Cognigy vs Sim

Which one do AI engines recommend, and how do they differ on price, fit and features?

The short answer

Sim is the stronger AI pick in AI Agents: it has a visibility score of 2.3 versus 0.9 for Cognigy, and ranks ahead in 0% of the answers that name both.

Choose Cognigy if…

You prefer a larger, established vendor (201–500 employees)
Recognised as a Forrester Wave Leader for conversational AI
Named among leading customer-service voice and chat platforms
Evaluated in Gartner's Conversational AI Platforms research

Choose Sim if…

You want the brand AI engines rank higher (2.3 vs 0.9)
You need more native integrations (275+ vs 110+)
You need a self-hosted or on-premises option
You need SOC 2 Type II or ISO 27001 or GDPR coverage

AI visibility side by side

Latest weekly run · Nov 3

Metric	Cognigy	Sim
Visibility score	0.9%	2.3%
Change vs last week	New	New
Rank in AI Agents	#61	#39
Share of voice	0.4%	0.7%
Mentions this run	3	5
Positive in AI answers	—	—

The stronger value in each row is marked with a ✓.

Visibility score trend

Weekly runs over the last 60 days

Cognigy 0pp · Sim 0pp over 0 weekly runs.

Engine by engine

Sim leads on 3 of 3 engines

ChatGPT

0.9%

2.8%

AI Mode

Perplexity

1.9%

4.1%

CognigySim

Head to head in AI answers

1 engine answers name both brands

1Cognigy ranked higher

0Sim ranked higher

Prompt	Engine	Cognigy	Sim
Compare the leading AI Agents platforms	Perplexity	#15	#23

Features, pricing & fit

Dimension	Cognigy	Sim
Pricing model	—	Per seat
Entry price	—	Free; paid from $25 per seat / mo
Free plan	—	Yes
Deployment	Standalone or inside NiCE CXone	Cloud-hosted, or self-hosted in your own cloud with Docker or Kubernetes
Integrations	110+	275+
Compliance	—	SOC 2 Type II, ISO 27001, GDPR
Support	—	Dedicated support on the Enterprise plan
Founded	—	2025
Headquarters	Düsseldorf, Germany	San Francisco, CA, United States
Employees	201–500	11–50
Funding	Seed · $175M raised	Series A · $7M raised
Best for	Enterprise customer service and contact center teams	Companies that need to build, deploy, and govern AI agents across the organization with central control over access, spend, and data