About Dusker AI

Enterprise AI AgentBenchmarking & Evaluation

We help organizations measure, validate, and deploy AI agents using real-world tasks, real tools, and production-grade evaluation methods—not synthetic demos or academic benchmarks.

As AI agents move from experimentation to production, enterprises face a critical gap: knowing whether an agent will actually work—safely, consistently, and at scale—inside real systems. Dusker AI exists to close that gap.

The Problem

Why Dusker AI Exists

Most AI failures in production don't come from model capability alone—they come from:

Incorrect Tool Usage

Agents calling wrong tools or passing invalid parameters

Long-horizon Failures

Breaking down on multi-step tasks that require planning

Silent Regressions

Performance degradation after model or prompt updates

Unsafe Behavior

Unreliable or risky actions in production environments

No Pre-Deploy Eval

Lack of objective evaluation before going live

Dusker AI was built to address these problems directly.

We focus on how AI agents behave in real environments—across terminals, operating systems, APIs, and enterprise tools—and provide enterprises with clear, quantitative evidence of agent readiness.

Our Focus

Exclusively AI Agents

Not general AI consulting. We go deep where enterprises need confidence the most.

Agent Benchmarking

Measuring agent performance on real, tool-driven tasks that reflect production conditions.

Agent Evaluation

Validating reliability, safety, reasoning, and failure handling before deployment.

Enterprise AI Agent Deployment

Supporting evaluation-first architectures and deployment readiness for enterprise workflows.

This narrow focus allows us to go deep where enterprises need confidence the most.

Our Philosophy

Evaluation-First Approach

Dusker AI follows an evaluation-first philosophy. Before an AI agent is trusted in production, we believe it must be:

  • Objectively benchmarked
  • Stress-tested on real tasks
  • Evaluated for failure modes and risk
  • Continuously monitored after deployment
Methodology

Industry-Aligned Frameworks

Our methodologies are inspired by and aligned with industry-leading benchmarking frameworks, while extending them to enterprise-specific use cases and constraints.

Terminal-BenchSWE-BenchOS-Level Evaluations
Built for Enterprise

Meeting Enterprise Expectations

Dusker AI works with enterprises that require production-grade standards for security, governance, documentation, and operational readiness.

Reliable & Repeatable

Consistent results you can trust

Clear Metrics

Performance metrics and reporting

Risk Visibility

For leadership and compliance

Long-term Stability

Not one-off demos

We design our evaluations and deployments to meet enterprise expectations for security, governance, documentation, and operational readiness.

Our Partners

Who We Work With

Dusker AI partners with:

  • Enterprises deploying AI agents in production
  • AI platform teams building agent frameworks
  • Organizations transitioning from pilots to real-world AI adoption

Whether validating a single critical agent or evaluating agent systems at scale, our goal remains the same: make AI agents predictable, trustworthy, and production-ready.

Our Mission

“To enable enterprises to deploy AI agents with confidence—backed by rigorous evaluation, transparent benchmarking, and continuous reliability assurance.”

Ready to Deploy Reliable AI Agents?

Partner with us to benchmark, evaluate, and deploy AI agents that work in production.