agents break down across workflows, tool calls, reasoning paths, and failure patterns.
Define What Good Means
Create evaluation criteria aligned to your policies, workflows, regulations, and business risks.
Test Before Launch
Evaluate agents against real-world tasks, edge cases, policy expectations, and regulatory requirements.
Monitor in Production
Track quality, safety, drift, latency, compliance, and workflow completion after launch.
Improve With Every Signal
Turn production insights and expert review into refinements for prompts, workflows, rubrics, and datasets.
Prove Every Decision
Generate evidence for ship/no-ship decisions, governance reviews, audits, and model change validation.
Proven Impact
Every Ship / No-Ship Decision, Backed by Data
60-70%
Fewer silent failures
Faster time-to-resolution
Increase in evaluation coverage
35-40%
Reduction in manual effort
12-18%
Improvement in detection precision
SLA compliance target
Industries
Built for High-Stakes AI Agent Workflows
Financial Services
Use Cases
- AML
- Fraud Detection
- Sanctions Screening
- Onboarding
- Customer Service
- Analyst Workflows
How Innodata Helps
- Custom regulatory criteria
- Trace-level decision review
- Human oversight
- Continuous monitoring
- Audit-ready reporting
Insurance
Use Cases
- Claims
- Underwriting
- Policy Review
- Fraud Workflows
- Customer Service
How Innodata Helps
- Domain-specific evaluation
- Human-reviewed scoring
- Escalation testing
- Policy adherence checks
- Quality monitoring
Retail & Consumer Operations
Use Cases
- Customer Support
- Recommendations
- Catalog Operations
- Order Support
- Multilingual Service
How Innodata Helps
- Response quality review
- Brand safety checks
- Escalation testing
- Multilingual evaluation
- Drift monitoring
Legal & Compliance
Use Cases
- Document Review
- Compliance Research
- Contract Analysis
- Policy Review
- Knowledge Retrieval
How Innodata Helps
- Retrieval evaluation
- Hallucination testing
- Citation checks
- Domain-specific scoring
- Expert validation
Get Started
Ready to Find Out Where Your Agents Stand?
Innodata (Nasdaq: INOD) is a global data engineering company. We believe that data and Artificial Intelligence (AI) are inextricably linked. Our mission is to enable the responsible advancement of artificial intelligence by providing the data, evaluation frameworks, and human expertise required to build AI systems that can be trusted at scale. We provide a range of transferable solutions, platforms, and services for Generative AI / AI builders and adopters. In every relationship, we honor our 36+ year legacy delivering the highest quality data and outstanding outcomes for our customers.