Kashikoi

Talk to the Founders

Kashikoi

Talk to the Founders

Kashikoi

Backed by Y Combinator

Benchmark your AI with 1 prompt. No code.

Kashikoi simulates real-world interactions to autonomously evaluate your agent - stop babysitting evals and ship with confidence!

Book a Demo

SOC AI Analyst

Explore Example →

Threat Detection

85.7%

▲ 6/7 correct

Actionable Recs

85.7%

6/7 actionable

False Positives

14.3%

▼ 1/7 false positives

Severity Accuracy

71.4%

5/7 correct

Performance Summary

Threat Detection Needs Improvement - 85.7%

Broaden training coverage to better capture emerging threat patterns

✓

Good Actionability - 85.7%

Enhance clarity and context in recommendations to improve analyst follow-through

✗

High False Positive Rate - 14.3%

Tighten alert logic to reduce noise and improve analyst efficiency

Good Severity Assessment - 71.4%

Improve prioritization consistency to sharpen response focus on critical incidents

SOC AI Analyst

Explore Example →

Threat Detection

85.7%

▲ 6/7 correct

Actionable Recs

85.7%

6/7 actionable

False Positives

14.3%

▼ 1/7 false positives

Severity Accuracy

71.4%

5/7 correct

Performance Summary

Threat Detection Needs Improvement - 85.7%

Broaden training coverage to better capture emerging threat patterns

✓

Good Actionability - 85.7%

Enhance clarity and context in recommendations to improve analyst follow-through

✗

High False Positive Rate - 14.3%

Tighten alert logic to reduce noise and improve analyst efficiency

Good Severity Assessment - 71.4%

Improve prioritization consistency to sharpen response focus on critical incidents

AI Data Analyst

Explore Example →

Accuracy Score

40%

↓ 0%

Test agent success rate

Context Understanding

60%

↑ +20%

Correctly interpreted context

Pivot Match Rate

10%

↓ -30%

Exact numerical accuracy

Comparison Breakdown by Metric

Basic Accuracy

Context Understanding

Pivot Match

Both Good

GPT-4 Better

GPT-5 Better

Both Failed

AI Data Analyst

Explore Example →

Accuracy Score

40%

↓ 0%

Test agent success rate

Context Understanding

60%

↑ +20%

Correctly interpreted context

Pivot Match Rate

10%

↓ -30%

Exact numerical accuracy

Comparison Breakdown by Metric

Basic Accuracy

Context Understanding

Pivot Match

Both Good

GPT-4 Better

GPT-5 Better

Both Failed

OpenAI vs. Perplexity

Explore Example →

Interview Details

Selected PromptSummarize the key economic impacts of climate change on global agriculture output

InterviewerAnthropic/Claude

Conversation Selector

Aggregated Metrics

ⓘBest Response: Both

28/54

ⓘBest Response: GPT

4/54

ⓘBest Response: Perplexity

22/54

ⓘBest Response: Neither

0/54

⚙️

Fully Customizable to Your Needs

Tailor metrics, comparisons, and visualizations to your exact requirements

Code Explorer

Explore Example →

OVERALL SCORE

85%

17/20 passed

+12% vs Base

ACCURACY RATE

17/20

85% accurate

AVG RESPONSE

2.3s

Token: 4.2K

SCENARIOS

8/10

PASSED

Performance by Task Type

Architecture Decision3/3

100%

Change Proposal2/2

100%

Solution Evaluation4/4

95%

Impact Assessment3/3

88%

Code Analysis3/4

75%

Refactor Planning2/3

67%

Key Insights

✓Excels at architectural decisions

✓Strong solution evaluation (95%)

✓Reliable change impact assessment

Areas for Improvement

⚠Code Analysis (75% accuracy)

⚠Refactor Planning (67% accuracy)

Code Explorer

Explore Example →

OVERALL SCORE

85%

17/20 passed

+12% vs Base

ACCURACY RATE

17/20

85% accurate

AVG RESPONSE

2.3s

Token: 4.2K

SCENARIOS

8/10

PASSED

Performance by Task Type

Architecture Decision3/3

100%

Change Proposal2/2

100%

Solution Evaluation4/4

95%

Impact Assessment3/3

88%

Code Analysis3/4

75%

Refactor Planning2/3

67%

Key Insights

✓Excels at architectural decisions

✓Strong solution evaluation (95%)

✓Reliable change impact assessment

Areas for Improvement

⚠Code Analysis (75% accuracy)

⚠Refactor Planning (67% accuracy)

Code Explorer

Explore Example →

OVERALL SCORE

85%

17/20 passed

+12% vs Base

ACCURACY RATE

17/20

85% accurate

AVG RESPONSE

2.3s

Token: 4.2K

SCENARIOS

8/10

PASSED

Performance by Task Type

Architecture Decision3/3

100%

Change Proposal2/2

100%

Solution Evaluation4/4

95%

Impact Assessment3/3

88%

Code Analysis3/4

75%

Refactor Planning2/3

67%

Key Insights

✓Excels at architectural decisions

✓Strong solution evaluation (95%)

✓Reliable change impact assessment

Areas for Improvement

⚠Code Analysis (75% accuracy)

⚠Refactor Planning (67% accuracy)

How It Works

From Agents to Insights in 3 Steps

From agents to insights - test, evaluate, and improve your AI in three simple steps.

