From GPU to Model: Together AI Powers the AI Pipeline
1. How do you define “growth” at Together AI — are you focusing on user adoption, revenue, market expansion, model usage, or something else?
At Together AI, growth and marketing is a multi-dimensional concept that includes all of the above. We're operating at the intersection of product-led growth and enterprise sales, which means we need to think about growth in terms of both scale and depth.
On one side, we’re driving adoption through self-serve experiences, model usage, and community engagement. On the other, we’re building relationships and expanding accounts through a more traditional sales motion. We also support a mix of developer, consumer, and enterprise users, so growth means something slightly different across each segment.
Ultimately, growth at Together AI means launching new programs, expanding usage, accelerating time-to-value, and owning the key metrics that tie those activities back to long-term business outcomes like revenue, retention, and market leadership. It’s about moving fast while building in a way that compounds over time.
2. With competitors ranging from hyperscaler GPU clouds to serverless LLM platforms, what’s your core positioning strategy?
Together AI is positioned as the “AI Acceleration Cloud” - a comprehensive, full-stack solution that supports customers at every stage of their AI journey.
Whether you're just beginning to experiment with models or deploying mission-critical applications at scale, we provide the hardware, compute, tools, and flexibility needed to move fast and scale confidently. Unlike point solutions, our integrated stack bridges infrastructure, models, and deployment into a single cohesive platform.
3. Open‑source models like RedPajama and jointly developed research like FlashAttention are pillars of Together’s strategy. How do you use these to drive growth?
Our open-source initiatives are key drivers of both innovation and adoption. Projects like RedPajama and FlashAttention help us earn credibility and visibility within the research and developer communities. They create a flywheel of engagement – developers build with our models, researchers publish on our innovations, and enterprises see a trusted platform backed by cutting-edge work.
Our in-house research team, which includes multiple professor-founders (ex. Chris Re, Percy Liang etc.), plays a central role in sustaining this momentum and reinforcing Together AI as a thought leader in the space.
4. Partnerships like the recent Refuel.ai acquisition add data prep and integration value. How are you activating these in the field?
By integrating Refuel.ai’s specialized models and orchestration capabilities into the Together AI Platform, we’re not only removing one of the biggest roadblocks in AI development – dealing with unstructured, messy data – but also enabling our customers to use their data with greater speed, accuracy, and scale.
The acquisition marks a significant step forward in our mission to accelerate the development of production-grade AI applications.
5. How do you work with infrastructure partners — e.g., cloud, on‑prem deployments, GPU vendors — to scale awareness and adoption?
We view the AI infrastructure landscape as an interconnected ecosystem, not a zero-sum game. Strategic collaboration with hyperscalers, GPU vendors, and on-prem partners is critical to our go-to-market and scaling efforts. These relationships allow us to optimize resource availability, expand global reach, and tailor deployments to meet diverse customer requirements. Whether it's securing GPU supply or integrating with existing enterprise infra, we work hand-in-hand with partners to maximize performance and value for our customers.
6. As open-source demand grows rapidly, how do you ensure scale without compromising performance, support, and infrastructure cost efficiency?
Flexible Deployment Options: You can choose between serverless API endpoints (pay-as-you-go) and dedicated endpoints (reserved capacity with per-minute billing), allowing you to scale your deployment based on your traffic demands.
Horizontal and Vertical Scaling: Together AI offers flexible scaling options to ensure your deployment can handle traffic spikes and growth.
Optimized Inference Engine: Together AI's inference engine is designed for speed and efficiency, enabling fast processing of even complex AI tasks and large-scale deployments.
7. One growth channel you think is under‑leveraged in AI infrastructure today?
Top-of-funnel and brand marketing remain underutilized in AI infrastructure. Many teams focus heavily on bottom-of-funnel channels because they offer direct attribution and measurable ROI. But in a category as new and complex as AI, long-term growth depends just as much on trust and education as it does on performance marketing.
Even with all the attention around AI, we're still in the early days of true enterprise adoption. Buyers are often navigating unfamiliar technology, and they want to work with partners they trust to guide them through that process. A strong brand helps convey that trust. It positions a company as credible, forward-looking, and capable of supporting customers over the long term.
Investing in brand isn't just about visibility – it's about creating a durable advantage in a market where confidence and clarity matter as much as features and price.
8. Role models or mentors who shaped your approach to GTM in this space?
I really admire the team at Ramp and how they’ve managed to transform a traditionally “unsexy” category like corporate cards and payments into one of the most memorable and innovative brands of this decade. They take creative risks, run thoughtful experiments, and aren’t afraid to challenge the status quo. Their approach is confident, original, and highly effective.
What stands out to me is their view of go-to-market as a continuous journey rather than a one-time transaction. That perspective closely aligns with our business at Together AI, where consumption is a core part of the model. It's not just about selling credits or access to GPUs. It’s about ensuring customers are actively using and gaining value from the platform over time. Ramp’s ability to blend product, brand, and lifecycle marketing has been a real source of inspiration for how I think about growth in our own space
9. If you had 15 seconds to give an elevator pitch for TogetherAI, what would you say?
Together AI is your full-stack AI platform – from GPU clusters to fine-tuned models to scalable inference endpoints. Whether you're building with open-source, customizing your own models, or deploying at scale, we accelerate every step of your generative AI journey with speed, flexibility, and reliability.
