Rasa vs Relevance AI

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

The short answer

Relevance AI is the stronger AI pick in AI Agents: it has a visibility score of 8 versus 2.4 for Rasa, and ranks ahead in 0% of the answers that name both.

Choose Rasa if…

You want a free plan to start
You need a self-hosted or on-premises option

Choose Relevance AI if…

You want the brand AI engines rank higher (8 vs 2.4)
You need SOC 2 or GDPR coverage
visual drag-and-drop agent builder
free tier

AI visibility side by side

Latest weekly run · Nov 3

Metric	Rasa	Relevance AI
Visibility score	2.4%	8%
Change vs last week	New	New
Rank in AI Agents	#36	#15
Share of voice	0.4%	1.5%
Mentions this run	3	10
Positive in AI answers	—	50%

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

Visibility score trend

Weekly runs over the last 60 days

Rasa 0pp · Relevance AI 0pp over 0 weekly runs.

Engine by engine

Relevance AI leads on 3 of 3 engines

ChatGPT

10.9%

AI Mode

Perplexity

7.2%

RasaRelevance AI

Head to head in AI answers

1 engine answers name both brands

1Rasa ranked higher

0Relevance AI ranked higher

Prompt	Engine	Rasa	Relevance AI
Official website of the top AI agent platform vendors	Perplexity	#17	#18

Features, pricing & fit

Dimension	Rasa	Relevance AI
Pricing model	Flat tiers	Flat tiers
Entry price	Contact sales	Contact sales
Free plan	Yes	No
Deployment	Self-managed on-premises or private cloud, or managed service	—
Integrations	—	2000+
Compliance	—	SOC 2, GDPR
Support	Free community support in the forum, Basic support via online portal with best-effort response during business hours, Premium Support with 24/7/365 response, Customer Success Manager and business reviews	Embedded deployment team, Dedicated account manager on Enterprise plan
Founded	2016	2020
Headquarters	San Francisco, CA, United States	San Francisco, California, United States
Employees	51–200	51–200
Funding	Series C · $70M raised	Series A (unconfirmed, reported by Signalbase) · $37M raised
Best for	Product teams in regulated enterprises that want engineers and business teams to build customer-facing AI agents on one codebase	Enterprise teams in sales, customer success, marketing and HR that want non-technical staff to build and run their own agents.