The Best AI is Built, Not Bought
Train, inference, and continuously improve any model.
"AI has long been core to how DoorDash helps merchants succeed. By encoding our quality standards directly into model training, we scaled our internal expertise and raised the bar on menu accuracy on the platform."
Andy Fang
Co-Founder, CTO at DoorDash
"The training recipe was precisely tailored to our product and use case. Applied Compute's approach to dataset, environment, and harness construction gave us confidence that the model would perform well in the production setting with real users."
Moritz Stephan
Engineering Lead, Cognition
"We need to know that the data we’re creating actually makes models better. Applied Compute gives our engineers everything they need for post-training and inference, with the flexibility to use our own harnesses and configurations. It’s powerful infrastructure that is developer friendly."
Garret Lord
Co-Founder, CEO at Handshake
"Applied Compute achieving frontier capabilities on APEX Agents with just 2,000 tasks is incredible."
Brendan Foody
Co-Founder, Co-CEO at Mercor
"Applied Compute's platform gives us the high-performance training infrastructure we need to run large-scale RL inside a custom legal-agent harness. Their research team brought deep expertise across training, evaluation, and task design, helping us turn our legal data into a state-of-the-art model on our Legal Agent Benchmark."
Gabe Pereyra
Co-Founder, President at Harvey
"Our AI agents handle live customer conversations, so inference has to be fast and dependable. We are excited to partner with Applied Compute as we scale our own trained models in production."
Cyrus Asgari
Research Engineer, Decagon
"With AC2, we’re using years of our labeled security findings to post-train models. The result is agents that understand our internal vulnerability-tracing tools, higher accuracy at a fraction of the cost, and a sovereign model that keeps improving as our data and tools evolve."
Drew Dennison
Co-Founder, CTO at Semgrep
"Scientifically reliable agents require robust benchmarks. Applied Compute helped us better understand how well our benchmarks map to practical tasks, allowing us to further improve agents on biology."
Kenny Workman
Co-Founder, CTO at Latch Bio
"AI has long been core to how DoorDash helps merchants succeed. By encoding our quality standards directly into model training, we scaled our internal expertise and raised the bar on menu accuracy on the platform."
Andy Fang
Co-Founder, CTO at DoorDash
"The training recipe was precisely tailored to our product and use case. Applied Compute's approach to dataset, environment, and harness construction gave us confidence that the model would perform well in the production setting with real users."
Moritz Stephan
Engineering Lead, Cognition
"The training recipe was precisely tailored to our product and use case. Applied Compute's approach to dataset, environment, and harness construction gave us confidence that the model would perform well in the production setting with real users."
Moritz Stephan
Engineering Lead, Cognition
“There should be as many models in the world as there are firms.”
Satya Nadella, Chairman and CEO of Microsoft, discusses the future of enterprise AI and model ownership with our CEO, Yash Patil.
Built and used every day by frontier researchers
AC2 is one unified platform to train, serve, and continuously improve models you own, with our researchers working beside your engineers.
Train it. Serve it.
Improve it.
Our team of frontier lab veterans and applied research engineers help you train custom models on your data, deploy them at scale, and improve them continuously.
Scalable infrastructure for better, faster, cheaper models.
Post-train tool-using, long-horizon agents.Train across text, images, code, and structured data on a state-of-the-art stack using your own harness and graders.
Optimize your models towards your evals.Calibrate rewards to your product KPIs and domain expertise. Inspect what your model is learning with rollout-level observability.
Stay model-flexible.Train from the best available base models, then upgrade as stronger ones ship without changing your harness, data pipeline, or deployment stack.
Flexible, production grade inference in seconds
Serve in the harness you trained in.Move from training to production with zero train-to-deployment mismatch.
Optimize for any production workload.Configure deployments around the throughput, latency, and concurrency your product needs, from asynchronous agents to real-time user experiences.
Promote checkpoints to production instantly.Deploy your latest model as soon as it is ready, with replicas that spin up in seconds.
Models that get better the more they are used
Transform real usage into training data.Mine training data and reward signals directly from production traces to continually improve your model.
Improve deployments with real-time training.Attach your production inference endpoints to a training runtime. Update deployments online as real user feedback comes in using online RL and self-distillation.
Fearlessly roll out deployments with monitoring and observability.Directly run A/B tests with release candidates, and roll out production model updates frequently and with confidence.
Deployed with you from day one
Our team has pioneered RL post-training, long-horizon agents, and continual learning at frontier labs.
Embedded
We sit with your engineers, from co-designing the first eval, to deploying the model and beyond.
Managed
Your team designs and runs experiments. We manage the training, serving, and infrastructure load.
Your data. Your model. Your edge.
Built for the most security-conscious customers in AI, enterprise, and the public sector.
SOC 2 Certified
ISO 42001 CertifiedData never leaves your perimeter
Choose serverless or a VPC deployment based on the control you need.
Full access and audit
Role-based access control, audit logs on every dispatch, lifecycle automation for checkpoints, datasets, and artifacts.
You own the intelligence
The model is yours. You decide what trains, what deploys, and what memory is retained. Opt out of training any time.
News and Research
Enriching Domain-Specific Post-Training with Multi-Teacher On-Policy Distillation
Train your own decision model in AC2
Scaling On-Policy Self-Distillation with Hint Auto-Optimization