10. How can people learn more information?
Check out Together AI: www.together.ai
1. How do you define “growth” at Together AI — are you focusing on user adoption, revenue, market expansion, model usage, or something else?
At Together AI, growth and marketing is a multi-dimensional concept that includes all of the above. We're operating at the intersection of product-led growth and enterprise sales, which means we need to think about growth in terms of both scale and depth.
On one side, we’re driving adoption through self-serve experiences, model usage, and community engagement. On the other, we’re building relationships and expanding accounts through a more traditional sales motion. We also support a mix of developer, consumer, and enterprise users, so growth means something slightly different across each segment.
Ultimately, growth at Together AI means launching new programs, expanding usage, accelerating time-to-value, and owning the key metrics that tie those activities back to long-term business outcomes like revenue, retention, and market leadership. It’s about moving fast while building in a way that compounds over time.
2. With competitors ranging from hyperscaler GPU clouds to serverless LLM platforms, what’s your core positioning strategy?
Together AI is positioned as the “AI Acceleration Cloud” - a comprehensive, full-stack solution that supports customers at every stage of their AI journey.
Whether you're just beginning to experiment with models or deploying mission-critical applications at scale, we provide the hardware, compute, tools, and flexibility needed to move fast and scale confidently. Unlike point solutions, our integrated stack bridges infrastructure, models, and deployment into a single cohesive platform.
3. Open‑source models like RedPajama and jointly developed research like FlashAttention are pillars of Together’s strategy. How do you use these to drive growth?
Our open-source initiatives are key drivers of both innovation and adoption. Projects like RedPajama and FlashAttention help us earn credibility and visibility within the research and developer communities. They create a flywheel of engagement – developers build with our models, researchers publish on our innovations, and enterprises see a trusted platform backed by cutting-edge work.
Our in-house research team, which includes multiple professor-founders (ex. Chris Re, Percy Liang etc.), plays a central role in sustaining this momentum and reinforcing Together AI as a thought leader in the space.
4. Partnerships like the recent Refuel.ai acquisition add data prep and integration value. How are you activating these in the field?
By integrating Refuel.ai’s specialized models and orchestration capabilities into the Together AI Platform, we’re not only removing one of the biggest roadblocks in AI development – dealing with unstructured, messy data – but also enabling our customers to use their data with greater speed, accuracy, and scale.
The acquisition marks a significant step forward in our mission to accelerate the development of production-grade AI applications.
5. How do you work with infrastructure partners — e.g., cloud, on‑prem deployments, GPU vendors — to scale awareness and adoption?
We view the AI infrastructure landscape as an interconnected ecosystem, not a zero-sum game. Strategic collaboration with hyperscalers, GPU vendors, and on-prem partners is critical to our go-to-market and scaling efforts. These relationships allow us to optimize resource availability, expand global reach, and tailor deployments to meet diverse customer requirements. Whether it's securing GPU supply or integrating with existing enterprise infra, we work hand-in-hand with partners to maximize performance and value for our customers.
6. As open-source demand grows rapidly, how do you ensure scale without compromising performance, support, and infrastructure cost efficiency?
Flexible Deployment Options: You can choose between serverless API endpoints (pay-as-you-go) and dedicated endpoints (reserved capacity with per-minute billing), allowing you to scale your deployment based on your traffic demands.
Horizontal and Vertical Scaling: Together AI offers flexible scaling options to ensure your deployment can handle traffic spikes and growth.
Optimized Inference Engine: Together AI's inference engine is designed for speed and efficiency, enabling fast processing of even complex AI tasks and large-scale deployments.
7. One growth channel you think is under‑leveraged in AI infrastructure today?
Top-of-funnel and brand marketing remain underutilized in AI infrastructure. Many teams focus heavily on bottom-of-funnel channels because they offer direct attribution and measurable ROI. But in a category as new and complex as AI, long-term growth depends just as much on trust and education as it does on performance marketing.
Even with all the attention around AI, we're still in the early days of true enterprise adoption. Buyers are often navigating unfamiliar technology, and they want to work with partners they trust to guide them through that process. A strong brand helps convey that trust. It positions a company as credible, forward-looking, and capable of supporting customers over the long term.
Investing in brand isn't just about visibility – it's about creating a durable advantage in a market where confidence and clarity matter as much as features and price.
8. Role models or mentors who shaped your approach to GTM in this space?
I really admire the team at Ramp and how they’ve managed to transform a traditionally “unsexy” category like corporate cards and payments into one of the most memorable and innovative brands of this decade. They take creative risks, run thoughtful experiments, and aren’t afraid to challenge the status quo. Their approach is confident, original, and highly effective.
What stands out to me is their view of go-to-market as a continuous journey rather than a one-time transaction. That perspective closely aligns with our business at Together AI, where consumption is a core part of the model. It's not just about selling credits or access to GPUs. It’s about ensuring customers are actively using and gaining value from the platform over time. Ramp’s ability to blend product, brand, and lifecycle marketing has been a real source of inspiration for how I think about growth in our own space
9. If you had 15 seconds to give an elevator pitch for TogetherAI, what would you say?
Together AI is your full-stack AI platform – from GPU clusters to fine-tuned models to scalable inference endpoints. Whether you're building with open-source, customizing your own models, or deploying at scale, we accelerate every step of your generative AI journey with speed, flexibility, and reliability.
10. How can people learn more information?
Check out Together AI: www.together.ai
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