Deploy fine-tuned models for reasoning, research, and writing that accelerate insights, maintain context, and help teams make smarter decisions while cutting overhead
Most AI tools lose context, miss domain expertise, and create costly manual overhead, slowing research, collaboration, and decision-making while driving wasted spend and competitive lag
Assistants often lose track of multi-step queries, producing incomplete or inaccurate responses
Generic outputs ignore enterprise standards, forcing manual review and increasing risk
Off-the-shelf models fail under high concurrency and low-latency requirements, driving up infrastructure costs and slowing teams
Deploy fine-tuned, scalable AI that understands your organization’s workflows, accelerates insights, and delivers structured, context-aware outputs
Synthesize literature and internal documents instantly into actionable summaries and insights
Maintain context across multi-step workflows, delivering precise, reliable outputs at scale
Multi-line suggestions delivered as developers type, reducing context switching and accelerating iteration
Enable multi-agent, multi-query workflows with sub-2s latency, keeping teams productive at enterprise scale
Train models on internal data to enforce standards, improve accuracy, and accelerate decision-making
Scale securely and cost-effectively with GPU autoscaling, high throughput, and predictable performance under load
Built with long context windows, high throughput, and fine-tuning flexibility, these production-ready models help teams turn research into action, streamline collaboration, and accelerate decision-making. They support multi-step reasoning, multi-agent workflows, and internal knowledge synthesis, delivering accurate, consistent outputs aligned with enterprise standards and brand voice
Always-on, real-time AI keeps global teams productive
Lower infrastructure costs while scaling high-concurrency workflows
Proven to launch and scale seamlessly at viral demand
Deliver business value faster with production-ready AI
Sentient scaled to 1.8M users in 24 hours, maintaining sub-2s latency across 15-agent workflows with 50% higher throughput per GPU, all while keeping infrastructure efficient and cost-effective
Fireworks Conversational AI drives smarter decisions, faster workflows, and clearer insights
