Features How It Works About Pricing Contact Start Free Trial
Trusted by 2,000+ ML Engineering Teams

Train AI Models
10× Faster at Scale

Lucidstensor is the enterprise ML training platform that compresses months of model development into days. Distributed training, automated hyperparameter tuning, and one-click deployment — built for serious ML engineers.

10×
Faster Training
2,000+
Teams Worldwide
99.99%
Uptime SLA
$48M
Compute Saved

Trusted by ML teams at leading companies

Anthropic
Stability AI
Cohere
Mistral
Inflection
Adept

Everything you need to
build production AI

From experimental prototypes to billion-parameter production models, Lucidstensor handles every stage of the ML lifecycle with precision and speed.

Distributed Training Engine

Scale training across thousands of GPUs with our fault-tolerant distributed training engine. Supports data parallelism, model parallelism, and pipeline parallelism out of the box.

Multi-GPU · Multi-Node

Automated Hyperparameter Tuning

Our Bayesian optimization engine explores your hyperparameter space intelligently, finding optimal configurations 5× faster than grid search with 40% lower compute cost.

Bayesian · AutoML

Real-Time Experiment Tracking

Monitor every metric, gradient, and artifact in real time. Compare thousands of experiments side-by-side, visualize loss curves, and reproduce any run with a single command.

MLflow Compatible

Model Optimization & Compression

Reduce model size by up to 90% with quantization, pruning, and knowledge distillation — without sacrificing accuracy. Deploy leaner models to edge or cloud in minutes.

INT4 · INT8 · FP16

Enterprise Security & Compliance

SOC 2 Type II certified. Your data and models never leave your VPC. Supports SSO, RBAC, audit logs, and full GDPR/HIPAA compliance for regulated industries.

SOC 2 · HIPAA · GDPR

Native Framework Integrations

First-class support for PyTorch, JAX, TensorFlow, and Hugging Face Transformers. Zero-config integration — just wrap your existing training script and go.

PyTorch · JAX · HuggingFace

Elastic Compute Orchestration

Dynamically provision and release GPU clusters. Spot instance integration cuts compute costs by up to 70%. Automatic checkpointing ensures no work is lost on preemption.

Spot Instances · Auto-scaling

Model Registry & Versioning

Centralized model registry with full version control, lineage tracking, and automated CI/CD pipelines. Promote models from staging to production with one-click approval workflows.

CI/CD · Lineage Tracking
10×
Faster model training vs. baseline
70%
Reduction in compute costs
4.2B+
Parameters trained monthly
99.99%
Platform uptime SLA

From code to production
in four steps

No infrastructure headaches. No DevOps rabbit holes. Just fast, reproducible model training that scales with your ambitions.

01

Connect Your Code

Install our lightweight SDK (pip install lucidstensor) and wrap your existing training script. No rewrites required.

02

Configure Your Run

Define compute resources, hyperparameter search spaces, and experiment configs via YAML or our visual dashboard. Launch with a single command.

03

Train at Scale

Our engine automatically distributes your workload, manages checkpointing, and surfaces real-time metrics as your model trains across your cluster.

04

Deploy & Monitor

Register your best model, run automated evaluations, and deploy to any cloud or on-prem environment with built-in A/B testing and performance monitoring.

Built by ML engineers,
for ML engineers

Founded in 2021, Lucidstensor was born out of frustration with fragmented, overcomplicated ML tooling. Our team of former Google Brain, DeepMind, and OpenAI researchers built the platform they always wished existed — one that treats ML engineers as first-class citizens.

  • Headquartered in San Francisco with offices in New York and London
  • Backed by $62M in Series B funding from Sequoia Capital and a16z
  • Team of 120+ engineers and researchers across 18 countries
  • Processing over 4.2 billion parameters in training jobs monthly
  • SOC 2 Type II, ISO 27001, GDPR, and HIPAA compliant infrastructure

Leadership Team

AK

Arjun Kapoor

CEO & Co-Founder
Ex-Google Brain

SC

Sarah Chen

CTO & Co-Founder
Ex-DeepMind

MR

Marcus Rivera

VP Engineering
Ex-OpenAI

"

We started Lucidstensor because we spent more time fighting infrastructure than doing actual ML research. We fixed that — for everyone.

— Arjun Kapoor, CEO

Loved by ML engineering teams

Don't take our word for it. Here's what production ML engineers say about training with Lucidstensor.

"

"We cut our LLM fine-tuning time from 3 weeks to 4 days using Lucidstensor's distributed training. The automated hyperparameter search alone saved us $180K in compute last quarter. It's become the backbone of our entire ML infrastructure."

