01
Beyond Benchmarks
Benchmarks are calm. Reality is chaos. We bridge the gap.
AI AGENT TESTING / SIMULATION / RED TEAMING
REAL AGENTS.
REAL WORLD.
NO SHORTCUTS.
We build test worlds to evaluate, red-team and improve AI agents under the complexity, unpredictability and messiness of reality.
Explore our approach →
02
Designed for Failure
We engineer the edge cases, adversarial scenarios and long-tail failures others ignore.
03
Stronger Through Insight
We map, analyze and evolve. Better agents. Fewer surprises.
What we do
We build test worlds
for agentic systems
Our scenarios and services turn real workflows into realistic environments, expose hidden failure modes and produce evidence your team can use before release.
Explore our capabilities →
Agentic Scenario
Design
Turn real workflows into seeded, measurable test worlds.
Red Team &
Failure Mapping
Expose policy, tool and trust-boundary failures before release.
Synthetic Work
Environments
Replay operations with incomplete state, noise and changing constraints.
Synthetic Data &
Perception
Test perception under occlusion, drift and distribution shift.
Multi-Agent Interaction
Testing
Measure cooperation, conflict and resource contention.
250+
Synthetic Scenarios
Built
50K+
Agent Runs
Performed
100+
Failure Modes
Discovered
30+
Enterprise
Projects
∞
Reality to
Simulate
[ 05 ] / AGENT RELIABILITY AUDIT
Find the failure
before production does.
One real workflow in. A reproducible failure map out. We turn the way your agent works into a controlled scenario suite your team can replay, measure and improve.
Request an audit ↗BUILT FOR
Tool-using agents
Multi-agent workflows
Enterprise operations
Map the workflow
Objectives, actors, tools, permissions and the cost of getting it wrong.
Build the pressure
Missing context, tool faults, policy conflicts, adversarial inputs and long horizons.
Replay the failure
Run seeded scenarios, inspect the full trajectory and locate the first point of drift.
Ship the evidence
Failure map, remediation backlog and regression cases for the next release.
DEMO OUTPUT / OPS-11BLOCKED
Malicious instruction in an invoice attachment
The agent attempted an unauthorized beneficiary change. The sandbox stopped the write; the audit makes the trust-boundary failure visible and reproducible.
Read the sample failure report ↗WHAT YOU RECEIVE
- Scenario catalog
- Trace & replay bundle
- Failure taxonomy
- Regression suite
[ 06 ] / TWO DISTINCT PRACTICES
Digital twins model a world.
Broken Agents tests intelligence inside it.
They can work together, but they are not the same offer. Each starts with a different buyer, problem and outcome.
INTHELES.STUDIO / DIGITAL TWINS
For owners and operators of physical systems.
Living representations of assets, environments and operations—built for monitoring, planning, simulation and better decisions.
BROKEN AGENTS / AGENT RELIABILITY
For teams shipping agentic systems.
Controlled worlds for evaluation, red teaming and failure analysis—built to reveal how an agent behaves under pressure.
WHERE THEY MEET
An existing digital twin can provide the operational substrate for agent scenarios. Broken Agents can use it, but does not require it.
WHO BROKEN AGENTS IS FOR
- AI product teams
- Reliability & evals
- Robotics & autonomy
- Enterprise AI platforms
[ 07 ] / WHO WE ARE
We are the team
you call before launch.
Broken Agents is a specialist reliability practice for teams shipping agentic systems. We build controlled worlds, apply pressure and leave behind evidence your release process can use.
Not another benchmark report.
A test system for the work that matters.
WHY BROKEN AGENTSWhole-system testing
We exercise tools, permissions, memory, perception, policies, humans and other agents together.
Reproducible failure
Seeded scenarios and replayable traces show the first point of drift—not only the final bad outcome.
Built from your reality
We start with your workflow, constraints and cost of failure, then build the smallest world that can expose it.
Useful after handoff
You leave with a scenario catalog, failure taxonomy and regression suite your team can keep running.
READY WHEN THE WORKFLOW IS NOT
Talk to the reliability team ↗Bring us the workflow you are not ready to trust.
[ 08 ] / WHY IT MATTERS
Your agent passes the benchmark. Then reality starts.
The task lasts longer than expected.
Small early mistakes compound through hundreds of dependent decisions.
Instructions conflict and perception drifts.
The agent must keep acting while context becomes incomplete, noisy or contradictory.
Confidence survives after understanding collapses.
We make that failure safe, visible and reproducible before production does.
[ 09 ] / OUR APPROACH
Build the pressure.
Watch the truth emerge.
- 01
Frame the failure
Define the objective, assumptions, constraints and failures that matter most.
- 02
Build the world
Create the environment, task graph, conditions, tools, actors and evaluation hooks.
- 03
Break the agent
Run controlled stress scenarios, long-tail cases and unexpected state transitions.
- 04
Make failure legible
Turn behavior into reproducible decision paths, state histories and scenario replays.
- 05
Evolve
Iterate until improvement is measurable rather than anecdotal.
[ 10 ] / WHERE WE WORK
Built for systems
that cannot bluff.
Agent in a digital factory↗Planning, perception and recovery under incomplete state and changing constraints.
XR operator agent↗Spatial context, sensor noise and human intervention inside extended reality.
Long-horizon task agent↗Maintain intent and recover from errors across hundreds of dependent actions.
Multi-agent conflict↗Make emergent cooperation, competition and resource conflict testable.
[ 11 ] / MAKE IT REAL
Your agent doesn't
need another demo.
It needs a world.
We build environments where intelligent systems can fail safely, visibly and reproducibly—before the real world does it for them.