Sold by: PremÂ
Deployed on AWS
Create private, domain-specific Small Language Models (SLMs) with no ML expertise. Our platform provides an end-to-end pipeline for fine-tuning and evaluation.
Overview
A platform that allows teams to create domain-specific Small Language Models (SLMs) without deep machine-learning expertise.
- For: Enterprises that need private, high-performance AI models tailored to their specific domain without a large in-house ML team.
- Core Value: Turns complex model customization into a manageable, repeatable process.
- Key Features: End-to-end data pipeline (with synthetic data generation), flexible fine-tuning, built-in evaluation, and one-click deployment to your own secure infrastructure (VPC/on-prem).
Highlights
- Fine-tune large language models on your data with no AI expertise required
- Use AI to augment small datasets and improve training outcomes
- Test and deploy models through an integrated chat UI and API access
Details
Sold by
Delivery method
Deployed on AWS
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Features and programs
Financing for AWS Marketplace purchases
AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.
Pricing
Pricing is based on actual usage, with charges varying according to how much you consume. Subscriptions have no end date and may be canceled any time.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Description | Cost/unit |
|---|---|---|
LoRA FT Unit Experiment | Lightweight fine-tuning job using LoRA | $0.00000001 |
Full FT Unit Experiment | Standard full fine-tuning job | $0.00000001 |
GRPO FT Unit Experiment | Full FT with reasoning (GRPO) for complex tasks | $0.00000001 |
External LLM Unit Request | External model call measured per request | $0.00000001 |
Internal LLM Unit Request | Internal model call measured per request | $0.00000001 |
Data Augmentation Unit | Single augmented datapoint for training | $0.00000001 |
Evaluation Unit | Model evaluation on a single datapoint | $0.00000001 |
Prem Credit | Credits are consumed based on the service used | $1.00 |
Vendor refund policy
Refunds are generally not offered due to the minimal cost per unit. However, if you encounter any issues or discrepancies, please contact us at info@premai.io to discuss your case. We evaluate refund requests individually and are committed to ensuring customer satisfaction.
Legal
Vendor terms and conditions
Upon subscribing to this product, you must acknowledge and agree to the terms and conditions outlined in the vendor's End User License Agreement (EULA)Â .
Content disclaimer
Vendors are responsible for their product descriptions and other product content. AWS does not warrant that vendors' product descriptions or other product content are accurate, complete, reliable, current, or error-free.
Delivery details
Software as a Service (SaaS)
SaaS delivers cloud-based software applications directly to customers over the internet. You can access these applications through a subscription model. You will pay recurring monthly usage fees through your AWS bill, while AWS handles deployment and infrastructure management, ensuring scalability, reliability, and seamless integration with other AWS services.
Support
Vendor support
For support, email info@premai.io . For enterprise customers or critical issues, dedicated channels are available upon request.
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
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Customer reviews
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1 external reviews
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reviewer2760291
Has accelerated AI solution development through automated evaluation and fine-tuning
Reviewed on Sep 29, 2025
Review provided by PeerSpot
What is our primary use case?
I use Prem Studio to automate fine-tuning and evaluation of AI solutions.
How has it helped my organization?
Prem Studio allowed me to easily automate and solve the complicated problem of exploring and identifying the best AI architecture for our problems. Prem Studio has a straightforward yet powerful approach to evaluate disparate AI architectures on our business problems and to accurately fine-tune the most promising ones.
This significantly reduced time-to-market, almost by a factor of ten in my case, for solutions tailored and optimized for customer requirements and KPIs.
What is most valuable?
The most valuable features of Prem Studio are evaluation, fine-tuning, and experiment design.
What needs improvement?
Prem Studio is perfect for text input and output. We requested support for vLM, which should be available soon.
For how long have I used the solution?
I have been using the solution for 3 months.
What was my experience with deployment of the solution?
I did not experience any deployment issues.
What do I think about the stability of the solution?
I did not encounter any stability issues.
What do I think about the scalability of the solution?
I did not experience any scalability issues.
How are customer service and support?
I did not interact with customer service.
Which solution did I use previously and why did I switch?
Before Prem Studio, I used FireworksAI and adaptive-ml.com, but they were too brittle and rigid. It was difficult to update experiments given the new models and architectures that constantly emerge. Finetunedb is very low-level if you have to make it work for real.
How was the initial setup?
The initial setup was straightforward and did not present any challenges.
What about the implementation team?
The implementation was handled internally.
What was our ROI?
I have observed significant value in terms of reduced time-to-market, although I have not formally calculated the ROI.
What's my experience with pricing, setup cost, and licensing?
To maximize the effectiveness of fine-tuning, I would suggest using the parallelism features of the platform. This allows fine-tuning and evaluating multiple models at the same time, making comparisons more informative and helping to choose the best configuration among a representative set of models.
Which other solutions did I evaluate?
I considered and used FireworksAI, adaptive-ml.com, finetunedb.com, Claude, ChatGPT, Optuna, and Neptune.ai.
What other advice do I have?
If you want specific features, I recommend contacting the Prem Studio team since they are happy to listen to your needs.