DL
Dr. David Liu
Head of ML Engineering · Synthesis AI
"

"The model registry and CI/CD integration transformed how our team ships models. We went from ad-hoc deployments to a rigorous, reproducible pipeline in two weeks. Our production incident rate dropped by 80%. Absolutely game-changing tooling."

JP
Jessica Park
Principal ML Engineer · NovaTech Labs
"

"As a regulated financial firm, security was our #1 concern. Lucidstensor's VPC deployment, audit logs, and SOC 2 certification gave our compliance team full confidence. We've now trained 40+ production models without a single security incident."

RM
Robert Mitchell
Director of AI · Apex Financial Group

Frequently asked questions

Everything you need to know about Lucidstensor. Can't find your answer? Contact our team.

What frameworks and hardware does Lucidstensor support?

Lucidstensor natively supports PyTorch (1.12+), JAX/Flax, TensorFlow 2.x, and Hugging Face Transformers. On the hardware side, we support NVIDIA A100, H100, V100, A10G GPUs, AMD MI250, and Google TPU v3/v4 pods. We also support multi-cloud deployments across AWS, GCP, Azure, and on-premises clusters via our Kubernetes operator.

How does billing work? Are there hidden costs?

Pricing is fully transparent. The platform fee covers all Lucidstensor features — there are no surprise charges for features, API calls, or seats. Compute costs are billed separately at cloud provider rates (we pass through at cost with no markup). Enterprise customers can bring their own cloud accounts (BYOC) to use their committed spend and reserved instances. We publish a full pricing breakdown in our docs.

How does Lucidstensor handle data privacy and model security?

Your data and model weights never leave your environment. Lucidstensor can be deployed entirely within your VPC (Virtual Private Cloud) with no data egress. We are SOC 2 Type II certified, ISO 27001 certified, and HIPAA-compliant. All communication is encrypted in transit (TLS 1.3) and at rest (AES-256). We support SSO (SAML 2.0, OIDC), RBAC, and full audit logging. Our security whitepaper is available on request.

Can I migrate existing experiments and models from other platforms?

Yes. We provide migration tooling and dedicated support for moving from Weights & Biases, MLflow, Comet, Neptune, and SageMaker. Our import CLI can ingest existing experiment metadata, model artifacts, and training histories. For Enterprise customers, we offer a white-glove migration service at no additional cost, including data validation and pipeline reconstruction by our ML platform engineers.

What kind of support do you offer?

All paid plans include email support with a 24-hour SLA. Growth plans add live chat with 4-hour SLA during business hours. Enterprise plans include a dedicated Customer Success Engineer, 1-hour critical incident SLA, quarterly business reviews, and direct access to our engineering team via Slack Connect. We also maintain extensive documentation, tutorials, and a community forum with 12,000+ active members.

Is there a free trial? What's included?

Yes — we offer a full-featured 14-day free trial with no credit card required. The trial includes access to all platform features, $200 in free GPU compute credits, up to 5 concurrent training runs, full experiment tracking and model registry access, and email support. After the trial, you can continue on our free Starter tier (limited to 2 runs/month) or upgrade to a paid plan. No features are locked behind paywalls during the trial.

How does Lucidstensor compare to SageMaker or Vertex AI?

Unlike SageMaker and Vertex AI, Lucidstensor is cloud-agnostic and designed specifically for training workloads rather than serving as a general-purpose cloud ML service. We offer 3–5× faster job startup times, a significantly better developer experience with our SDK and CLI, and no vendor lock-in. Our distributed training engine outperforms both platforms on large model training benchmarks. We also provide much deeper experiment tracking, model comparison, and hyperparameter optimization capabilities out of the box.

Simple, transparent pricing

Start free, scale as you grow. No hidden fees, no surprise bills. All plans include a 14-day free trial.

Starter
$0/month
For individual ML engineers exploring the platform.
  • 2 concurrent training runs
  • 10 GB model storage
  • Basic experiment tracking
  • Community support
  • PyTorch & TensorFlow support
Enterprise
Custom pricing
For large organizations with advanced security and scale requirements.
  • Unlimited concurrent runs
  • Unlimited storage
  • VPC deployment (BYOC)
  • SOC 2 / HIPAA compliance
  • Dedicated CSE & Slack Connect
  • Custom SLAs & contracts
  • On-premises option

Let's talk about
your ML stack

Whether you're evaluating Lucidstensor, need a custom enterprise quote, or just want to geek out about distributed training — our team is ready to help.

Address 535 Mission Street, Floor 14
San Francisco, CA 94105
Phone +1 (415) 802-7340
Business Hours Monday – Friday, 9am – 6pm PST

Send us a message

We typically respond within 4 business hours.

By submitting, you agree to our Privacy Policy.

✓ Message sent! We'll be in touch within 4 hours.