How It Works

From Agents to Insights in 3 Steps

From agents to insights - test, evaluate, and improve your AI in three simple steps.

How It Works

From Agents to Insights in 3 Steps

From agents to insights - test, evaluate, and improve your AI in three simple steps.

Connect your agents

We support custom integrations for your AI stack. We will build the connectors you need to ensure full coverage during testing

YOUR AGENTS

💬

Support Bot

📊

Data Agent

💻

Code Assistant

CONNECT

→

TESTING PLATFORM

🎯

Your Platform

Test in realistic
scenarios

Connect your agents

We support custom integrations for your AI stack. We will build the connectors you need to ensure full coverage during testing

YOUR AGENTS

💬

Support Bot

📊

Data Agent

💻

Code Assistant

CONNECT

→

TESTING PLATFORM

🎯

Your Platform

Test in realistic
scenarios

Connect your agents

We support custom integrations for your AI stack. We will build the connectors you need to ensure full coverage during testing

YOUR AGENTS

💬

Support Bot

📊

Data Agent

💻

Code Assistant

CONNECT

→

TESTING PLATFORM

🎯

Your Platform

Test in realistic
scenarios

Run realistic simulations

Test agents against many customizable scenarios, track performance metrics, and identify edge cases

Active Simulations

Running

Customer Support1247 runs

Success Rate94%

Avg: 1.8s

Cost: $0.045

Data Extraction892 runs

Success Rate87%

Avg: 2.1s

Cost: $0.063

3.7K

Total Runs

89%

Avg Success

Run realistic simulations

Test agents against many customizable scenarios, track performance metrics, and identify edge cases

Active Simulations

Running

Customer Support1247 runs

Success Rate94%

Avg: 1.8s

Cost: $0.045

Data Extraction892 runs

Success Rate87%

Avg: 2.1s

Cost: $0.063

3.7K

Total Runs

89%

Avg Success

Run realistic simulations

Test agents against many customizable scenarios, track performance metrics, and identify edge cases

Active Simulations

Running

Customer Support1247 runs

Success Rate94%

Avg: 1.8s

Cost: $0.045

Data Extraction892 runs

Success Rate87%

Avg: 2.1s

Cost: $0.063

3.7K

Total Runs

89%

Avg Success

Ship better agents faster

Use our actionable insights and synthetic data to optimize prompts, fine-tune models, and boost agent performance

⚡

Performance Insights

Based on 1,247 simulations

✓Accuracy

73%→94%

⚡Response Time

3.2s→1.1s

$Cost per Call

$0.08→$0.04

847

Synthetic data points

Prompts optimized

Ship better agents faster

Use our actionable insights and synthetic data to optimize prompts, fine-tune models, and boost agent performance

⚡

Performance Insights

Based on 1,247 simulations

✓Accuracy

73%→94%

⚡Response Time

3.2s→1.1s

$Cost per Call

$0.08→$0.04

847

Synthetic data points

Prompts optimized

Ship better agents faster

Use our actionable insights and synthetic data to optimize prompts, fine-tune models, and boost agent performance

⚡

Performance Insights

Based on 1,247 simulations

✓Accuracy

73%→94%

⚡Response Time

3.2s→1.1s

$Cost per Call

$0.08→$0.04

847

Synthetic data points

Prompts optimized

FAQ's

FAQs

Here are answers to the most common things people ask before getting started.

FAQ's

FAQs

Here are answers to the most common things people ask before getting started.

FAQ's

FAQs

Here are answers to the most common things people ask before getting started.

Why Simulation?

Testing AI agents in production is risky and expensive. Simulation lets you catch failures before they reach real users, so you can fix issues safely and quickly.

Do I really only have to write 1 prompt?

How do you automate evals?

How does the integration work?

How much does it cost?

Why Simulation?

Testing AI agents in production is risky and expensive. Simulation lets you catch failures before they reach real users, so you can fix issues safely and quickly.

Do I really only have to write 1 prompt?

How do you automate evals?

How does the integration work?

How much does it cost?

Why Simulation?

Testing AI agents in production is risky and expensive. Simulation lets you catch failures before they reach real users, so you can fix issues safely and quickly.