Viven, a new AI startup spun out by the co-founders of Eightfold, has emerged from stealth with a $35 million seed round led by Khosla Ventures, with participation from Foundation Capital, FPV Ventures, Operator Collective, and a group of angel investors. 

Viven’s mission is bold: to create digital twins of employees -  personalized AI models that replicate how individuals think, communicate, and act, drawing from their internal documents, emails, Slack messages, and other knowledge sources. These twins can respond to queries, brief on past context, and ensure knowledge continuity when someone is absent. 

Leadership is shared by Ashutosh Garg and Varun Kacholia, the same duo behind Eightfold, who bring deep experience in AI, enterprise systems, and scaling category-defining platforms. 

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The Problem Viven Aims to Solve

In modern organizations, a frequent- but underappreciated- challenge is knowledge silos, delays, and “who-knows-what” dependency. When key contributors are unavailable- on vacation, in meetings, time zones apart- teams stall while waiting for answers.

Viven’s twins let colleagues query the “digital version” of someone to retrieve context, summaries, or responses -  as though the person were there. Crucially, it’s not a free-for-all: Viven implements pairwise privacy, meaning the twin only reveals what’s appropriate between two parties, along with role-based permissions and audit logs. 

Already, Viven is live with enterprises such as Genpact, Eightfold, and Josh Bersin Company. In one deployment at Genpact, the platform was rolled out across leadership within 8 weeks, and executives saw smoother collaboration and continuity of knowledge across roles. 

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Market Context & Strategic Timing

Viven’s launch comes at a moment when both enterprise AI and digital twin markets are accelerating:

• The digital twin market (including enterprise and simulation) is forecast to grow into the tens of billions in the coming decade, as companies adopt simulation, context layering, and generative modeling.
  
• Enterprises are investing heavily in AI systems that enhance collaboration, institutional memory, and cross-silo knowledge flow- areas where generative systems traditionally struggle with context and consistency.
  
• As generative AI becomes woven into core operations, the ability to retain context, surface relevant knowledge, and scale individual knowledge is becoming a competitive advantage.
  

Viven’s “twin for every employee” vision positions it to capture a foundational layer of enterprise intelligence -  not just a chatbot overlay, but a connected neural fabric across roles, departments, and history.

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A Founder Lever Hidden in the Twin Strategy

One of the most powerful lessons from Viven’s narrative isn’t in the code -  it’s in how they frame adoption as a knowledge continuity play, not as yet another assistant.

Most AI startups pitch “productivity gains” or “smart assistants.” Viven pitches preserving institutional memory and bridging absence gaps. That shift matters. In large enterprises, what leaders fear is not slow tools- it’s information loss, context erosion, and decisions made in ignorance.

When building AI for organizations, your highest leverage is not in automating a task -  it's in protecting what would be lost without you.

By anchoring its value to continuity and context, Viven repositions itself from “nice-to-have AI feature” to “essential insurance for knowledge.” Founders in enterprise tech should pattern-match this: in any system where roles, personnel, or knowledge flow change, the biggest friction is what vanishes. The stronger your product prevents that vanishing, the harder it is to replace or ignore.

Viven doesn’t just sell AI agents. It sells a guarantee: your team’s context doesn’t die when people step away or move on. That’s a narrative that resonates deeply in legacy enterprises.

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Building & Scaling the Twin Platform

With $35M in seed capital, Viven will accelerate:

• Technical development of twin models (memory, summarization, predictive inference)
  
• Product integrations with email, workspace tools, CRM, internal docs, and enterprise data stores
  
• Enterprise pilots and client onboarding at scale
  
• Scaling twin inference pipelines while managing privacy, latency, and cost
  

Some of the key challenges ahead:

• Scalability and model cost: Maintaining quality, latency, and responsiveness at scale across thousands of employees will demand efficient infrastructure.
  
• Privacy and control: Because twins ingest personal and work data, fine-grained access control, audit trails, and legal compliance matter deeply.
  
• User trust & adoption: Teams must trust that queries won’t leak sensitive information, and that the twin’s answers reflect real context rather than hallucinations.
  
• ROI demonstration: Enterprises will demand measurable gains in decision velocity, fewer follow-ups, and reduced knowledge friction to justify deployment.
  

The backing of Khosla Ventures, Foundation Capital, and FPV Ventures signals confidence not only in the technical vision but in the founding team’s ability to execute at this ambitious frontier.

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Why This Seed Raise Matters

Viven’s seed round is more than capital -  it marks a paradigm shift in how we think about AI systems at work. Instead of building agents that answer questions, Viven aims to build agents that become extensions of people, preserving context, bridging absence, and accelerating decision-making across shifting roles.

For enterprises, that means less friction when team members leave, fewer bottlenecks waiting on responses, and continuity in institutional knowledge. For founders in enterprise AI, the lesson is clear: the real battleground isn’t functionality -  it's continuity of context.

As organizations evolve, a system that can grow with the flow of roles, memory, and processes will win more than one that just automates a task. Viven looks bold -  and in a world where knowledge is power, a twin that holds that power might just become indispensable.

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