Sold by: Trellis Data
Deployed on AWS
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Leverage Trellis Data's expertise in fine-tuning AI for translation and transcription. Our specialists design and optimize models to handle bespoke languages and dialects, delivering accurate, context-aware results where off-the-shelf tools fall short.
Overview
Trellis Data addresses the limitations of off-the-shelf translation and transcription tools by developing custom AI solutions capable of understanding and processing bespoke languages.
We create production ready models that bridge the gap where mainstream options fall short, equipping enterprises, government agencies, and high-security organizations with language solutions tailored to their unique needs and use cases.
We specialize in training, fine-tuning, and optimizing speech-to-text AI models, ensuring accurate output for niche, low-resource, or specialized languages. Our models are designed to deliver optimal results, while providing the linguistic accuracy and cultural sensitivity required for mission-critical applications.
Our models are already deployed and trusted by law enforcement and high security agencies in Government.
Highlights
- Accurate speech transcription for Bahasa Indonesian
Details
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Delivery method
Latest version
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
Free trial
Try this product free for 5 days according to the free trial terms set by the vendor.
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/host/hour |
|---|---|---|
ml.m5.xlarge Inference (Batch) Recommended | Model inference on the ml.m5.xlarge instance type, batch mode | $1.59 |
ml.g4dn.xlarge Inference (Real-Time) Recommended | Model inference on the ml.g4dn.xlarge instance type, real-time mode | $2.39 |
ml.g5.xlarge Inference (Real-Time) | Model inference on the ml.g5.xlarge instance type, real-time mode | $3.03 |
ml.g6.xlarge Inference (Real-Time) | Model inference on the ml.g6.xlarge instance type, real-time mode | $1.59 |
Dimensions summary
You pay by the hour for the compute instance that runs the Indonesian speech transcription model. Pricing is split by how the model processes audio. One option runs on an ml.m5.xlarge instance in batch mode, which handles pre-recorded audio in bulk. Three options run in real-time mode on ml.g5.xlarge, ml.g4dn.xlarge, and ml.g6.xlarge instances, which process audio as it streams. You choose the instance based on your workload and processing speed needs. Charges accrue for each hour an instance stays running.
Top-of-mind questions for buyers
You pay for each hour an instance stays running, billed per host-hour. Charges accrue while the instance is active, whether or not audio is being processed. The software meters running time. Stopping the instance stops the software charges, though underlying AWS storage fees may still apply.
The ml.m5.xlarge batch option processes pre-recorded audio in bulk. The three real-time options (ml.g5.xlarge, ml.g4dn.xlarge, ml.g6.xlarge) process audio as it streams. All bill per host-hour. Choose batch for stored files processed together, or a real-time GPU instance for live streaming workloads.
Yes. Each running instance bills separately per host-hour. If you run multiple instances, charges add up across all active hosts. The platform supports scaling processing up or down and load balancing across locations to match changing demand.
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Vendor refund policy
Refund Policy (Effective: 09/10/2026) Refunds for Trellis Data Speech Transcription models may be granted for technical issues unresolvable by support, billing errors, or duplicate charges. Services already rendered, custom configurations, or costs from customer misuse or misconfiguration are non-refundable. This policy operates per AWS Marketplace terms. Contact: support@trellisdata.com.au (9AM-5PM AEDT, weekdays). Policy subject to updates.
Legal
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Content disclaimer
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Delivery details
Amazon SageMaker model
An Amazon SageMaker model package is a pre-trained machine learning model ready to use without additional training. Use the model package to create a model on Amazon SageMaker for real-time inference or batch processing. Amazon SageMaker is a fully managed platform for building, training, and deploying machine learning models at scale.
Deploy the model on Amazon SageMaker AI using the following options:
Version release notes
- Support for Sagemaker Invocations
Additional details
Inputs
- Summary
Supports file inputs with the following media types ['audio/wav', 'audio/mpeg']. For files larger than 30 seconds the model will split the audio into 30 second chunks for processing and provide the output per chunk.
Please include the content-type when sending a file for inference. See sample notebooks linked.
https://github.com/Trellis-Data/sagemaker-samples/tree/main/asr/data/input/real-time
https://github.com/Trellis-Data/sagemaker-samples/tree/main/asr/data/input/real-time
Input data descriptions
The following table describes supported input data fields for real-time inference and batch transform.
Field name | Description | Constraints | Required |
|---|---|---|---|
ContentType | Please specify a valid content type matching the file being uploaded. One of ['audio/wav', 'audio/mpeg'] | - | No |
Support
Vendor support
Email our team at: support@trellisdata.com.au
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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