Researchers lost months debugging network failures. Bare-metal clusters ended the crashes and enabled custom orchestration.
The creator of a frontier AI model for customer experience builds specialized systems for regulated sectors like banking and healthcare to ensure deterministic behavior and compliance.
Training runs longer than a few hours frequently failed due to networking issues, while standard managed platforms lacked the bare-metal access...
“We spent 3-4 months blocked by infrastructure failures with previous providers—debugging networking issues that had nothing to do with our models. Together AI's cluster has had zero training-blocking issues since we switched. That reliability, combined with significant cost savings compared to other providers, completely changed our development velocity. But honestly, the responsive support is what keeps us here: shared Slack channel, problems resolved within hours, smooth scaling of our training cluster as our needs have been expanding. Together AI lets us focus on building breakthrough models instead of fighting infrastructure.”
Conversational AI platform for automated enterprise customer experience.
AI-native cloud platform for training, fine-tuning, and deploying open-source models.
Scaled Cognition's AI model training is part of this use case:
Related implementations across industries and use cases
Open datasets age on Wikipedia while real questions live on the web. Training on their own web graph taught the model to reason, not loop.
Multi-step research ran one search at a time, burning tokens on extended reasoning. Astra takes fewer steps and fans work across sub-agents.
Isolating data for 50,000 clients was operationally impossible. Multi-tenancy now serves 6.1M queries from a single instance.
Open datasets age on Wikipedia while real questions live on the web. Training on their own web graph taught the model to reason, not loop.
Isolating data for 50,000 clients was operationally impossible. Multi-tenancy now serves 6.1M queries from a single instance.
Campaign variants took 2 days; no shared customer view. AI now orchestrates audience, journeys, and creative while marketers steer outcomes.
On-chain AI agents took weeks of stitching and ran trapped on local machines. BNB Agent Studio ships them globally in 15 minutes.
Tournaments running simultaneously meant an hour of manual checks each. AI agents now run them in minutes, freeing the team to be proactive.
Large AI training jobs meant fighting for preemptible slots or leaving campus. Marlowe gave any lab guaranteed multi-node access on demand.
Researchers lost months debugging network failures. Bare-metal clusters ended the crashes and enabled custom orchestration.
The creator of a frontier AI model for customer experience builds specialized systems for regulated sectors like banking and healthcare to ensure deterministic behavior and compliance.
Training runs longer than a few hours frequently failed due to networking issues, while standard managed platforms lacked the bare-metal access...
“We spent 3-4 months blocked by infrastructure failures with previous providers—debugging networking issues that had nothing to do with our models. Together AI's cluster has had zero training-blocking issues since we switched. That reliability, combined with significant cost savings compared to other providers, completely changed our development velocity. But honestly, the responsive support is what keeps us here: shared Slack channel, problems resolved within hours, smooth scaling of our training cluster as our needs have been expanding. Together AI lets us focus on building breakthrough models instead of fighting infrastructure.”
Conversational AI platform for automated enterprise customer experience.
AI-native cloud platform for training, fine-tuning, and deploying open-source models.
Scaled Cognition's AI model training is part of this use case:
Related implementations across industries and use cases
Open datasets age on Wikipedia while real questions live on the web. Training on their own web graph taught the model to reason, not loop.
Multi-step research ran one search at a time, burning tokens on extended reasoning. Astra takes fewer steps and fans work across sub-agents.
Isolating data for 50,000 clients was operationally impossible. Multi-tenancy now serves 6.1M queries from a single instance.
Open datasets age on Wikipedia while real questions live on the web. Training on their own web graph taught the model to reason, not loop.
Isolating data for 50,000 clients was operationally impossible. Multi-tenancy now serves 6.1M queries from a single instance.
Campaign variants took 2 days; no shared customer view. AI now orchestrates audience, journeys, and creative while marketers steer outcomes.
On-chain AI agents took weeks of stitching and ran trapped on local machines. BNB Agent Studio ships them globally in 15 minutes.
Tournaments running simultaneously meant an hour of manual checks each. AI agents now run them in minutes, freeing the team to be proactive.
Large AI training jobs meant fighting for preemptible slots or leaving campus. Marlowe gave any lab guaranteed multi-node access on demand.