Gong
Gong analyses sales calls, emails, and meetings for coaching, deal risk, and forecasts.
Overview
- Transparency
- 5 / 10
- Trust
- 95 / 100
Trains on your data
- Free
- No
- Paid
- No
- Opt-out
- Not captured
Incidents
1- highGong customer data exposed in Klue third-party breach
Assessed SEP 21, 2026 · Checked by hand SEP 21, 2026
Gong asserts SOC 2, ISO 27001, GDPR and HIPAA and prohibits generative-model training; its Klue disclosure confirms limited user-data exposure through a third-party integration.
Trust breakdown
95 / 100
Overall trust score
Data and privacy
Trains on your data
No training on user data
Storage regions
Sub-processors
Data retention
Upon 30 days following termination or expiration of the Agreement, Gong shall delete all Customer Data in its possession or control.
Deletion: Upon 30 days following termination or expiration of the Agreement, Gong shall delete all Customer Data in its possession or control.
Incidents
2026-06-19
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Gong uses a multi-model AI system with in-house AI models that are purpose-built and tuned specifically for revenue teams. These models are trained on a large dataset of customer interactions and deal lifecycles, and then customized for individual businesses. They also support Model Context Protocol (MCP) for interoperability with other AI systems.
Integrations and access
Integrations
Available on
Pricing
Customized Proposal
Custom
Gong's pricing model depends on factors specific to your team, including licenses priced per user and a platform fee based on the number of users supported. There is also a one-time onboarding fee. Add-on modules like Gong Forecast, Gong Engage, Enable Essentials, and Data Cloud carry additional per-user costs. Pricing is not publicly available and requires a customized proposal. Estimates from third-party sources suggest a platform fee of $5,000-$50,000 annually, per-user licenses for the 'Foundations' tier at $1,300-$1,600 per user per year, and onboarding fees ranging from $2,000-$65,000+.
Prices as listed on SEP 21, 2026; check the vendor's page.
Moat and openness
Moat
- Proprietary Model
- Proprietary Data
- Network Effects
- Switching Costhigh
- Unique UX
- Distributionstrong
Gong possesses a strong moat due to its proprietary, in-house AI models trained on a vast, unique dataset of revenue interactions, creating a data network effect. The deep integration into revenue workflows and customized solutions for large enterprises result in high switching costs, further solidifying its market leadership.
Openness
- Open model weights
- Published research
- Open source contributions
- Transparency reports
- Public safety evals
Gong demonstrates a moderate level of transparency, particularly concerning data privacy, security, and compliance. They provide extensive information on their certifications (ISO 42001, SOC 2, GDPR, CCPA), data protection measures (encryption, retention policies, granular access controls), and offer customers control over their data. They also publish research on AI trust and transparency. However, they are less transparent about their AI models, specifically regarding the use of external models, training data, and model explainability. There is no indication of open-source contributions or public safety evaluations.
Company
Gong
- Founded
- 2015
- HQ
- San Francisco, California, United States
- Site
- gong.io
Popularity
Not disclosed
monthly visits
Notable customers
Gong Revenue AI OS is a leader in the Revenue AI market, with over $500 million in annual recurring revenue and serving more than 5,000 companies globally, including half of the Fortune 10.
Value and ROI
What it should move: It improves seller training, forecast accuracy, and message consistency.
Best fit
It fits teams whose managers cannot review enough calls themselves.
The catch
Gong records customers. Check consent, retention, and training use before rollout.
- Chime: Uses Gong across its B2B team for forecasting and efficiency.[1]
- Culture Amp: Uses Gong for forecast accuracy and global sales training.[2]
In our stacks for