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C3 AI vs Deepgram comparison

 

Comparison Buyer's Guide

Executive Summary

Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Categories and Ranking

C3 AI
Ranking in AI Sales & Marketing
52nd
Average Rating
6.0
Number of Reviews
2
Ranking in other categories
AI Data Analysis (36th), AI Customer Experience Personalization (56th), AI Content Creation (12th), AI Procurement & Supply Chain (14th)
Deepgram
Ranking in AI Sales & Marketing
7th
Average Rating
8.6
Reviews Sentiment
6.0
Number of Reviews
10
Ranking in other categories
Text-To-Speech Services (4th), Speech-To-Text Services (1st), AI Customer Support (5th), AI Scheduling & Coordination (2nd)
 

Mindshare comparison

As of January 2026, in the AI Sales & Marketing category, the mindshare of C3 AI is 0.8%. The mindshare of Deepgram is 0.7%. It is calculated based on PeerSpot user engagement data.
AI Sales & Marketing Market Share Distribution
ProductMarket Share (%)
Deepgram0.7%
C3 AI0.8%
Other98.5%
AI Sales & Marketing
 

Featured Reviews

reviewer2795349 - PeerSpot reviewer
Group Head of Data Strategy & Enterprise Governance at a consumer goods company with 10,001+ employees
Struggled to justify enterprise adoption but have valued broader developer accessibility
If I could change or add anything to improve C3 AI, I would suggest making it not just an AI platform, but a data and AI combined platform, as bringing in data management elements, governance, and cloud features is critical. The real AI and modeling represent only 20 percent of what is needed; there is over 80 percent in the rest of the world that should be addressed. Given Tom Siebel's deep understanding of corporate work and his network, integrating C3 AI with other ERP solutions such as Oracle, SAP, or Microsoft is essential. If C3 AI can be an enterprise platform, embedding more data elements and ensuring seamless integration with other ERP solutions would significantly enhance its capabilities and attractiveness. If someone told me that they have SAP, and C3 AI can seamlessly integrate the data and perform action calls between SAP, allowing me to operate on C3 AI as I would on SAP, that would be a killer feature for me. I would suggest avoiding traditional licensing sales as it is too expensive; the starting price is too high. Considering a subscription model or a pay-per-use model is the best business structure for AI or data solution vendors. The pay-per-use model benefits usage, as the more you use, the more successful you become with the platform.
Arunkumar HG - PeerSpot reviewer
Technology Architect & Hands-On Leader | Prototyping, Automation, AI/LLM Integration | 20+ Years in at Regalix
A Powerful, Adaptable, and Constantly Evolving STT Solution for Voice Automation
Honestly, Deepgram has been exceptionally proactive in addressing the primary area that needed improvement. My main challenge was with the real-time detection of when a user has finished speaking in a live conversation, which is critical for a responsive voice bot. They directly solved this by releasing their Flux model. Because Flux is a recent release, I haven't yet had enough time to thoroughly test it and identify new limitations. At this stage, any "improvement" would be more of a "nice-to-have" feature rather than a fix for an existing problem. The core service is already very robust and meets all of our current needs. What additional features should be included in the next release? ---------------------------------------------------------------- Looking toward the future, here are a few features that could add even more value to an already excellent platform: * Advanced Built-in Analytics: While I can get the raw transcript and build my own analytics pipeline, it would be powerful to have features like sentiment analysis, emotion detection, or automatic summarization offered directly through the API. This would save significant development time. * More Granular Speaker Diarization: For calls with multiple participants, enhancing the real-time speaker diarization (labeling who is speaking) to be even more precise would be a fantastic addition for creating detailed call analyses. * Tighter Integration with TTS: Since Deepgram is also expanding into Text-to-Speech (TTS), offering a more seamlessly integrated STT-to-TTS pipeline could simplify the development stack for creating voice agents from start to finish. * Specialized, Pre-Trained Industry Models: While the general models are highly accurate, offering even more specialized, pre-trained models for specific industries like finance, healthcare, or legal-which are heavy on specific jargon-could push the accuracy even higher for those niche use cases.
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Top Industries

By visitors reading reviews
No data available
Financial Services Firm
10%
Comms Service Provider
9%
University
9%
Computer Software Company
9%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
By reviewers
Company SizeCount
Small Business8
Midsize Enterprise1
Large Enterprise1
 

Questions from the Community

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What is your experience regarding pricing and costs for Deepgram?
My experience with pricing, setup cost, and licensing was good, as I found it to be cheaper without any problems.
What needs improvement with Deepgram?
Even though Deepgram has many customization options, I wish that Deepgram had voice cloning customization to a much larger extent. I also wish that the price were a bit lower if possible.
What is your primary use case for Deepgram?
My main purpose for Deepgram was to convert meeting voices to text very easily, and the other purpose was for content creation. I mostly use Deepgram for those two purposes.
 

Comparisons

No data available
 

Overview

Find out what your peers are saying about C3 AI vs. Deepgram and other solutions. Updated: January 2026.
881,114 professionals have used our research since 2012.