Table of Key Initiatives, Technologies, and Partnerships

Initiative / Product	Technology	Partner(s)	Capabilities	Applications
Tavus Integration	Phoenix Model (NeRF & diffusion)	Tavus (Generative AI video)	Voice and face cloning; text-to-video; lip-sync	Personalized marketing videos; sales demos; onboarding
Salesforce AI Cloud & Einstein GPT	Proprietary LLMs; OpenAI models	OpenAI, Anthropic	Generative content across CRM; potential for video pipelines	Automated email, chat, code generation; content personalization
Waylay Digital Twin (AppExchange)	Real-time IoT & ML	Waylay	Virtual replica of physical assets; predictive analytics	Asset monitoring; proactive maintenance; field service
Ethical AI Maturity Model	Organizational practices & Guardrails	Internal Ethical AI Team	Consent verification; bias mitigation; audit trails	Governance of AI applications, including digital clones

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1. Partnerships with Generative AI Video Startups

Salesforce has embraced partnerships to explore ‘digital replicas’ of humans through generative video technologies. In March 2024, Tavus, a four-year-old generative AI startup, announced a Series A funding round and revealed that companies including Salesforce and Meta are already using its platform to create “digital replicas” of individuals. By integrating Tavus’ APIs into its ecosystem, Salesforce customers can leverage photo-realistic face and voice clones trained in minutes using proprietary Phoenix models that build 3D constructs via neural radiance fields (NeRF) technology. Such partnerships enable Salesforce to offer scalable, personalized video solutions without investing in in-house video-generation R&D.

Salesforce has positioned this capability as part of its broader AI Cloud strategy, enabling customers to generate personalized video content within existing CRM workflows. Integrations include direct API calls for replica training, lip-sync, dubbing, and large-scale campaign APIs that automate campaign orchestration with hosting, metadata, and performance analytics. This partnership model underscores Salesforce’s preference for combining best-in-class generative AI research with its enterprise platform.

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2. Technological Foundations: Phoenix Model and NeRF

At the heart of these digital clone capabilities lies the Phoenix model, a proprietary deep learning architecture developed by Tavus. Phoenix-3, the latest iteration, employs a Gaussian diffusion model to capture full-face rendering, micro-expressions, and dynamic emotion control in real time. By using as little as one to two minutes of unedited video footage, the model generates a 3D digital twin capable of pixel-perfect lip synchronization and identity preservation.

While Phoenix is not native Salesforce technology, the integration of NeRF-based Phoenix pipelines into Salesforce workflows demonstrates the platform’s extensibility. Through Salesforce’s AppExchange and Agentforce platforms, customers can add replica actions alongside other AI-driven automations, bridging proprietary LLMs, third-party generative video, and enterprise data in a unified interface.

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3. Applications of AI-Driven Digital Clones

3.1 Personalized Marketing Videos

By coupling CRM data with digital clones, marketing teams can automate 1:1 video touches at scale. For example, a marketing automation platform can trigger a personalized video that addresses a prospect by name, showcases region-specific offers, and leverages the sales executive’s digital avatar to deliver a more engaging message. Early customers report improved click-through rates and accelerated nurturing cycles compared to static video or text-only campaigns.

3.2 Sales Demo and Onboarding Personalization

In sales workflows, digital clones can reduce friction in prospect engagements. Once a sales rep records minimal training footage, the system can dynamically generate bespoke demo videos tailored to a prospect’s industry and pain-points—without additional live recordings. Similarly, product teams can create scalable onboarding tours that guide thousands of new customers through product features using the original trainer’s digital avatar.

3.3 Digital Avatars in Customer Service

Customer service organizations are piloting digital avatars for asynchronous support. By integrating replica APIs with self-service portals, customers can receive video responses for common inquiries, complete with personalized greetings and contextual explanations. This approach can deflect repetitive tickets and boost satisfaction by combining human-like presence with AI efficiency.

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4. Salesforce AI Cloud and Digital Replication Features

Salesforce’s broader AI Cloud and Einstein GPT roadmap focuses on generative experiences across all clouds. While these offerings primarily target text and data, video generation is a logical next step. Einstein GPT currently powers email generation, code assistance, and chat replies using proprietary large language models and integrations with OpenAI’s ChatGPT. Salesforce’s Trust Layer ensures data privacy, dynamic grounding, and zero-retention policies to protect sensitive information in generative AI workflows.

Plans to natively support video-generation APIs within Einstein GPT or Agentforce would align with this trust-first approach. Current development efforts, such as Anthropic Claude hosting and Model Context Protocol (MCP) for interoperability, lay the groundwork for adding new generative modalities, including digital clones, to Salesforce’s unified AI platform.

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5. Digital Twins in the Salesforce Ecosystem

Although digital clones of individuals remain partner-led, Salesforce offers its own Digital Twin solutions for physical assets. The Waylay Digital Twin AppExchange package provides IoT asset management and predictive maintenance** within the Salesforce Platform**. In parallel, the “Digital Twin: Definition + Benefits” blog articulates how real-time data and AI models can simulate objects, systems, or persons for scenario planning and decision-making. While these primarily address equipment and process twins, the underlying digital twin concept provides a conceptual framework that could extend to person-level clones as the technology matures.

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6. Ethical Considerations and AI Governance

Salesforce has invested heavily in ethical AI practices, guided by its AI Ethics Maturity Model, which outlines four stages of responsible AI governance: Ad hoc, Organized & Repeatable, Managed & Sustainable, and Optimized & Innovative. The model stresses consent verification, bias mitigation, transparent policies, and continuous auditing. Salesforce’s Digital Verification features enforce identity checks and audit trails, ensuring that any digital clone creation is accompanied by informed consent statements and human review steps.

Internally, Salesforce’s Ethical & Humane Use Officer and associated teams lead adversarial testing, stakeholder engagement, and policy integration to safeguard against misuse and discrimination. These governance frameworks extend to generative AI partnerships, mandating that third-party tools like Tavus adhere to verifiable consent processes, automated and human-driven safety checks, and ongoing accountability measures.

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7. Conclusion

While Salesforce does not yet produce an in-house digital clone engine, it has integrated third-party generative video solutions through partnerships (e.g., Tavus) and laid infrastructure within its AI Cloud and AppExchange to support advanced AI modalities. Salesforce’s robust ethical AI governance and Trust Layer ensure that as digital clone capabilities evolve, they will be deployed responsibly, with user consent, bias mitigation, and transparent auditability. Organizations seeking AI-driven replicas today can leverage Salesforce-integrated offerings and prepare for deeper native support in forthcoming Einstein GPT and Agentforce releases.

https://copilot.microsoft.com/shares/M9mRjuWGdvkwG6irZXZio