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Synthetic Sciences - AI Orchestration and MLOps Tool

AI Orchestration and MLOps · Founded by Aayam Bansal

Synthetic Sciences

Synthetic Sciences

Delegate literature reviews, train models, manage gpus, and write latex papers — ai agents that do the work for you.

Cost

Paid

Rating

Mixed Reviews

Time to value

Quick Setup (< 1 hour)

You can use Synthetic Sciences to delegate scientific research tasks to AI agents that can conduct literature reviews, train machine learning models on cloud GPUs, design experiments, and generate publication-ready LaTeX papers. The tool provides four specialized modes for different research needs, manages your credentials across all sessions, orchestrates GPU clusters, and maintains persistent workflows that continue running even when you're offline.

What Synthetic Sciences does

Train DeepSeek models on distributed GPU clustersGenerate structured research hypotheses from initial ideasSynthesize findings from hundreds of academic papersCreate camera-ready LaTeX documents with verified citationsRun protein folding simulations and analysisDesign A/B tests for machine learning experimentsQueue multiple training runs across different compute providersBuild automated model evaluation and comparison pipelinesFour specialized research modes for different scientific domainsPersistent AI agents that continue working offlineAutomatic credential sync across all sessions and agentsGPU cluster orchestration across multiple cloud providersPublication-ready LaTeX document generationIntegrated literature review and model training workflowsSandboxed runtime environments with full checkpointingLong-horizon reinforcement learning for research tasks

Pricing breakdown

PlanPrice10 seats / yr
Plus$50.00 / mo$6,000
Pro$200.00 / mo$24,000

Annual estimates assume continuous billing at the listed list price. Volume discounts typical above 50 seats.

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Synthetic Sciences, AI research agents, scientific research automation, GPU orchestration, literature review, model training, LaTeX papers, computational biology, machine learning workflows, Y Combinator, research execution, experiment design, scientific writing, cloud compute, research infrastructure